There has been talk of "rescheduling" cannabis for years, a regulatory move that would significantly ease federal restrictions on the drug. Now, with a recent push from the White House to expedite the rescheduling process, we may see that change come to pass.

Moving cannabis to Schedule III — a less-restrictive classification for drugs — would represent a very important shift in how the federal government treats cannabis research, in that it would officially state that cannabis has medical use. This landmark decision would encourage some of the largest scientific investment in cannabis research to date and help build some of the strongest evidence of the value of cannabis-based therapies.

However, the move to Schedule III should be viewed as a transition rather than an endpoint.

How cannabis is regulated, today

Cannabis has existed in a complicated space in medicine, policy and public perception for decades.

More than 6 million Americans are registered to use cannabis through state medical programs. Clinicians participating in state medical cannabis programs generally "certify" and "recommend" specific cannabis products to certain patients, rather than write traditional prescriptions. Additionally, a handful of cannabis-derived and cannabinoid-based medications have received formal Food and Drug Administration (FDA) approval.

However, since the Controlled Substances Act was enacted in 1970, cannabis has been classified as a Schedule I substance. This category is associated with the highest level of restriction, including substances such as heroin, MDMA, and LSD.

Under federal law, Schedule I drugs are defined as having a high potential for abuse and no currently accepted medical use. Given some cannabis-derived drugs are FDA approved, it may seem contradictory that cannabis remains a Schedule I substance. The key is that federal drug scheduling, FDA drug approval and state cannabis laws are separate legal and regulatory systems.

Federal law classifies cannabis as a Schedule I drug. Separately, the FDA evaluates and approves individual cannabinoid medications for specific medical conditions. Independently, states can authorize cannabis for medical or adult use under their own laws, even though cannabis remains illegal under federal law.

This three-tiered regulatory landscape can be confusing for patients, clinicians and the general public alike.

Rescheduling would be a boon for research

For a few years, federal officials have recommended moving cannabis to Schedule III, which includes drugs with accepted medical uses that are subject to fewer federal restrictions. Ketamine and anabolic steroids, like testosterone, are examples. Compared with Schedule I substances, Schedule III drugs are considered to have a lower potential for abuse and can be prescribed for accepted medical uses under federal law.

Rescheduling cannabis would thus create a regulatory environment that's more favorable to research, which could support the development of future FDA-approved cannabis-based medicines. Researchers are already exploring cannabinoids as potential treatments for conditions including chronic pain, post-traumatic stress disorder, inflammatory bowel disease and sleep disorders, but the available evidence remains limited for many uses.

Evidence is limited, in part, because for decades researchers studying cannabis have faced regulatory hurdles that extend beyond those encountered with many other controlled substances.

Studies using cannabis often require additional federal, institutional and local approvals, compared to research with less-restricted drugs. They have extra requirements around securely storing and handling cannabis. They require detailed record-keeping to document how research materials are received, stored and used, as well as Drug Enforcement Administration registration for the principal investigator conducting Schedule I research.

Additionally, federal restrictions have historically limited researchers' access to cannabis products that reflect those people regularly use, such as commercially available flower, vape products and edible formulations.

This regulatory burden has historically discouraged some universities, healthcare systems and funding organizations from investing in cannabis research. These hurdles have made cannabis studies slower, more costly and smaller in scale than those conducted with more loosely controlled drugs.

Shifting cannabis to Schedule III would help to reduce these barriers, opening opportunities for more universities and healthcare systems to conduct much-needed clinical studies for medical cannabis. It could help researchers conduct the larger, more rigorous clinical trials needed to determine which therapies are truly safe and effective — and which are not.

Such gold-standard studies would better evaluate cannabis' potential benefits and risks, as well its effects in specific medical conditions and appropriate dosing for each. This evidence could, in turn, help reduce the stigma associated with cannabis use.

What rescheduling won't accomplish

Rescheduling cannabis will not automatically make cannabis more accessible to patients or immediately establish where cannabis is beneficial, what doses are most appropriate or which patients are most likely to benefit.

It would not automatically convert existing state cannabis programs into the conventional prescription model used for most Schedule III drugs. And it would not immediately resolve the complexities surrounding state medical cannabis programs, which operate outside the traditional FDA-approved medication pathway.

Unlike most prescription drugs, medical cannabis is an umbrella term that includes hundreds of products that differ in cannabinoid content, formulation, dose and route of administration. Most of those products have not been approved by the FDA, so rescheduling would not automatically place them into the traditional prescription drug system or immediately resolve many of the financial and access barriers patients face when trying to use them.

Without robust follow-up research, rescheduling alone would do little to resolve the uncertainty surrounding many cannabis products.

In short, the greatest benefit of moving cannabis to Schedule III would not be the policy change itself; it would be the opportunity to build a stronger evidence base for cannabis science and medicine. Policymakers may open the door to Schedule III, but researchers, clinicians and regulatory agencies will determine whether this opportunity will actually lead to the appropriate and meaningful advances in cannabis science and medicine.

The value of rescheduling will be measured not by how quickly it changes patients' access to cannabis, but by whether it helps create the scientific foundation needed to guide responsible medical use.

This article is for informational purposes only and is not meant to offer medical advice.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

In the weeks around the 2026 annual meeting of the American Society of Clinical Oncology, my phone kept buzzing with alerts about GLP-1 drugs and cancer. The headlines were everywhere — from NPR and The Washington Post to Substack and heated exchanges on social media — all circling the same claim: Ozempic might lower the risk of cancer.

Behind those headlines is a real wave of studies, involving millions of patients. I'm a physician and clinical epidemiologist, and my team and I design and interpret these same kinds of studies that test what widely used drugs actually do.

The excitement around the idea that GLP-1 drugs can prevent cancer is running well ahead of the evidence. Not wrong, necessarily. Just not yet earned.

Cancer is among the hardest things to study, because it is not one disease but more than a hundred. Breast cancer, lung cancer and blood cancers are not variations of the same disease; each has its own distinct biology and its own mix of genetic, environmental and behavioral risks.

A single drug never gets one verdict on how it affects cancer. It gets a hundred, raising the risk of some, lowering it for others and leaving most untouched.

The early cancer concerns

Before the current buzz that GLP-1 drugs could reduce cancer risk, the worry ran in the opposite direction: that they might raise cancer risk.

Researchers were originally concerned about thyroid cancer. Studies in rodents found that Ozempic caused thyroid C cell tumors, which is why U.S. regulators added a black box warning in June 2026 to the drug that advises against its use among those with a personal or family history of related conditions.

But rodents are not people. Human thyroid C cells are less sensitive to GLP-1 drugs compared to rodent C cells because they have far fewer GLP-1 receptors. Long-term studies in monkeys did not show the same abnormal thyroid cell growth seen in rodents.

A 2025 analysis of data from 93 clinical trials found no clear link between taking certain GLP-1 drugs and thyroid cancer. European regulators reached the same conclusion in 2023 after reviewing available research on GLP-1s.

Pancreatic cancer was another concern. Here, too, researchers found no consistent increased risk from taking GLP-1 drugs in a 2025 analysis of data from 62 studies.

The reassurance is real but provisional. These drugs are young, and cancer can take decades to surface.

The cancer story turns on its head

GLP-1 drugs, once scrutinized for possibly causing cancer, are now being discussed as drugs that might prevent or even treat cancer.

A 2024 study of more than 1.6 million people with Type 2 diabetes found lower rates of 10 out of 13 obesity-related cancers in people treated with a GLP-1 drug compared to insulin.

A 2025 study of about 87,000 adults found that overall cancer rates among those who started a GLP-1 drug were roughly 17% lower, with the clearest reductions in endometrial and ovarian cancers as well as a type of brain cancer called meningioma. The risk of kidney cancer was 38% higher among patients taking GLP-1 drugs, though larger studies are needed to confirm its significance.

A 2026 study of more than 110,000 women undergoing breast imaging found a roughly 30% lower risk of breast cancer among those who use GLP-1 drugs compared to those who do not.

Researchers are also studying how GLP-1 drugs affect a patient's chances of surviving cancer. Among more than 6,800 colon cancer patients in a 2024 study, around 16% of the 103 on a GLP-1 drug died within five years compared to 37% of those who were not taking one. A study presented at the 2026 American Society of Clinical Oncology reported a 34% lower risk of death across six cancer types for those taking GLP-1 drugs.

Why the evidence is so easy to misread

While these findings are exciting, studies on the effects of GLP-1 drugs on cancer risk have three features that make them especially easy to misread.

The first is healthy user bias. People who start a GLP-1 drug tend to be healthier and wealthier than those who do not. A person with obesity who has insurance, sees doctors regularly and can afford Ozempic is far more likely to start the drug than someone with the same height and weight who lacks those advantages.

Healthy user bias is very difficult to scrub out of observational studies, which compare people as they are treated in real life rather than assigning the drug at random. The very advantages that made it possible to receive a GLP-1 prescription, not the drug itself, may be what lowered a patient's cancer risk.

The second is the choice of the comparison drug. To understand the effect of a drug, it has to be measured against something else. What it's measured against will shape the results of the study. The 2024 study reported that patients taking GLP-1 drugs saw large reductions in cancer risk compared to those taking insulin. But comparing patients on GLP-1 drugs with patients taking the diabetes drug metformin showed no clear reduction in cancer risk.

Insulin is reserved for patients with more advanced diabetes, a condition that is itself a risk factor for cancer. In these studies, patients on insulin start out with a higher risk of cancer. Measured against a group at higher risk of developing cancer, almost anything can look protective. The apparent benefit came from the comparison drug, not the GLP-1 drug.

The third is timing. It is not so much another source of bias as a clue that other biases may be at work. Cancer can take decades to develop, yet most GLP-1 studies follow people for only a handful of years. In some studies, the apparent cancer benefits of GLP-1 drugs show almost immediately. But prevention doesn't work that quickly. A drug that truly lowered the risk of developing cancer would show its effect gradually as fewer tumors surface over time, not within the first few months of taking a drug.

When cancer risk appears to drop almost as soon as a patient starts treatment, the speed is not a magical triumph of GLP-1 drugs. Rather, in my view, it is the tell: People who start these drugs were already at lower cancer risk, and the GLP-1 drugs are getting credit for that preexisting advantage.

Moreover, almost all of this research comes from a handful of high-income countries, even as uptake of these drugs is increasing globally and the burden of cancer has disproportionately grown in lower-income countries. The idea that GLP-1s may reduce cancer risk for much of the world is being inferred from data generated almost entirely in a few rich ones.

What do randomized trials show?

The cleanest way around these study biases is randomized trials, which by design make comparison groups alike from the start.

Available clinical trials tell a quieter story than the headlines. Two 2025 meta-analyses, which pool data from multiple studies — one covering 50 trials and a second covering 48 — found little evidence that GLP-1 drugs either raise or lower cancer risk.

The findings of these meta-analyses are generally more reliable than those of observational studies because their total amount of data increases their statistical power. Despite their strengths, these analyses inherit the limitations of the trials they include. Most of the trials in these 2025 studies had a short follow-up of a year or two and recorded too few cancer cases to settle the question.

Randomized clinical trials designed to answer the question of whether GLP-1 drugs affect cancer risk would need to enroll tens of thousands of people and follow them for many years. Short of that, the next best evidence will come from observational studies designed to emulate randomized trials.

Until then, the idea that GLP-1 drugs lower cancer risk is a hypothesis worth testing but not a conclusion to act on.

The bottom line

Based on the available evidence, the clearest conclusion is the reassuring one: GLP-1 drugs do not appear to raise overall cancer risk. However, more ambitious claims that GLP-1s actively prevent cancer or improve survival after diagnosis remain unproven.

Suppose GLP-1s do have an effect on cancer risk. Researchers still would not know where that effect comes from: weight loss itself, broader improvement in metabolic function, or a more direct effect on inflammation, the immune system or tumors.

The surest thing I can say is also the least satisfying: It's still too early. These drugs are far younger than the cancers they are being credited with preventing.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Female farm managers are hidden in plain sight in ancient Roman texts, mentioned in laws, literature and grave inscriptions across five centuries. Modern historians have generally assumed they were housekeepers, in charge of domestic tasks and household meals, and segregated from the productive business of the farm.

My new paper, published in the Journal of Roman Archaeology, challenges this assumption.

In fact, there is evidence to suggest that many Roman female farm managers supervised wine production and other processes vital to farming and profits.

A false lead

A farming manual written by the Roman writer Lucius Junius Moderatus Columella in the 1st century CE is a window to the roles of the female manager.

An upper class landowner himself, Columella lists the responsibilities of farm managers, who were probably enslaved. The male manager was termed the vilicus, and the female manager the vilica, terms derived from their roles at the "villa".

But many historians reading this text have been side-tracked by a false lead: Columella begins his section on the vilica with a long quote from the Greek philosopher Xenophon, who wrote in Athens more than four centuries earlier.

The "natural" role of women, according to Xenophon, was to work indoors. Therefore in his discussion, the ideal upper-class married woman is depicted staying inside her town house to supervise the domestic work of the slaves.

The Greek writer is not discussing farm workers. In fact, Columella says four times that these ideas are not his own, but those of Xenophon, writing long ago.

Columella lists a completely different set of responsibilities for the vilica on a Roman farm: most importantly, the making of wine and olive oil, which were highly valuable commodities — the backbone of landowners' profits.

In his description of the vilica's duties, Columella includes the extraction of the juice from grapes during the harvest; adding flavorings and preservatives such as salt, wormwood, fennel or boiled grape-juice; and overseeing successful fermentation into wine.

According to Columella, the vilica also managed the processing of other farm products to make them long-lasting and profitable, such as turning inedible olives into olive oil for sale.

From archaeology we know that production of wine or oil, using huge machines in substantial buildings, could reach 50,000 to 100,000 litres per year, or even more. The vilica was therefore responsible for overseeing large-scale work essential to the operation of the estate.

Calling on the gods

Correct sacrifices to the gods were seen as vital to the success of the farm. Archaeology has uncovered altars for offerings in Roman wine-making buildings.

Wine-making in the Roman world was a precarious process, due to uncontrolled temperatures, bacteria or oxygenation. Wine could easily go moldy or turn into vinegar.

A striking element of Columella's account is that he includes carrying out offerings to avert such a disaster in his instructions for the female farm manager.

Looking for more clues

Other texts contain barely more than a mention of the vilica, revealing only her presence.

But we can still put together some clues.

Legal writings on inheritance, quoting the 1st century BCE jurist Trebatius, include her in the instrumentum fundi — whatever (including enslaved personnel) is required for productive work, gathering and preserving produce of the estate.

Another aristocratic landowner and writer, Cato the Elder, living two centuries before Columella, lists both the female and the male farm manager as essential staff for a vineyard or olive farm.

He devotes only one small section to outlining the female farm manager's tasks, but a close look shows these are not predominantly domestic. Cato includes keeping poultry and processing of seasonal farm products. Although he does include supervision of cleaning, this could refer to maintenance of work spaces such as stables and wine making buildings, an integral part of estate management – and also listed by Columella among the vilica's duties.

Cato also gives the vilica the responsibility for making sacrifices to the gods for the success of the farm. She must regularly offer garlands at the altar "for abundance", he writes.

A Roman mosaic showing estate work in different seasons depicts a scene of sacrifices for abundant crops to the god Jupiter (in his Celtic form as a sky and weather god). A woman is shown holding an offering of garlands, just as Cato instructs. Beside her are a jug for wine offerings and a male figure.

Perhaps this mosaic shows the vilica and vilicus, both essential to the success of annual harvests. While such images of female figures are rare, one fragmentary wall painting from Rome shows a female overseeing wine-making workers, just as Columella describes.

This combined body of evidence suggests we should expand outdated understandings of the roles that Roman women played in farm production, the dominant sector of ancient economies.

No vilica has left us an account of her work in her own words. But by paying careful attention to the evidence, we can hear an echo of her voice.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

From Augustus to Nero, see how much you know about ancient Rome's famous leaders with our Roman emperor quiz!

On July 14, 2026, "Gus," one of the most complete specimens of Tyrannosaurus rex, went to an as yet unidentified buyer for US$50.1 million. This auction at Sotheby's set a record for most valuable fossil ever sold. Another dinosaur has entered the luxury collectibles market, a reminder that even Earth's deepest history can be sold to the highest bidder.

To paleontologists like me, however, a fossil like "Gus" — excavated from the Hell Creek Formation in South Dakota over three years starting in 2021 by commercial collector Thomas Heitkamp and his team — is not a trophy or a work of art. It is an irreplaceable scientific archive. Fossils preserve evidence of evolution, extinction, growth, disease, injury and ancient ecosystems. They are finite, nonsubstitutable records of life’s history on Earth.

Science depends on independent verification of claims and healthy debate. Researchers must be able to revisit specimens, test earlier conclusions and ask new questions.

But once a scientifically important fossil enters a private collection, access for researchers is no longer guaranteed. Collectors typically sequester their fossils in their homes. Even when privately owned specimens are loaned to museums, the owners can change their minds, ending access at any time. This issue is especially of note when it comes to Tyrannosaurus rex; a 2025 study found that while there were 61 T. rex fossils in public trusts at that time, 71 were privately held.

That is why the Society of Vertebrate Paleontology, of which I'm a long-term member and president-elect, has long argued that scientifically significant vertebrate fossils belong in the public trust, curated in museums and universities that preserve them permanently, make them available for research and share them with the public.

Finding a fossil

Supporters of commercial fossil sales often argue that without sales to private collectors, specimens like "Gus" would remain buried or erode away. They’re right about one thing: Discovery matters. Many extraordinary fossils have been found by ranchers, hikers, amateur collectors and commercial excavators. Paleontology is accessible to everyone who has an eye for observing nature — you don't need to be an expert with academic credentials to make an important discovery.

But discovery is only the beginning. A fossil's scientific value depends on careful documentation of where it was found, the rocks surrounding it, and the plants and animals preserved alongside it. Those details allow scientists to reconstruct ancient ecosystems, understand how an animal lived and died, and interpret how its remains became fossilized. When that contextual information is incomplete or lost, much of the fossil's scientific value is lost as well.

Yet even discovery, excavation and publication barely scratch the surface of a fossil's scientific importance. The greatest scientific value of a specimen often comes decades later, when researchers ask new questions and apply new technologies that earlier generations never imagined. A specimen that seems fully studied today may yield surprising new information tomorrow, but only if it is still available for study.

Delayed discoveries

Consider the iconic dinosaurs, including T. rex, Triceratops, Diplodocus and Stegosaurus, first collected more than a century ago. Early paleontologists could describe their shapes but had no way to dig deeper by peering inside the bones. Because those specimens were preserved in museum collections, later generations could revisit them with technologies that didn't exist when they were discovered.

Paleontologist Larry Witmer and his collaborators at Ohio University started using CT imaging 20 years ago to reconstruct the internal anatomy of historic dinosaur fossils without damaging them, based on how X-rays travel through specimens. Brain cavities, inner ears, air spaces, nerves and blood vessels became visible for the first time, revealing how dinosaurs balanced, heard, smelled and perceived their world.

Henry Fricke, Thomas Cullen and other geochemists have used isotopic signatures preserved in fossil teeth and eggshells to reconstruct dinosaur diets, migration patterns and body temperatures. This research has revealed how dinosaurs lived: what they ate, how they moved through ancient landscapes, and even how warm their bodies were.

More recently, molecular paleontologist Jasmina Wiemann and her collaborators have identified chemical traces preserved in fossil bone, eggshell and skin that reveal aspects of dinosaur biology unimaginable even a generation ago. Until now, paleontologists had no way to know details about metabolic rates and reproduction or the colors of skin, feathers and eggs.

In my own research I use microscopes to uncover the hidden stories preserved inside dinosaur bones and teeth. Thin sections of fossil bones reveal that dinosaurs grew more like mammals and birds than like oversized reptiles. Microscopic modifications to bones capture traces of ancient scavenging, and tiny signatures deep inside baby dinosaur bones indicate the moment of hatching.

None of these discoveries would have been possible if the original fossils had vanished into inaccessible private collections.

Shared natural heritage, on the auction block

Fossils are not static objects whose scientific value is exhausted once they are described. Their value grows as science advances, but only if future researchers can continue to examine the original specimens.

Of course, sometimes dinosaur fossils are rescued from obscurity through purchase and immediate deposition or donation to natural history museums. Some of the world's most important dinosaur fossils are accessible today because individuals, companies or organizations with the means to acquire extraordinary specimens recognized that they belong where scientists can continue to study them and where future generations can learn from them.

Purchasing a fossil in order to place it permanently in the public trust is fundamentally different from acquiring it as a private collectible: One expands access, the other leaves access uncertain.

But as fossil prices rise into the millions, museums increasingly cannot compete. The most significant fossils are no longer reliably entering public collections. Instead, they are becoming luxury assets whose market value supersedes their scientific value.

Dinosaurs belong to our shared natural heritage. They inspire wonder because they connect all of us to a world unimaginably older than our own. For me, the question raised by auctions like the one on July 14 of "Gus" is not who can afford to own these relics of the past. It is whether future generations have the chance to study and learn from them.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

How much do you know about the king of the dinosaurs? Test your knowledge with our T. rex quiz!

The use of nicotine pouches is increasing among teenagers and young adults in the U.S. As researchers who study nicotine use among young people and develop strategies to prevent it, we worry these discreet products might be driving a new public health crisis. It may be that more and more teens are becoming addicted to nicotine pouches under our watch.

To stop that crisis in its tracks, we need to act now. Myriad strategies would help, including eliminating flavored pouches and reducing the amount of nicotine in the products, as well as regulating their marketing and stopping companies from making deceptive claims. And while we await such regulation, informing educators, parents and teens about the harms of nicotine pouches will be key.

Why worry now? Nicotine pouches — small, pillow-like products that users place between their gum and lip — are now the second most used tobacco product among U.S. adolescents. In a recent survey, 2.3% of high school and about 1% of middle school students, an estimated 460,000 students total, reported using a pouch in the past month. More than 9 in 10 pouch users opted for flavored pouches, with mint being the most popular.

While rates of pouch use remain behind e-cigarette use, more students reported using pouches than cigarettes, cigars, smokeless tobacco or any other form of nicotine. Nicotine pouches were the only product whose use increased in the survey, while the popularity of other products declined or remained stable.

What makes nicotine pouches particularly tricky is how invisible they are to the outside observer. Unlike cigarettes, they produce no smoke. Unlike e-cigs, they generate no visible aerosol. They are small and easy to conceal. That invisibility is not a coincidence; it's part of big tobacco companies' intentional design. An adolescent can use nicotine pouches during class and no one around them would know.

Each pouch contains nicotine powder that is either derived from tobacco plants or synthetically produced, as well as other ingredients like acidity regulators and flavorings. Those flavors can be dessert-like, fruity, minty, and reminiscent of coffee or cocktails — all of which appeal to young people.

The amount of nicotine per pouch varies by brand, but generally, using one pouch is roughly equivalent to smoking one to four — or more — cigarettes. That's a problem because, although pouches don't produce smoke, nicotine is still very addictive and harmful to the developing brain.

Nicotine use can negatively affect teens' attention and impede their impulse control, hurting their academic performance and mental health. In regards to physical health, data suggest that smokeless oral nicotine products may harm some aspects of heart health and raise the risk of death in people with existing heart disease.

It may be tempting to wave away concern because the percentage of adolescents using these pouches appears relatively small. However, that would be a mistake, as doing so would mean watching history repeat itself.

Rates of e-cigarette use also started low, and by the time national data finally showed a clear increase, their use was already a deeply entrenched behavior among adolescents, with many addicted. Furthermore, national surveillance studies are, by design, snapshots in time and often lag behind what is happening in real time in classrooms and communities.

We're concerned that more teens are becoming addicted to nicotine pouches, now, and want to curb the trend. At Stanford Medicine's REACH lab, we work with thousands of schools and teachers across the U.S. every year, providing free, evidence-based tobacco prevention curriculums. We've spoken with hundreds of educators, parents and students across the country who have raised significant concerns about nicotine pouches, and presented talks to over 1,200 people on the subject.

It became clear that we must create a specific approach to prevent teens from using pouches — so, we created a course called Not So Sweet: Oral Nicotine and Smokeless Tobacco Prevention Curriculum.

The free course is designed to be used in schools or by anyone who works with teens. It explains the different types of oral nicotine and smokeless tobacco products and their many health effects, including addiction. It also lays out the marketing tactics employed by the tobacco industry to attract youth in the first place. In just a few short weeks of releasing the curriculum, we already have over 1,500 active users.

We're heartened that people are already engaging with the course, because we might already have a public health crisis on our hands.

Today's nicotine pouch market in the U.S. is dominated by three brands: the top seller, ZYN; On!; and VELO. These brands are owned by Philip Morris International, Altria, and British American Tobacco, respectively. The companies have decades of knowledge in marketing nicotine products that they are now deploying to sell nicotine pouches.

They're falling back on successful advertising tropes, telling consumers that nicotine pouches could help them socialize, unwind, or appear cool to potential romantic partners. Ads also emphasize the discreet nature of the pouches, which allows them to be used anywhere without drawing too much attention.

Through these marketing strategies, nicotine pouches have soared in popularity and sales, Zyn has become a household name, gaining nicknames like Zynnie, Zynfluence and Zyndulgence. Zyn has effectively become the "Coke" of colas, the Kleenex of tissues, the Juul of e-cigs.

What's more, the Food and Drug Administration just authorized various Zyn products to be marketed with the claim that using Zyn instead of cigarettes puts you at a lower risk of mouth cancer, heart disease, lung cancer, stroke, emphysema and chronic bronchitis. But when it comes to teenagers, we see many using Zyn or other nicotine pouches alone or alongside other nicotine products that aren't cigarettes. Unlike adult smokers who may be switching to pouches, teens may be newly introduced to nicotine addiction through products like Zyn.

It is not a matter of cigarettes versus Zyn for many teens; it is Zyn versus nothing.

Nicotine pouches might come in tantalizing flavors, but they are not sweet — they are dangerous, especially for adolescents. Reminiscent of what we've seen for decades with cigarettes and over the last decade with e-cigarettes, we once again have a nicotine product that is very appealing to and being increasingly used by young people. Yet, they contain a great deal of nicotine and are unsafe. We need to work together, now, to ensure we don't perpetuate another generation of addicted kids.

Editor's note: Bonnie Halpern-Felsher has served as an expert witness in litigation against various tobacco companies.

This article is for informational purposes only and is not meant to offer medical advice.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

Consider the following scenario. Suzy is 63, recently retired, and trying to decide when to start receiving Social Security and how to manage her retirement savings to minimize the tax hit.

She opens an AI chatbot, types in the details and gets a calm, well-organized and confident answer: Claim now, convert this much, here is the reasoning.

The chatbot sounds authoritative and even shows its work. So Suzy follows its guidance and never calls a financial planner. Maybe the advice was fine. But maybe it quietly ignored the fact that Suzy's spouse is younger and in poor health, which can flip the Social Security math. It also may have overlooked that the retirement savings plan conversion it suggested would push Suzy into paying higher Medicare premiums two years later.

Suzy won't find out for a long time, if ever, whether this guidance was right for her. And the AI will never call back to say it was unsure.

Suzy isn't an exception. AI chatbots have entered everyday life with remarkable speed: A 2025 Pew Research Center survey found that 34% of U.S. adults and 58% of those under 30 have used ChatGPT, roughly double the share two years earlier.

A growing number are asking AI about money, and some are getting burned. According to a 2025 survey of 2,000 U.S. adults by Pearl.com, a professional services platform, 19% said they lost more than $100 by following financial advice from an AI chatbot. Among Gen Z investors, that figure rose to 27%.

These aren't hypothetical risks. People are already paying for answers about their money that are confident — and wrong.

As a finance professor who has been closely watching the spread of AI into personal finance, this is the part of the AI story that worries me most. And it's not the part you usually hear about.

We argue about AI the wrong way

There are two seemingly opposite complaints about AI. One is that people trust it too much, treating a chatbot like an oracle, a tendency researchers call algorithm appreciation. The other is that people don't trust it enough and dismiss its useful tools, a tendency known as algorithm aversion.

I argue these are actually two sides of the same coin, and what decides which side you see is whether you can tell when the AI is wrong.

When an AI fails in an obvious way, you notice and lose confidence. So you're more likely to seek a professional or another human you trust sooner than you otherwise would. That is the safe failure.

The dangerous failure is the opposite. The answer is fluent, confident — and wrong. You have no way to catch it, so you keep managing the problem yourself long past when you should have asked for help.

The trouble is that with money, the second kind of failure is the common kind.

When you mistake fluency for accuracy

Three things make financial advice especially treacherous for AI.

First, fluency is not accuracy. People naturally read a confident and well-articulated answer as competent. But how polished an answer sounds tells you almost nothing about whether it fits your situation or the accuracy of the proposed solution. A chatbot can be word-perfect and still be wrong about your taxes, because your taxes depend on details it never asked about.

Second, AI is least reliable exactly where the stakes are highest. AI tools are good at routine and general topics: what a Roth IRA is, how compound interest works, the difference between a stock and a bond.

But financial life is full of rare, complicated, one-time decisions: exercising stock options, understanding the alternative minimum tax, making required, minimum 401(k) distributions, deciding on a Social Security strategy as a couple, drawing up a divorce settlement.

I made a similar argument three years ago about AI trading on Wall Street. Because market crashes are rare, there's little data for AI to learn from, so it can be most confident exactly where it is least informed.

That worry hasn't faded. Market watchers now caution that AI trading bots are creating fresh financial risks, and that same blind spot applies to your personal finances. Researchers call this uneven competence a "jagged frontier" — reliable with common cases but unreliable for unusual ones. And in finance, the unusual cases tend to be the expensive ones.

Third, you often can't check the work. Financial advice is what economists call a "credence good," like a mechanic's diagnosis or a doctor's recommendation. You often can't tell whether the advice was good, sometimes for years. A mistaken tax move may not surface until an audit. A bad 401(k) drawdown plan may not bite until the stock market slumps. Without quick feedback, the wrong-but-confident answer never gets corrected.

This is why the Pearl numbers above are probably an undercount, since they capture only losses people noticed.

The quiet failure is the one to watch

Notice that the real harm in Suzy's story isn't a single dramatic mistake. It's that a confident answer made Suzy feel no need to call a professional, so the call never happened.

The danger is not so much that you act on bad advice but that you never seek good advice. The smoother and more reassuring the tool, the easier it is to stay in do-it-yourself mode past the point when you need outside help.

Who's most at risk? In a study of a large robo-advising platform in India, co-author Vishaal Baulkaran and I found that its users skew young, are predominantly male and tend to be smaller retail investors and professionals. And new account sign-ups rise during periods of high market volatility.

In other words, the people leaning hardest on automated advice match that 27% figure among those Gen Zers who lost more than $100 while using a chatbot for financial advice. They reach for it just when markets turn turbulent and a wrong move is most costly.

There's also an incentive worth naming. In my new analysis, I argue that a tool that earns its revenue by holding your attention has a reason to sound confident and helpful: Confidence keeps you on the platform. The catch is that the user it retains that way is sometimes the one who should have been handed off to a human.

A system tuned to keep you engaged isn't the same as one tuned to protect your financial future, and the two can point in different directions. The disruption is already underway, as wealth managers face what Bloomberg has called a chatbot reckoning. A single, new AI tax tool recently sent wealth management stocks sliding as investors bet that automated advice will eat into the business.

How to be smart about using AI

These findings don't mean that people should avoid AI for money advice. Used well, these tools are a valuable and free financial educator.

This is also not to say that a financial adviser always has the right answers. As with finding any kind of specialist, it's important to do research first and make sure they meet the kind of criteria laid out by the Consumer Financial Protection Bureau. Fee transparency is also crucial.

But if you do turn to AI, the skill is knowing where to draw the line.

Treat AI as a starting point, not a verdict. It's excellent for learning concepts, drafting questions and getting oriented before a meeting. It can teach people the vocabulary to have a smarter conversation with an expert.

But watch out for the signals that you have left its comfort zone and entered the territory where AI is weakest and a confident answer is least trustworthy. The red flags are large dollar amounts, tax consequences, anything irreversible and anything that turns on the specifics of your situation rather than a general rule.

Estate questions, the drawdown of retirement savings, strategies for claiming Social Security benefits, business structure and major one-time transactions all belong in this category. Those are the decisions that call for bringing in a human, such as a certified financial planner.

And remember, confidence isn't competence. When the answer about your money sounds most polished and most certain, that's not a reason to relax. On the hardest questions, that smooth confidence is exactly the signal that you should pick up the phone and talk to an expert.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Tropical forests draw down and store large quantities of CO₂ from the atmosphere. The Amazon rainforest in South America, for example, stores approximately 123 billion tonnes of carbon — more than is stored in any other terrestrial ecosystem in the world. But these forests are facing a critical challenge.

Research from 2023, which was carried out by me and more than 100 colleagues, found that tropical forests in South America are vulnerable to climate extremes. We determined that during an El Niño event, the warm phase of a natural fluctuation in the Earth's climate system, South American tropical forests may fail to act as a carbon sink.

This finding becomes even more alarming when we consider the increasing frequency and intensity of El Niño events. There have been twice as many "very strong" El Niños in the last 60 years as there were in the 60 years before that. And the US National Oceanic and Atmospheric Administration has recently confirmed that such an El Niño is currently underway.

Tropical forests absorb CO₂ through the process of photosynthesis and convert it into biomass. However, the balance between photosynthesis and respiration is delicate and depends on two factors: temperature and water availability.

In hotter and drier conditions, plants close the pores of their leaves to avoid water loss. But closing them effectively cuts off a plant's fuel supply because it is through these pores they absorb CO₂. This starves plants of the carbon needed for photosynthesis and to grow.

During El Niño years, which are characterized by high temperature anomalies, prolonged climate stress leads to reduced forest growth and increased tree mortality. The effects of this are felt for decades as carbon is released back into the atmosphere when the dead trees decompose.

Our findings revealed that during the 2015-2016 El Niño, when temperatures on land were at least a degree higher on average than usual conditions, some of South America's tropical forests effectively stopped absorbing carbon. This raises concerns about the possible impact of the current El Niño on the Amazon and global climate.

In our research, we measured over half a million trees across six South American countries over a period of more than 30 years, using tape measures to track their growth. These trees belonged to over 4,000 different species. We used this data to calculate precise estimates of the amount of carbon stored as a forest's aboveground biomass.

We found that the vulnerability of these forests to El Niño conditions was closely linked to their baseline climate. While we tend to assume that rainforests are all hot, wet and biodiverse ecosystems, seasonal drought is a reality for many tropical forests. Conditions in regions at the edge of the Amazon rainforest, for example, tend to be particularly hot and dry.

Our findings revealed that drier forests at the edge of the Amazon, where trees regularly endure periods of limited water availability, were especially susceptible to extreme El Niño conditions. On average, a 0.5°C increase in temperature caused these forests to lose 0.5% of their aboveground carbon.

Larger trees suffered the most. While tree mortality rates increased from 1.8% to 3% per year during the El Niño in South American tropical forests as a whole, mortality rates effectively doubled for medium (classified as over 20cm in diameter) and large trees.

The fact that larger trees with less dense wood died at much higher rates compared to small trees and those with high wood density points strongly to hydraulic failure, when intense atmospheric moisture demand snaps the tension in the tree's internal water column rather than slow carbon starvation.

These results suggest that adaption to seasonal drought may not be sufficient to protect tropical forests from extreme events. Climate extremes are possibly already pushing forests at the edges of the Amazon beyond their capacity to adapt, causing catastrophic carbon losses.

A looming threat

Scientists have warned that 2026 may again be the warmest year on record. Heightening the alarm further is the severity of the current El Niño. Never before has an an El Niño begun when oceans are already so warm and air temperatures so high.

On top of this is the fact that, over the past three decades, the edges of the Amazon have experienced some of the highest temperatures and most rapid warming the tropics have ever seen. The structural integrity of a forest is compromised when a major climate anomaly occurs before it has recovered from recent, multi-year stress.

These compounding factors mean that we risk witnessing tree and carbon losses on scales not yet seen.

Tropical forests are invaluable assets in the fight against climate change. But South American tropical forests, a once-reliable carbon sink, are vulnerable to intensifying heat and drought. There is a risk these essential ecological allies stop acting as a carbon sink as extreme climate conditions become the norm.

Preserving tropical forests is thus essential. Their ability to continue acting as carbon sinks hinges on efforts to protect them and a collective commitment to limit global temperature rise. The Amazon's future depends on this, and so does ours.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Rainforest quiz: Can you sort Earth's largest rainforests from biggest to smallest?

For decades, cities have been designed around "gray infrastructure." Roads move people. Bridges connect communities. Water systems protect public health. These systems are governed by engineering standards because society recognizes that safety cannot depend on good intentions alone.

Urban nature deserves the same recognition.

In June, a heat wave gripped Europe, breaking temperature records across the continent. In France, officials reported over 2,000 excess deaths. In the U.K., hospitals declared critical incidents and machinery and IT systems failed. In the U.S., a heat dome over the Midwest and East Coast disrupted Fourth of July celebrations, with at least 25 heat-related deaths over Independence Day weekend.

Cities are being tested by a warming climate. Yet one of our most effective forms of climate infrastructure is being lost — not because it does not work but because we still do not treat it as infrastructure.

My view is simple: Urban nature ‪—‬ including street trees, parks, wetlands and other urban green spaces ‪—‬ should be categorized and managed as essential infrastructure, with minimum standards for its protection, quality and long-term maintenance. Just as we regulate roads, bridges and drinking water, we need standards that ensure all urban residents benefit from healthy and thriving urban nature. Without such standards, cities will become hotter, less resilient and increasingly unequal as climate change accelerates.

Scientific research shows that urban trees and green spaces cool cities during heat waves, reduce flooding by absorbing stormwater, improve air quality, store carbon, support biodiversity, and improve both physical and mental health. During extreme heat, neighborhoods with mature tree canopies can be several degrees cooler than nearby streets dominated by concrete and asphalt. Those few degrees can mean the difference between manageable discomfort and dangerous heat exposure, particularly for older adults, children and people with existing health conditions.

But while the science is strong, our governance is not.

Cities enthusiastically announce ambitious tree-planting campaigns, biodiversity strategies and new greening targets. These initiatives are valuable, but they often focus on what is easy to count rather than what truly matters. Planting a tree is not the same as growing a healthy urban forest. Creating a park does not guarantee biodiversity. A green roof delivers little value if it fails during drought.

The real measure of success is whether urban nature continues providing benefits decades after trees are planted and established.

This is where cities are still falling short.

Unlike buildings or transport systems, urban nature rarely operates under consistent minimum standards. Many cities have no requirements for minimum tree canopy cover, adequate rooting space, soil quality, biodiversity targets, long-term maintenance or even whether newly planted trees survive. As a result, access to nature depends heavily on where people live. Wealthier neighborhoods often enjoy mature tree canopy and high-quality parks, while disadvantaged communities experience hotter streets, fewer green spaces and greater exposure to climate risks.

That is not simply an environmental issue. It is a public health issue, a climate adaptation issue, and an issue of social equity.

The solution is not simply to plant more trees. It is to establish urban nature standards that recognize nature as essential infrastructure.

These standards would not prescribe the same solution for every city. Instead, they would establish minimum expectations based on scientific evidence. They could include targets for accessible green space, minimum tree canopy cover, sufficient soil volume for healthy tree growth, biodiversity outcomes, long-term maintenance funding and routine monitoring to ensure that urban nature continues delivering benefits to communities.

Importantly, these standards should focus on outcomes rather than simple planting targets. Counting how many trees are planted tells us little about whether cities are becoming more resilient. Measuring survival, canopy development, ecosystem health and equitable access provides a much better picture of whether investments in urban nature are actually returning dividends.

Some critics argue that cities cannot afford stronger standards for urban nature. Municipal budgets are already stretched by housing, transport and aging infrastructure. But this argument overlooks a fundamental reality: We already spend enormous sums responding to the consequences of extreme heat, flooding, poor air quality and declining public health. Healthy urban ecosystems help reduce these costs while delivering multiple benefits simultaneously.

As climate change accelerates, the distinction between gray and green infrastructure becomes increasingly blurred. Trees cool buildings and reduce energy demand. Wetlands decrease flood damage. Parks improve public health and strengthen communities. These are not optional amenities. They are functioning components of urban infrastructure that deserve the same level of planning, investment and accountability as any engineered system.

Building codes transformed the safety of our cities because they established minimum standards that every development had to meet. Climate resilience now demands a similar transformation for urban nature.

The next generation of resilient cities will not be defined simply by how many trees they plant but by the standards they adopt to protect, restore and sustain the living infrastructure urban life depends on.

The real question is not whether cities can afford to invest in urban nature; it is whether they can afford not to.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

Artificial Intelligence (AI) is continuing to have a disruptive impact on ever more parts of humanity. But what does it mean in the long run? A new paper, available in pre-print on arXiv from Austrian researcher Sergey Ivliev, extrapolates what the wide scale adoption of AI means for the future of humanity in space — and in particular what it means for the ultimate question of whether we're truly alone in the galaxy or not.

A framework for much of the search for extraterrestrial intelligence came from famous physicist Enrico Fermi, who simply asked "Where is everybody?" at a lunchtime discussion at Los Alamos in the 1950s. Though never officially published, Fermi's lunch partners from that day have passed down an oral history of that conversation that has cemented it into the Search for Extraterrestrial Intelligence (SETI), at least until Michael Hart formally laid out the argument and mathematics for the underlying question in a paper in 1975.

There are plenty of potential answers to the Fermi Paradox, many of which can be found floating around the internet — and some are likely more valid than others. But Ivliev, a Ph.D. in Mathematical Economics and founder of environmental project consultancies such as Peatland Ecosystems and Vlinder, suggests a new resolution: the Quiet Expansion filter.

The central argument of the paper is that there aren't thousands of alien mega-structures lighting up the night sky because once a civilization reaches the threshold of Autonomous AI-Cosmoindustry (AICI), "loud", resource-hungry empires motivated by prestige or romance become irrational. However, this does not mean expansion stops; instead, it shifts to a "quiet" mode driven by rational goals like survival diversification, knowledge preservation, and scientific observation.

The AICI threshold is reached when a civilization possesses a self-sustaining off-planet industrial and computational system capable of designing, manufacturing, repairing and launching space hardware through AI-mediated autonomy. We're already taking tentative steps in this direction with the advent of space-based data centers, but true AICI —where a civilization can extend its infrastructure beyond its home planet without continuous biological intervention — is leaps and bounds beyond our current capabilities.

In this vein, Ivliev is drawing on work done by astrophysicists Sergey Popov, who noted that a truly rational AI system would reject human-like motivations for space travel — such as romance, conquest, or prestige. Instead, AI would view space expansion as simple risk management.

To an AI, putting all your eggs in one basket — whether that basket is a single planet, solar system, or even galaxy, can lead to a single point of failure. Therefore, expansion is highly logical as a way of mitigating the risk posed by that single point of failure. At the point where we have reached AICI, the cost for sending a 10kg interstellar probe to another star at 1% of the speed of light is roughly 4.5x10^13 Joules — a tiny fraction of the overall energy budget of such a civilization.

One key aspect is that the 10 kg probe doesn't contain any actual people — it simply holds the "seeds" to restart life elsewhere in case a catastrophe happens back in the home system. It would contain a civilization's knowledge, and possibly some of its biological material, enabling a sufficiently advanced AI to rebuild the entire civilization from scratch. This is the "Quiet Expansion" where an AI sends low-mass and hard to detect "seed systems" instead of moving millions of biological entities around in massive interstellar space ships.

There are some additional constraints on this method of expansion, including selecting promising exoplanets discovered by remote sensing and deploying minimal local resources to maintain themselves until needed. Additionally, the AI would restrict self-replication of the probes in order to avoid any "grey goo" scenario with a probe attempting to take over entire swathes of the galaxy.

This has obvious implications for why we've never found "loud" technosignatures. In this scenario, a "null" result of being unable to find the thermal signature of a Kardashev-III scale civilization doesn't mean a galaxy is empty. It just means that the successful civilizations are residing in a "quiet" state in case its back-up plans are needed.

But there's another, more ominous implication from this framework. If interstellar backups are cheap to make, and we haven't found any in our own backyard, that means either we're one of the first civilizations to make it to that point or the transition from a planetary industrial society to a space-based one is a narrow path to tread. Admittedly the probes such civilizations would send out are probably hard to find even in our own solar systems, but if we're unable to, it means we're ending uncharted territory — and might just run into a filter that had silenced the rest of the galaxy. That's a sobering thought, but one to keep in mind as we start to advance our own AI capabilities.

The original version of this article was published on Universe Today.

Are you a UFO fanatic? Find out with our extraterrestrials quiz!

During several recent conversations, people have told me that they've stopped checking their phones in the morning. Not because nothing was happening, but because everything was. They described the feeling as standing under a waterfall of perpetual bad news.

This experience is far from an isolated one. According to Reuters Institute's 2025 Digital News Report, 69% of Canadians at least occasionally avoid the news now.

Globally, 40% report they at least sometimes or often do the same, the highest figure ever recorded. People shared consistent reasons for this: the news put them in a bad mood, they felt overwhelmed and powerless to act.

As a researcher in developmental psychology, focusing on social development and psychological well-being, I argue that news fatigue is not laziness, weakness or a generational decline in civic interest. It's the predictable response of a human brain meeting an environment it was never designed to navigate.

Wired for bad news

Long before smartphones or even the printing press, our cognitive architecture was shaped by a single problem: stay alive long enough to reproduce. Our ancestors whose attention drifted past the rustle in the grass left fewer descendants than those who froze, looked and listened.

The brain that paid attention to threats was the brain that survived.

This is the foundation of what psychologists call the negativity bias, one of the most replicated findings in cognitive science. Across decades of research, the human mind has been shown to weigh negative information more heavily than positive, attend to it faster and remember it longer.

A predator nearby mattered more than a beautiful sunset. The cost of missing a real threat was death, while the cost of overreacting was a few minutes of wasted vigilance. The asymmetry made this bias adaptive.

Here is the problem: the human brain has not changed since then. We are the same species as we were thousands of years ago. What's changed is the size of the world it's asked to scan for threats.

Scanning the whole world

For most of human history, the threats our nervous system processed were local. A neighbouring tribe. A drought. The illness of a child we personally knew. Information about distant places would barely arrive, and if it did, it was mainly irrelevant.

In 2026, the same neurological system is being asked to absorb a war in one region, a financial shock in another, a climate disaster in a third and a violent crime in a fourth, all before lunchtime.

A study published in the scientific journal Nature Human Behaviour examined more than 105,000 real news headlines viewed nearly six million times. Each additional negative word increased click-through rates, while positive words had the opposite effect.

Recent studies suggest people around the world demonstrate measurably stronger physiological responses to negative news than to positive news. The body is reacting before the mind has decided whether the threat is relevant.

Some researchers have introduced a clinical framework for what happens in this instance called Problematic News Consumption (PNC) — a pattern of news engagement that results in preoccupation, dysregulation and disruption to daily functioning. In their 2022 study, the researchers found that 17% of American adults qualified as having severe levels of PNC. Among that group, 61% reported feeling unwell quite a bit or very much, compared with 6% of those who didn't.

For minority populations, news fatigue may be even more consequential.

Repeatedly witnessing harm directed at our own groups, even when we're not the immediate target, can have a significant psychological impact on people from the same group affiliation. For racialized communities, such as immigrants, the cognitive load could be even heavier, and the option to simply stop watching is much harder to exercise when the news is about their country of origin.

Looking away is not the fix

What's the solution to news fatigue? Well, it's not avoidance. A democracy depends on informed citizens.

Many adults already cite the spread of misleading information as a major source of stress. Withdrawing from accurate, trustworthy information only deepens the problem. We're wired to pay more attention to bad news, and that kind of content will find its way to us one way or another.

The fix is to manage the consumption and the sources.

Several approaches can help manage news fatigue and protect mental health. Containing news consumption to defined windows of time reduces the sense of being overwhelmed. Choosing depth over volume also matters: one carefully reported long-form article will inform you better than bursts of random, unreliable and emotionally loaded posts on Instagram.

There is also value in distinguishing between information and action — research on perceived control and stress consistently shows that the gap between awareness and agency is one of the strongest predictors of psychological distress. Identifying what you can actually do about what you read in the news, however small, regulates that response.

Finally, be wary of "rage bait" — intentionally provocative messages or content designed to boost engagement on social media platforms by eliciting negative reactions. Recognizing that certain content creators want to provoke rather than reflect reality creates useful cognitive distance.

The news will not become less "heavy." But our relationship with it can become more deliberate. Our brains were not built for this scale of input. They were, however, built to learn to adapt.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

As I sip coffee in my Berlin apartment and fire a question at Google's AI chatbot Gemini, it's easy not to think about the energy it takes to generate a response. Once the signal reaches my router, it whizzes, I assume, through copper wires or fiber-optic cables to one of Google's data center hubs. Somewhere inside the data center's labyrinthine halls of stacked processors, my query gets converted into numbers and undergoes billions of computations to determine context and meaning. The answer, once assembled, races back, in the blink of an eye.

Data centers — the beating hearts of the internet, powering everything from email to web searches — have existed for decades, but with the growing popularity of AI to generate text, images and video, they're using more energy than ever. According to Google's own estimates, processing a median-length text prompt with its AI assistant Gemini consumes around 0.24 watt-hours.

These amounts, individually small — 0.24 watt-hours is equivalent to watching TV for about nine seconds — are adding up fast. In March 2026, OpenAI estimated that more than 900 million people use its AI chatbot, ChatGPT, every week, tallying billions of queries daily.

The exact amount of electricity consumed by data centers, globally or in the United States, which hosts more than any other nation, isn't publicly reported by all tech companies, says Eric Masanet of the University of California, Santa Barbara, who researches data center sustainability. But according to the most recent estimates by the International Energy Agency, US data centers guzzled some 224 terawatt-hours of electricity in 2025 — more than 5 percent of the country's electricity use. That's a significant uptick from an estimated 1.9 percent consumed in 2018, well before the mainstream surge of generative AI.

This electricity use seems set to soar. In the race to secure market leadership for generative AI products, companies like Google, Meta, Amazon, OpenAI, Anthropic, Microsoft and Oracle are investing tens to hundreds of billions of dollars to build AI-focused data centers. Compared to data centers of the pre-AI days that consume, say, 100 megawatts of electricity — enough to power 83,000 homes with average demand — the newcomers are often "hyperscale" and can use a gigawatt or more, or roughly a tenth of the electrical capacity of Los Angeles.

Masanet and other experts have been alarmed to see much of this demand met by plants powered by fossil fuels, such as gas, whose burning releases planet-warming carbon dioxide. A key reason is that data centers are often constructed in places without abundant renewable energy sources like hydropower, geothermal, solar or wind.

Tech companies often offset emissions by investing in renewable energy elsewhere. But unless those clean energy plants make more energy than the data centers use, this strategy — at best — keeps CO₂ emissions of centers in stasis rather than reducing them to a net of nothing, important for halting global warming. "For every megawatt for which we install fossil fuel power," Masanet says, "it sets us back on our progress."

And that's not considering the resources spent on manufacturing the hardware that fills new data centers, or the impacts on communities living near them, which often suffer from air and noise pollution from gas plants and possible strain on local water resources, which are used to cool the data centers.

Although forecasts for AI's energy impact remain devilishly tricky, especially since the size of payoffs from investments in AI are uncertain, it's clear to experts that energy-saving strategies are urgently needed. Without them, according to one 2025 estimate, US data centers could soon be releasing the equivalent of 24 to 44 megatons of CO₂ annually, the latter equivalent to the annual emissions of Norway.

And so computer scientists and engineers are rethinking some of the power-hungry hardware and software that fuel AI. They're working to develop energy-saving algorithms and processor designs, and carefully considering where, and how, data centers are constructed.

"AI's energy cost is not an accident: This is basically a product of how our systems are built," says Fengqi You, an expert in energy systems at Cornell University. But with the right mix of solutions, he says, "we could really reshape the trajectory."

The roots of AI's energy problem

To comprehend AI's energy cost, it helps to understand large language models (LLMs) — the lifeblood of AI text generation tools such as chatbots and AI assistants — specifically, ones based on a design described in 2017 by the machine-learning laboratory Google Brain. This design, transformer architecture, can process text at lightning speed by simultaneously taking each word and weighing its relationship to every other word it sees. It "learns" which words go together by computing how strongly each word relates to all other words in a text, examining each word in many contexts. (A similar design is used for AI image and video generators.)

On a computational level, this happens by converting words or word fragments into numbers and performing additions and multiplications between them. Key to the speed is being able to do these calculations in parallel, made possible by graphic processor units (GPUs) — mostly manufactured by the company NVIDIA — originally invented for rapid 3D rendering of imagery during gaming.

The initial training of an LLM, required to learn all these relationships, consumes vast amounts of energy. Because each word it trains on must be weighed against all others in a given chunk of text, the number of computations the model performs — hence the energy required — increases quadratically relative to the length of text (i.e., doubling the length of text quadruples the number of computations). That adds up quickly given that most LLMs are trained on massive swaths of publicly available internet text. Some estimates suggest that training GPT-4 — the iteration of ChatGPT that launched in 2023 — guzzled between 50 and 60 gigawatt-hours of electricity, enough to power San Francisco for three to four days.

But experts are more worried about the energy costs of using the models to generate data once they've been trained, a process called inference. "You train once, then you inference for a billion people in the world," says Mosharaf Chowdhury, an AI systems expert at the University of Michigan who has been measuring the electricity usage of a handful of large language models that have been made publicly available.

This process is surprisingly inefficient: Each time transformer models generate a word — by selecting the one with the highest probability of following the previous word, given context — they put the query and partially written answer through the model. In doing so, they apply all of the parameters they've calculated during training to understand language patterns — which number in the hundreds of billions or even trillions.

"The fact that you have to do a lot of calculations for a single word to be added — that’s a problematic thing," says Günter Klambauer, an AI expert at Johannes Kepler University in Austria.

Tweaking AI software to save energy

This recognition has triggered interest in smaller language models specialized to specific tasks. These are trained more narrowly, have fewer parameters — say, tens or hundreds of millions — and perform substantially less computation than larger models. In one 2025 paper published by UNESCO, computer scientist Ivana Drobnjak of University College London and colleagues compared energy consumption of Meta's language model Llama-3.1 with smaller AI models dedicated to particular tasks — ones called DistilBART and t5-small-xsum for summarization, and others for translation or answering questions. When used for their respective tasks, the smaller models consumed more than 90 percent less energy than Llama 3.1 on the same job.

And so computer scientists have been driven to build a similar kind of task specialization into LLMs themselves. In "mixture of expert" models, only particular parts of one big model are activated for certain tasks. These parts "learn to handle different patterns in language," Drobnjak says.

This is thought to be one reason why R1, an LLM developed by the Chinese company DeepSeek, reportedly consumed significantly less energy than other models (independent experts have raised doubts about those figures). Udit Gupta, an expert in electrical and computer engineering at Cornell Tech, says that LLMs like Gemini or ChatGPT are similarly routing queries to more specialized sub-models. "There's a lot of work being done on how to assess the complexity of the query or task that's coming from users and then find the right model," Gupta says. (While Google spokesperson Ralf Bremer notes that the 0.24 watt-hours currently spent on processing median-length Gemini prompts is already 33 times more efficient than it was back in 2024, some experts suspect that processing queries with an LLM still consumes more energy than an equivalent web search.)

Scientists are also exploring different kinds of LLMs, to break what Klambauer calls the "quadratic curse" of transformer models.

One alternative, called a long short-term memory (LSTM) model, gets around this alarming energy increase by temporarily storing a kind of summary of the prompt that was inputted by the user plus the text generated so far, akin to recalling important plot points instead of an entire movie. That way, it only has to process the summary, rather than all the words in the full text to date, every time it generates a new word. This prevents LSTM's energy costs from skyrocketing as it responds to a query — using about 50 percent less energy than transformer-type models to process texts of around 8,000 words in length, Klambauer says.

LSTM models were developed in the 1990s but were abandoned because transformers could be trained much faster. But Klambauer says that recent advances have improved the performance of LSTM, now called xLSTM. He's working with the Austrian startup NXAI to further develop and optimize xLSTM, "because we think it's worth it for energy efficiency," he says.

But major tech companies have invested so many years and resources into developing transformer-based models that switching to other models would be costly, says Wolfgang Maaß, an AI and business informatics researcher at the German Research Center for Artificial Intelligence. "We have to see whether this becomes as dominant, or whether it finds a niche in the whole market."

Computing with wafers and light

Though experts say the fastest energy savings will come from software tweaks, some are also taking aim at the energy-hungry processing chips that fuel AI computations. Engineers have made chips increasingly efficient over time by packing more computing capacity into individual processors — reducing the energy required to shuttle data between chips that are working together to perform AI computations. Engineers have done this by shrinking the size of transistors — microscopic electrical switches that process data — inside the chips.

But because engineers are reaching the physical limits of how small transistors can be, "we need to think of alternate ideas to improve the designs," says computer architect Ajay Joshi of the Boston University Photonics Center.

One strategy is to make the chips larger. Dinner-plate-sized "wafer-scale chips" can pack nearly 70 times as many transistors as a single, postage-stamp-sized GPU and consume 143 times less electricity for communication than comparable GPUs, says computer engineer Rakesh Kumar of the University of Illinois Urbana-Champaign. Commercially produced by the California company Cerebras, wafer-scale chips have drawbacks, including a greater risk of damage during manufacturing. But because of their energy-saving and other beneficial features, "they would be very attractive to many hyperscalers and AI companies," Kumar says.

Many tech companies have improved energy efficiency by fashioning their own processors that are tailor-made for AI computations — such as Amazon Web Service's Trainium2 chip or Google's Ironwood Tensor Processing Units — according to statements from those companies. As for NVIDIA, the company's head of sustainability Josh Parker says its AI-specialized GPUs have come a long way from the ones used for gaming and are now designed to run AI tasks as efficiently as possible; other innovations, such as making the interconnections between GPUs more efficient, have also helped. "Over the past eight years, NVIDIA GPUs have improved 45,000 [times] in energy efficiency for large language model workloads," he says.

Engineers are also exploring alternative computing methods. Conventional AI processors calculate by encoding numbers in a binary system of ones and zeros, which is achieved by turning transistors on and off (representing the number 5, for instance, requires four transistors to represent the code 0101). But transistors can do more than function as binary switches allowing electron flow or not; they can also work as analog dials and hold intermediate voltages representing different numbers. That requires fewer transistors, and less energy, for computations. "People have known for decades that doing certain things in analog … can be a lot more energy efficient," Kumar says.

For example, electrical engineer Paul Manea of the German research institute Forschungszentrum Jülich and colleagues are working to develop devices called "gain cells" that are full of transistors working this way. Importantly, gain cells can both store the data required to process a query, and compute the answer. That overcomes another big energy bottleneck of conventional computing systems, where memory storage and computation occur on separate pieces of hardware.

That's especially problematic for transformer-based LLMs, because each time they generate a word, they must shuttle the query and partially written answer from memory to a processor. Manea and colleagues estimate that gain cells in lieu of traditional GPUs can reduce the energy guzzled by one of the most energy-consuming parts of transformer-based LLMs by four orders of magnitude. But it will take more refining before they can be more widely used, Manea says.

The notion of devices that both store and compute information is a key idea of "neuromorphic" computing, an up-and-coming field of computer engineering inspired by the human brain, which consumes orders of magnitude less energy than computers. Another brain-inspired invention is chips that encode information not in continuous data streams but — like human nerve cells — in the timing of voltage "spikes" propagating through the system. Allowing components to rest until they're needed "could potentially translate to less energy," says Eleni Vasilaki, an expert in bioinspired machine learning at the University of Sheffield in England.

Maaß, for example, is part of a team that received roughly $5.8 million from the German government to test neuromorphic chips, among other strategies, to reduce the energy required for AI models. Some brain-inspired chips are already commercially available, but the technology is still far from being attractive for mainstream computing, says nanoelectronics expert Tony Kenyon of University College London, whose team recently received $17 million from the UK government to develop neuromorphic computing.

Other scientists are developing chips that process information not with electrons but through the interaction of photons — particles of light — with matter (fiber-optic cables, which encode and transmit data as light pulses, are used around the world). With photons, more information can be transmitted at the same time, and signals can be altered much faster, says Elena Goi, a photonic computing researcher at Friedrich Schiller University Jena in Germany.

Several companies have developed chips that can perform some AI computations with optical methods, says Joshi; he recently estimated that manufacturing optical chips could consume up to an order of magnitude less energy than conventional ones of the same size. Joshi hopes that, "in 10 years, we would have a practical solution that can be deployed pervasively across the data centers."

Reshaping AI's energy trajectory

Even without reinventing how computers work, much can be done to reduce AI's impact not just on energy but also on water resources used for cooling data centers. Importantly, tech companies should reconsider where they build those centers, says energy systems expert You. Right now, existing US ones are concentrated in northern Virginia, which has limited water resources and renewable energy capacity compared with the Midwest, for instance. You recently estimated that better siting — along with energy-efficient hardware and software — could reduce future carbon and water footprints of US data centers by 73 percent and 86 percent, respectively.

Masanet adds that tech companies already with data centers across the country could at least train their models in strategic places. "Some companies like Google have been doing this: They shift their loads to follow renewables," he says. They also should address the electricity and resources spent on manufacturing processors for new data centers, as well as electronic waste as outdated tech is replaced every few years, he adds.

Minimizing e-waste by using hardware for longer periods and recovering old electronics is one of Amazon's sustainability strategies, according to a statement to Knowable Magazine; so is designing data centers in energy- and water-saving ways and investing in a slew of renewable and nuclear energy projects. "We'll continue to implement solutions that benefit our customers and the communities we operate in," says Brandon Oyer, Amazon Web Services' head of energy and water in the Americas.

Meanwhile, a press representative at Microsoft points to a number of sustainability initiatives the company has taken, including new cooling technologies, renewable energy investments and waste reduction. Google spokesperson Ralf Bremer emphasized the company's goal of reaching net-zero emissions across its operations by 2030 and replenishing 120 percent of the fresh water consumed by its offices and data centers by 2030. An OpenAI representative points to a press release outlining efforts to minimize water use and plans for solar energy generation at one of its campuses. Anthropic, Meta and Oracle did not respond to requests for comment by deadline.

Though tech companies are taking sustainability into consideration, their main objective is to rapidly build out data center capacity, says computer engineer Benjamin Lee of the University of Pennsylvania. He predicts that, eventually, they'll need to step up efforts to improve energy efficiency to reduce costs. Governments should help to accelerate this shift, Masanet says. So far, he and his team have counted nearly 220 policies introduced to address data center sustainability at the US state level, 18 at the federal level, and more from other countries, though not all were ultimately adopted.

"It's clear that governments around the world are beginning to take action," he says. However, he adds, "we also see some state and local governments with proposed policies that mostly aim to incentivize and accelerate data center builds."

AI's energy cost will ultimately be a balancing act: Will it save more resources through its problem-solving abilities deployed toward everything from finding cancer cures to improving logistics, than it demands? But though building a more frugal, energy-saving AI is important, so is carefully considering where AI is needed, Kenyon says. Is the world truly a better place, for example, with nonhuman "AI agents" providing customer support?

"I think it’s a common mistake, when a new technology comes in, to suddenly think, 'Well, everything has to adopt that new technology,'" he says. "That approach really isn't doing us any favors."

This article originally appeared in Knowable Magazine, a nonprofit publication dedicated to making scientific knowledge accessible to all. Sign up for Knowable Magazine's newsletter.

Plants, insects, and larger animals, like the forest’s white-faced capuchin monkeys, are well adapted to these changes. But in 2015, during an abnormally severe drought influenced by the El Niño–Southern Oscillation (ENSO), Perry, an evolutionary anthropologist at the University of California, Los Angeles, observed behaviors that once seemed impossible.

Under normal conditions "The [capuchin] mothers are quite devoted," she explained. "Now, I was seeing babies crying on the ground piteously. And the mothers just looking down like 'Too much trouble' and walking off, abandoning their infants."

"Even capuchins have their limits," Perry said. "And we need to start paying attention because all the weather predictions are saying that we're going to get more unpredictability and more climate extremes."

Monkeying around

Odd Jacobson, a behavioral ecologist at the Max Planck Institute of Animal Behavior, was a student at Lomas Barbudal in 2016, a year after this severe drought. His focus was on understanding how the study site's 12 different capuchin groups were moving through the forest. But now he's set out to investigate how else climate extremes may affect the behaviors and social structures of these monkeys.

In a paper published in Nature Ecology and Evolution, Jacobson and his coauthors — including Perry — analyzed how climate variability correlated to the 33 years of geolocation data they had on the capuchins.

Their first step was understanding how the size of each group was affecting the relationships between monkeys within the same group. To do this, they observed variables such as daily fruit intake, the size of the group's home range, and the distance the group traveled each day to find food.

Finally, to understand how monkey groups interacted, they used a "hierarchical social relations model," which allowed the scientists to predict how two different monkey groups would move through the forest and where their territories would overlap.

The team repeated this process, two monkey groups at a time, until they analyzed the interactions between all 12 monkey groups at Lomas Barbudal. Then, they added the climate-over-time layer to predict how the home range overlap and encounter rates (meaning moments where capuchins from two different groups engaged, often violently) would change with the seasons.

Strength (and weakness) in numbers

Generally, large monkey groups have advantages and disadvantages in the forest. One key advantage is the ability to control resource-rich areas, such as land with fruiting trees known as food patches. A key disadvantage is increased intragroup competition for food, meaning the daily fruit intake of individual monkeys was lower.

The researchers found that during climatic extremes, such as extremely wet or dry seasons, this intragroup competition intensifies, making the group less efficient at foraging overall. Behavior between groups changed with the climate as well. For example, in a typical dry season, large groups often overpower smaller ones to take over areas with more available fruit, such as along rivers.

But the new research found that this long-understood idea doesn't always hold true: During extreme climate events, like a dry season made even drier by the effects of El Niño, capuchins didn't try to hoard the higher-quality areas.

"We don't really know exactly why," Jacobson said. "Maybe there's not as much heterogeneity in the landscape during these resource poor times, and so there's not much that larger groups can monopolize."

Climate extremes, the research suggests, may be upsetting the balance that determines the optimal size of monkey groups. And, as a warming atmosphere makes climate extremes like El Niño or La Niña more intense, it's growing increasingly important to understand how these changes will affect animal societies.

Filippo Aureli, an ethologist at the Universidad Veracruzana, in Mexico, was not involved with this study, but he has studied the effects of extreme weather events on spider monkeys in Mexico. He also registered the infant mortality rates of capuchin and spider monkeys in the Costa Rican dry tropical forest during that 2015 drought. Capuchin populations experienced high infant mortality during the extreme event, while spider monkey populations tended to stop reproducing.

"With climate change, [climate extremes] are going to be more frequent and intense," Aureli said. "And we don't know what's going to happen. For this period [so far], they've held on very well, the spider monkeys, but we don't know for how much longer."

Perry agreed, noting "the importance of having a baseline when you're trying to study rare events like El Niño droughts."

"We know what normal is," she explained. "If you just try to drop in right now in all the chaos that we're starting to feel around the planet, then you really can't study it."

This article was originally published on Eos.org. Read the original article.

A photograph of Earth glowing in deep space, the moon's cratered horizon stretching across its foreground, caught many people's eyes in April 2026. Astronauts captured the image while aboard NASA's Artemis II mission, and like the famous Apollo 8 "Earthrise" image, the picture felt instantly real and inspiring for many.

But when almost anyone can fabricate a visually similar image in seconds from a text prompt using artificial intelligence, how do people decide which image is real?

The proliferation of AI-generated science images in public spaces is not simply a misinformation problem. As a researcher who studies visual science communication and public trust, I believe it also contributes to a crisis of trust in science in the age of AI, and the tools scientists have long relied on to establish visual credibility are losing their grip.

AI-generated images infiltrate science

AI tools are already changing how scientific visuals are created, shared and publicized.

Researchers use them to generate illustrations, create synthetic data, edit lab images and produce materials for education and public outreach.

While AI can help scientists communicate complicated ideas more creatively and efficiently, these same tools blur the lines between illustration, enhancement and fabrication.

In 2024, two papers were retracted after publishing AI-generated figures posessing biologically impossible structures. In April 2026, the New England Journal of Medicine retracted a paper after discovering that a clinical image had been manipulated with AI. These are just cases that came to mass public attention and are likely just the tip of the iceberg. Researchers have warned that AI-generated visuals pose growing threats in fields that depend heavily on visual evidence, such as materials science.

Academic publishers are beginning to adopt AI-detection tools. However, systems designed to detect fake images will almost always lag behind systems designed to create them. Many detectors can identify only image patterns they were trained to recognize. As new AI models emerge, developers must constantly obtain new data and retrain detectors to catch up.

The biggest concern are realistic-looking visuals that subtly distort scientific details while remaining believable enough to pass initial review.

Trust in scientific images

For decades, scientific images carried authority partly because they were difficult to produce. Creating microscope images, climate graphs and space photographs required expensive equipment, institutional resources and specialized expertise. Most people assumed such images represented true observations because very few people could make them.

Research in science communication, including my own, suggests that people judge scientific visuals using a few mental shortcuts. Does the image look technically sophisticated? Does it come from a trusted institution? Does it match what I already believe? Generative AI is undermining all three of these heuristics, or mental shortcuts.

Today, anyone can create a polished, scientific-looking image from a text prompt. Images are also detached from their original source when circulating online. When visual quality and institutional attribution become unreliable cues for judging the credibility of science images, people tend to fall back on something else: their own prior beliefs.

As a result, authentic scientific images that challenge someone's existing beliefs can now be dismissed as AI-generated, whereas fabricated images that confirm them are easily accepted as evidence. AI, in this way, may amplify motivated reasoning — that is, people's tendency to accept what they already agree with and question what they do not.

This shift matters because visuals have long served as evidence for scientific claims. Nonexpert audiences rely on images not only to see what scientists have discovered but also to develop an emotional connection and perceive credibility in the science being presented.

If audiences stop trusting visual evidence altogether, science loses one of its most powerful tools for public communication.

Transparency, not restriction

AI tools offer real benefits for researchers communicating their work to diverse audiences. The challenge is using these tools without quietly transferring AI's credibility deficit onto the science the images are meant to convey.

One practical path forward is for researchers to treat image provenance — where an image came from and how it was created — with the same seriousness they already apply to data provenance.

Scientists routinely disclose funding resources, study methodologies and conflicts of interest. Similar standards may now be necessary for scientific images. Was AI used to generate or modify this image? Is it a direct observation, a simulation or an illustration? What exactly does the image represent, and how was it verified? Can it be replicated by other researchers?

My colleagues and I found that people's familiarity with AI significantly shapes how they judge the credibility of AI-generated visuals. Those familiar with AI tools were more likely to view AI disclosure as a sign of transparency, and some rated clearly labeled AI-generated content as more credible than unlabeled content.

Transparency gives audiences the necessary context to evaluate what they are seeing, but it may not resolve every dispute about how images are made. Responsible use of AI-generated scientific images will require honesty, adherence to professional norms and the collective development of evidence-based standards across fields.

Why authentic images remain powerful

The original Apollo 8 "Earthrise" photograph of 1968 carries significant emotional impact. So do the Artemis II images of 2026.

What makes them meaningful is not simply their beauty. It is their traceable connection to scientific reality. When people look at these photographs of planets, they also know there are astronauts, physical cameras, documented missions and verifiable observations behind the images. In this sense, authenticity is a documented relationship between an image and the world.

In the age of generative AI, scientific institutions can no longer assume audiences will automatically trust their visuals. Trust now depends on transparency, documentation and clear communication about how visual evidence is produced.

Without guidelines and standards, science risks entering a world where every image can be questioned and no image carries inherent credibility.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Who is responsible for AI's output? Artificial intelligence (AI) companies like OpenAI maintain that they are not. In fact, their terms and conditions in 2023 stated that responsibility lies solely with the user. A German court disagrees.

On June 9, a Munich court (subject to appeal) ruled that Google can be liable for false claims produced by its AI summaries, drawing a sharp line between ordinary search results and machine-generated assertions. In other words, AI companies must be held legally responsible for the output that is created by their systems and pushed to users.

The court's logic was simple but profound: Search results point outward to sources, while AI summaries speak in Google's own voice. That distinction matters because it goes to the heart of what kind of speech deserves protection — and what kind is subject to legal scrutiny. The U.S. should follow the German court's lead. In the absence of such provisions, the entire burden of discerning truth from falsehood falls on the reader.

In the U.S., the First Amendment is intended to protect the right to speak, argue, persuade and offend. But freedom of speech is not free of caveats. It does not allow people to incite others to commit crimes, to threaten or to defame, for example. And if speech causes material harm, speakers can be held liable for those harms. When a company chooses to put a synthetic answer engine between users and the web, it is no longer merely hosting speech; it is producing an amalgamation of complex mathematical expressions that, outputted as text, resemble human speech. AI companies want this text to enjoy the same protections user-generated text has, while simultaneously dodging all the responsibility associated with being a speaker.

The roots of this dilemma go back to the 1990s, when the advent of online forums and social media created a new problem. Unlike traditional publishers, forum hosts needed to provide a platform for their users' voices, without being liable for what their users were saying. This problem was addressed with Section 230 of the Communications Decency Act, enacted in 1996. Section 230 was a bipartisan amendment written to preserve the internet as a space where ordinary people could speak (or post) without the forum host becoming liable for every third-party post.

That broad immunity reflected a democratic judgment: If the law made platforms responsible for all user content, many would censor aggressively or stop hosting speech altogether. This would limit free speech. Section 230 was meant to protect the ecosystem of human expression. In this sense, hosts of online spaces can be seen as providing a public square where speech occurs.

The lawmakers who passed Section 230 three decades ago could not have foreseen a world populated by chatbot-generated text. As such text increasingly leads to real-world harms, lawsuits are proliferating and tech companies are deploying a number of often-contradictory legal strategies to avoid culpability. In some cases, they are arguing that AI-generated text is not speech, but rather simply a tool, and that companies are therefore protected as "carriers," not "publishers" by Section 230's protection of a public forum for free expression.

But the companies deploy this argument only when it suits them.

In other cases, they are increasingly reaching for free-speech language to defend AI-generated text because free-speech protections provide broad legal immunity. For example, in a Florida wrongful-death lawsuit against Open AI (maker of ChatGPT), a plaintiff has alleged that the company’s chatbot pushed a 14-year-old to take his own life. OpenAI argued that the chatbot was protected by the First Amendment, though the judge dismissed that defense and allowed the case to proceed.

Neither of these arguments is convincing. AI companies are not merely providers of a public forum, as the words produced by their AI summaries and chatbots are generated by the company's products.

Similarly dubious is the claim that bots should be seen as equal participants in a public square. This is a category error. Free speech is a human right — it protects people as speakers and listeners in a democratic public sphere. Bots do not vote, deliberate, dissent, worship or participate in civic life. They generate text, but they do not possess a moral and political standing. Bots have no skin in the game.

What, then, justifies constitutional protection in the first place? Extending the strongest speech protections to machines would not defend liberty; it would confuse "botput" with free expression. It would, in actuality, extend the strongest free-speech protection to companies. But that requires a separate line of argumentation that ought to be agreed upon by society.

The Munich court's limited and nuanced way of governing "botput" provides a clear way forward.

Given its history with Nazism, Germany does not enshrine free speech quite the way the U.S. does. But the German court's arguments still provide a useful template for a future U.S. ruling.

The Munich court held that if a system simply points users to sources, it resembles traditional search and should continue to enjoy broad protection afforded to aggregators. If it synthesizes claims, imitates the tone of authority, and offers a single authoritative answer generated by an AI, it should carry corresponding duties of care that entail liability for the company.

The need for such safeguards is only growing. AI-generated summaries can be copied instantly, scaled globally, and repeated across interfaces until a falsehood becomes regarded as "truth." That is not a hypothetical concern; it is already happening.

Moreover, it is important to remember that the original intention of Section 230 was to insulate platforms from liability for third-party posts, not their own text.

This is not an anti-innovation argument. AI can be helpful, efficient and genuinely transformative. The law should encourage useful tools while insisting that the companies deploying them remain responsible for the foreseeable harms of their products.

We need clearer rules that keep the internet free for people while preventing machines from laundering falsehood into authority. The German ruling points toward that future. The sooner U.S. law and policy follow, the better chance we have of preserving our shared reality and a healthy democracy.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

As summer in the U.S. heats up, people become more diligent about protecting their skin from the sun. Another option for doing so will soon be available.

On June 9, 2026, the U.S. Food and Drug Administration approved the first new sunscreen ingredient to be permitted for over-the-counter consumer use in the U.S. since 1999 — a chemical called bemotrizinol.

Bemotrizinol isn't new — consumers in Europe and Asia have used it for decades. Some are hailing its long-overdue approval and arrival onto the U.S. sunscreen scene.

I am a biomedical engineer studying skin science — including the damaging effects of the sun's rays. To understand what bemotrizinol does and how it fits in with products already available to consumers in the U.S., let's take a tour of the physics of sunlight and sunscreens.

A short primer on sunlight

Our planet is irradiated by a yellow dwarf star 93,000,000 miles away that we fondly call the sun. It radiates light from its surface at a temperature of about 10,000 degrees Fahrenheit.

The Earth's atmosphere blocks most of the sun's radiation. Of the rays that get through, about half consist of infrared light — which gives you that warm feeling you feel on a sunny day — and 40% visible light, which you are probably familiar with as daylight.

About 10% of those rays are ultraviolet, or UV, light. UV light has the shortest wavelengths of the three types. That makes it the most dangerous — it's invisible and can damage living tissue.

Ultraviolet damage

Physicists further categorize solar UV light into several types, based on the wavelength, which is measured in nanometers. About 95% of it is UVA (315-400 nm) and 5% is UVB (280-315 nm). Sunscreens need to be able to block those rays from penetrating the skin.

The sun also emits two other types of UV light — UVC (200-280 nm) and vacuum UV (100-200 nm) — but these are stopped by the atmosphere, so sunscreens do not typically need to be able to block them.

Scientists used to think only UVB was harmful because UVB rays cause sunburns. But today, researchers know both types of UV can damage the skin.

UVB, with its shorter wavelength, has more energy, but UVA can penetrate the skin more deeply. And all UV can degrade the integrity of your skin, damage the structure of your DNA and cause skin cancer.

The only natural safeguard your body has against UV light is a microscopically thin layer of a pigment called melanin in your epidermis. The skin produces more melanin when exposed to the sun — that's what tanning is.

This extra melanin does protect the skin, but not fully. That's why protecting your skin with sunscreen is so important.

Sunscreens old and new

Sunscreens come in two different forms — mineral and chemical.

The first chemical sunscreen, developed in 1891, was an ointment made from quinine — a plant-derived compound that makes tonic water bitter.

Chemical sunscreens cover the skin in a transparent coating, acting like a solar sponge. They absorb UV photons and undergo a harmless chemical reaction, then dissipate the energy as heat. Bemotrizinol falls into this category.

Mineral sunscreens such as zinc or titanium oxide ward off the sun's rays by forming a protective film that also absorbs most UV light, but reflects some of it. Unlike chemical sunscreens, the film absorbs the light naturally, without a chemical reaction — which is why they are often visible as a white film on the skin.

Chemical sunscreens that have been available in the U.S until now combine ingredients like avobenzone, the most widely used UVA filter, with UVB filters such as octinoxate, octocrylene octisalate and homosalate. Working together, these substances protect the skin against the broad spectrum of ultraviolet rays.

These sunscreens are only effective for a short time because they are degraded by the chemical reactions they undergo, which means they must be frequently re-applied.

Another important element of sunscreen — whether mineral or chemical — is its Sun Protection Factor, or SPF. This number tells you how well a sunscreen prevents your skin from burning — in other words, what amount of UVB rays it absorbs.

An SPF of 2 would mean a sunscreen cuts your exposure to UVB rays in half, filtering out 50% of those rays. An SPF of 30 means the sunscreen lets just 1/30 of the rays penetrate your skin - which is 3.3%. So it blocks about 97% of the UVB rays.

Dermatologists generally recommend using a sunscreen with an SPF of at least 30.

Benefits of bemotrizonol

Bemotrizinol, while new to the U.S., isn't a new compound. European regulators approved it in 2000. Chances are, if you brought back sunscreen from a vacation in Mexico, Europe, Canada or South Korea, you may even have some laying around your house.

One benefit of bemotrizinol is its ability to filter both UVA and UVB rays, so it doesn’t have to be mixed with other products to do the job.

It has some other beneficial features as well. First, its molecules prefer to sit on the surface of the skin rather than being more readily absorbed into the bloodstream, which can occur for some formulations.

Such absorption has raised concerns that sunscreens might be harmful — though this has not been demonstrated in people, it may discourage some people from using it.

Bemotrizinol also does not degrade as readily in the sun than other chemical sunscreen products. That photostability means it can last for four to eight hours, rather than having to be applied every two hours or so.

Regardless of the type, as a skin scientist I can say with certainty that any sunscreen is better than none. Your skin does an excellent job protecting you from the world outside — so make sure you protect it in return.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Pets form an important part of many people's lives, providing meaningful companionship. However, our pets can sometimes also be a source of unwelcome pathogens and diseases, particularly if they frequently roam outdoors.

We are ecologists and a veterinarian who study wildlife health and the movement of pathogens among wildlife, domestic animals and people. If you let your cat outdoors, or if outdoor cats visit your yard, our recent findings may be relevant.

Zoonotic pathogens are organisms that can infect both animals and humans. From a pathogen's perspective, humans are just another animal host. Wildlife is often emphasized as a source of emerging disease for humans because there are vastly more wild animal species than domestic animal species.

However, even if a pathogen is capable of infecting people, it needs a way to reach us. Humans share more zoonotic pathogens with domestic animals than with wildlife, because domestic animals live close to us. Pathogens benefit even further if they can infect a companion animal.

In our newly published research, we compiled data from more than 400 studies to investigate how a cat's lifestyle, whether they're mostly indoors, outdoor-roaming or feral, affects that cat's likelihood of carrying pathogens that can infect people.

Across this compilation, there were nearly 100 pathogens detected in cats that are considered zoonotic and capable of infecting humans. Familiar examples are rabies, Toxoplasma gondii, roundworms and Salmonella.

Our research

We found that outdoor-roaming pet cats had three to five times the odds of carrying a zoonotic pathogen compared with indoor-only cats. More surprisingly, cats allowed to roam outdoors had similar odds of carrying at least one zoonotic pathogen as feral cats. Outdoor-owned cats carried fewer types of pathogens than feral cats, but the same pathogens that infect feral cats can also infect owned cats.

These risks become a large-scale problem because pet cats that roam freely interact closely with people, wildlife and other domestic animals. Across the studies we reviewed, about 60 per cent of owned cats had unsupervised outdoor access; in some regions, that rate exceeded 90 per cent.

Roaming cats hunt, interact with wildlife or other domestic animals, and move through environments contaminated with pathogens and toxins. Research suggests that cat owners may underestimate hunting by around 80 per cent, meaning that many prey captures and animal contacts go unnoticed.

These interactions are not uncommon and not limited to so-called pest species. Single-country estimates of wildlife killed by cats run into the billions, with more than 2,000 wildlife species documented as prey for domestic cats.

Cats hunt animals that can carry zoonotic pathogens, including rodents, birds and bats, many of which would otherwise have little direct contact with people. Owned cats might bring home rodents carrying viruses, and there are documented cases of cats bringing rabies-positive bats into homes. A cat returning home with prey can therefore create a pathway by which pathogens circulating in wildlife populations reach people.

In addition, it is not only owners who are at risk. Outdoor cats defecate in gardens, parks, playgrounds and other shared spaces, potentially leading to high contamination rates. One study estimated that outdoor cats deposited more than 60 tonnes [60 tons] of feces per 10,000 households each year.

Depending on the parasite, feces can contain hundreds to hundreds of thousands of parasite eggs that can persist in soil or water for months to years, which can infect people or other animals that come in contact with those eggs.

What cat owners can do

The most straightforward intervention is also the most economical and humane: prevent unsupervised roaming. That does not mean denying cats access to the outdoors. It can mean building "catios" or enclosures, leash walks, supervised time outside or other forms of contained outdoor access.

Veterinary care still matters. Treating existing parasitic infections and vaccinating against diseases like rabies are essential precautions, even for indoor cats. Since neither vaccines nor anti-parasitic treatment cover the full spectrum of wildlife-associated pathogens, managing exposure remains the more comprehensive protective approach.

The free-roaming debate is often framed as a false choice: either cats roam freely, or they are deprived of a natural life. That framing is misleading and inconsistent with how we manage other companion animals.

We do not assume dogs need unrestricted access to roads, neighbors' yards or to hunt wildlife to have good welfare. Indoor cats and cats with supervised outdoor access can live healthy, enriched and longer lives.

Policies and strategies that address how and where owned cats roam outdoors can help safeguard biodiversity, feline and wildlife welfare and public health. That is the central insight of One Health, that the same choices that protect ecosystems can also protect the animals and people who share them.

This article was co-authored by David Lapen, who works for and receives research funding from Agriculture and Agri-Food Canada.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

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Humans are the only species known to use fully symbolic language: a system capable of expressing abstract ideas, imaginary worlds and endless combinations of meaning. But how did we get there?

The origins of language have fascinated philosophers, scientists and storytellers for thousands of years. Despite all our advances in linguistics, archaeology and cognitive science, we still don't know exactly how language began.

That uncertainty hasn't stopped people from trying to solve the mystery. In fact, some of the earliest theories of language's origins are among the strangest and most entertaining ideas in the history of science.

Bow wow, ding-dong

In the 19th century, scholars proposed a flurry of curious theories to explain how speech first emerged. Many of these theories were given playful nicknames by the German philologist Max Müller, who intended them partly as satire. Yet the theories were genuine attempts to tackle one of humanity's biggest questions.

The most famous is probably the Bow-Wow Theory. This suggested language began through imitation of natural sounds. Early humans, according to this theory, copied the noises around them: animal cries, splashing water, thunderclaps and birdsong. Words such as "buzz," "hiss," "bang" and "splash" seem to support the idea because they sound like what they describe.

But there is a problem. Different languages hear the same sounds differently. English dogs go "woof" or "bow-wow," but in Turkish they go "hev-hev," while Indonesian dogs go "guk-guk." Even animal noises, it turns out, are filtered through culture and language.

And onomatopoeic words (words that imitate sounds) make up only a tiny fraction of our vocabularies. Most words sound nothing like their meanings. For instance, there is nothing inherently tree-like about the word "tree."

That brings us to the Ding-Dong Theory, which argued that sounds and meanings are naturally connected in some deeper, almost mystical way.

Some words do seem to fit their meanings uncannily well. "Mini," "teeny" and "itsy-bitsy" feel small and delicate. "Lump," "rump" and "plump" sound heavier and rounder.

Modern linguists call this sound symbolism. One famous experiment asked participants to match two nonsense words, "bouba" and "kiki," to two shapes: one rounded and one jagged. Most people matched "bouba" with the soft shape and "kiki" with the sharp one.

The effect is real, but it is limited. Most language still appears to be arbitrary, which means there is no natural reason why a particular sound should mean a particular thing.

Pooh-pooh, la-la, ye-he-ho

Other theories focused less on imitation and more on emotion and social interaction.

The Pooh-Pooh Theory proposed that speech began with instinctive emotional cries such as "ouch," "oh" or perhaps less publishable exclamations uttered after stubbing a toe. According to this idea, language evolved from spontaneous vocal reactions to pain, surprise, fear or joy.

Again, though, there are complications. Interjections vary widely across languages. English speakers say "ouch." Greeks say "aou." Czechs might exclaim "ach." Emotional sounds are not nearly as universal as they seem.

Then there is the wonderfully named Yo-He-Ho Theory, which suggested language emerged from rhythmic chants used during collective labor, like sailors chanting "yo-heave-ho" while hauling ropes, or workers singing together to coordinate physical effort.

The theory may sound quaint, but modern researchers do think rhythm, cooperation and social bonding played important roles in human evolution. Language is, after all, deeply social.

Another proposal, the La-La Theory, linked language to music. Charles Darwin entertained the possibility that speech evolved from musical calls used in courtship and emotional expression. Before humans spoke, perhaps we sang?

Some modern theories echo this idea. One hypothesis suggests that, as early humans began walking upright, parents increasingly needed to soothe babies from a distance. Sing-song vocalizations, cooing and proto "baby talk" may have helped strengthen emotional bonds and eventually paved the way for speech.

Gestures, symbols and brains

Today, most scientists think no single theory fully explains language origins. Instead, language probably emerged gradually through a combination of gestures, vocalizations, facial expressions, social cooperation and increasing cognitive complexity.

Some researchers argue that language began with gestures before shifting to speech. Others believe language evolved as a tool for social bonding, allowing larger groups of humans to cooperate and share information. Still others see language as tied to the evolution of symbolic thought itself: our ability to imagine, plan, remember and communicate abstract ideas.

Biology is also a factor. Humans have developed unusually precise control over the tongue, lips and vocal tract. We have evolved specialized brain regions linked to language processing.

But anatomy alone cannot explain language. Parrots can mimic speech sounds. Many animals communicate. None, however, appear to possess grammar and symbolism on the human scale. And, frustratingly, early language leaves no evidence behind. Spoken words don't fossilize.

That lack of evidence is one reason the topic became so controversial that, in 1866, the Société de Linguistique de Paris banned discussions about language origins altogether, dismissing the field as hopelessly speculative.

Of course, theories about language origins also appear in religion and mythology. In Greek mythology, the messenger god Hermes was associated with language and communication. In the Hindu tradition, the goddess of knowledge and speech Saraswati bestowed Sanskrit upon humanity. In the Judeo-Christian tradition, language was a gift from God, who enabled Adam to name the animals in the Garden of Eden.

These stories reflect something deeply human: our urge to explain where language came from, because language itself feels almost magical. Every theory of language origins captures a small piece of the puzzle. Imitation, emotion, rhythm, music, gesture, cooperation and symbolic thought probably all played some role.

But none can provide a complete answer. The truth is that language evolved so long ago, and likely so gradually, that we will never pinpoint a single moment when it began, unless someone invents a time machine.

The birth of language will probably remain one of humanity's greatest unsolved mysteries. Still, the theories themselves tell us something important. Humans are always trying to explain what makes us human. And language may be the most human thing of all.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Humans are not isolated, interchangeable biological machines. We seek medical care carrying complicated backstories, life experiences, and cultural perspectives that shape how we experience illness, communicate pain, and respond to treatment.

For decades, medicine ignored this fact and the cost fell heaviest on patients from marginalized groups. Study after study has documented the result: stark disparities in health outcomes that track closely with race, income, zip code, and immigration status.

Medicine has only recently begun to reckon with this blind spot. For the last few years, medical students across the country have been required to receive training in what are called "social determinants of health" to better understand how trauma, poverty, racism, and life experience shape what patients bring into the exam room and what they need from the people treating them.

But the board governing medical school accreditation no longer wants this training to be mandatory. This would be a big step back for medicine. Keeping these standards in place is essential for making a more effective medical workforce that can deliver the best care possible while doing no harm.

My experience with both sides of the medical system — as a second-year MD/PhD student and a patient — shows why this training is so necessary.

A few months after I turned 21, I went in for a routine checkup and was told by my physician that I needed my first Pap smear. I understood the importance of the test, but it wasn't something I had prepared for that day.

When the exam began, I flinched at the cold speculum. My physician noted my tension and said it was interfering with the exam. I tried to relax, but as a survivor of sexual violence, the sensation triggered memories I hadn't expected. I asked her to slow down and at some point, stop. Instead, one of the physician assistants held my legs open as the speculum moved further. As the exam wrapped up, the only sounds in the room were my occasional sniffles as I cried quietly.

My mother, too, has endured the experience of being unheard by physicians. An immigrant from Accra, Ghana, she had healthcare providers hear her accent and see her non-citizen status and make a quiet calculation: one that placed her judgment below theirs and created a lifetime of consequences she continues to deal with to this day.

At five years old, the phrases "structural violence" or "medical racism" were not yet a normal part of my vernacular, but I didn't need a college education to understand that my mother's immigrant identity shaped the care she received, or more accurately, the care that was withheld from her. Her experiences were the consequences of a system that delivers less attentive, less thorough, and less humane care to patients who are Black, low-income, or immigrant. It has done so for so long that the disparity reads as normal.

We've finally started to see a shift in that system, however slight. A year after the first Pap smear, I needed an additional one. Despite knowing this screening was essential for my health, I was still very hesitant and expressed my fears to my physician. This time, however, my physician used trauma-informed care throughout the procedure. She checked on me before we got started, narrated each step, and moved slowly so I could stop and breathe when I needed to. She gave me back the control and autonomy I had lost. Once we were done, she checked on me before letting me get dressed.

When the door closed, I let myself sob, not from pain, but because she cared. I mourned the version of me that wished she could have been granted that care the first time, and I found myself mourning my mother too, feeling a connection to her in the most unfortunate way.

The difference in my two experiences was not incidental. It is the result of training. Medical education now teaches future physicians to recognize how trauma, lived experience, and social context shape patient care, which collectively is called structural competency.

Such training equips future doctors to ask better questions, communicate more effectively, and avoid causing harm, even during routine procedures. Since starting medical school, I have seen how this training shapes the way my peers and I understand patients. A patient with uncontrolled asthma is not simply "noncompliant" with their treatment regimen, but may be living in substandard housing with mold exposure. A patient with poorly controlled diabetes may not lack "motivation," but may face food insecurity or unstable income.

Structural competency enables physicians to see the full picture and ultimately treat patients with the dignity they deserve. Rather than simply adjusting a medication dose or repeating discharge instructions, a structurally competent physician might coordinate with a social worker, connect a patient to community resources, or advocate for systemic changes that no prescription can address.

Research supports that structural competency training improves both how physicians practice and how patients fare. A 2016 pilot study in California found that such training led to better patient satisfaction scores, and a more recent study found that it increased residents' sense of competency.

The training curriculum has only been required for a few years, but some early evidence hints that it could yield positive patient outcomes. Physicians trained to recognize these factors are also more likely to advocate for policy changes related to housing, education, and income equality: key determinants that influence chronic disease prevalence, infant mortality rates, and overall life expectancy.

The American College of Physicians has formalized this thinking, publishing recommendations urging physicians to ask about and address social factors as a core part of patient care, and real-world implementation backs this up. One Michigan physician network that began systematically screening patients for social needs in 2017 conducted over 20,000 screenings and used the results to connect patients to social services.

This is partly why the Liaison Committee on Medical Education (LCME) that accredits med schools currently mandates that structural competency be taught in every school — but that's about to change. In the wake of the second Trump administration's attack on diversity, equity and inclusion efforts, the committee is indicating that it will likely no longer require structural competency training as a part of medical education.

It would be reassuring to think that even in absence of this training, nothing would change; that good physicians will remain attentive, and empathy will fill the gap. My mother's story and my own suggest otherwise. Medicine does not become neutral in the absence of this education. It defaults, reverting to entrenched habits of thinking that ignore the nuances of how a patient's background informs their care.

At a time when mistrust in medicine is already high, we cannot afford to strip away the training that helps rebuild it. So what can be done?

Medical students must advocate within their institutions to preserve and strengthen structural competency education. Faculty must keep such training in their medical curriculum, even if LCME doesn't require it. Most importantly, professional organizations from local institutions to national bodies like the American Medical Association, must speak out clearly and use their congressional lobbying powers to push for the LCME to reverse its decision.

I love medicine. I am training to become a physician-scientist because I want to help build a future where care is both innovative and just. But I will not stand by while medicine forgets its own history. We have made progress, inches in the right direction. So we must do all that we can to ensure that we don't fall back, because the consequences will ultimately be the trust, the support and the lives of our patients.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

One argument often used to quell concerns about the rising energy and resource demand of data centers is that artificial intelligence (AI) models will need less in the future as they improve and become more efficient.

But this seemingly logical thinking is a trap, according to a new United Nations report that quantifies the environmental costs of AI.

The report estimates that by 2030, AI's energy use could double to consume 3% of the world's electricity, produce emissions to equal the UK and deplete more water for cooling than the annual drinking water need of the global population.

It also anticipates the use of AI will follow an economic principle known as the "Jevons paradox", which predicts that when technological improvements increase the efficiency of a resource, it leads to a rise, rather than a fall, in the total consumption of that resource.

The paradox is named after economist William Stanley Jevons who observed this effect with the use of coal in 19th-century England. Efficiency gains did not reduce overall consumption. Instead, the lower costs resulted in expanded use and higher overall demand.

As AI models become cheaper and more attractive, the report expects this to encourage new uses and higher volumes of use, eroding and possibly erasing any savings from efficiency advances.

To avoid falling into this trap, it lays out a roadmap for responsible AI use based on guiding principles of transparency, efficiency by design, equity and justice, lifecycle responsibility, global cooperation and sustainable use.

The scale of the problem

Last year, data centers already consumed as much electricity as Saudi Arabia, which ranks as the world's 11th largest electricity consumer.

If electricity use doubles as projected by 2030, the associated carbon footprint would require 6.7 billion trees grown over ten years to offset this demand.

Data centers would also require 9.3 trillion liters of water and land nearly ten times the size of Mexico City.

Beyond resource use, the report also underscores the structural inequity at the heart of the AI boom, with only 32 nations hosting AI-specific cloud infrastructure and 90% of that capacity located in the US and China.

It warns of a widening digital divide between nations that build and control AI systems and those that consume them, with the latter often bearing a disproportionate environmental burden caused by mineral extraction and e-waste.

Responsible AI use

Two main forces shape AI's operational footprint: how much we use it and how we use it.

This involves all tasks AI models perform, from text and code generation to image and video. Each of these tasks requires different levels of computational effort.

The model choice also matters as each AI system performs these task with distinct energy and environmental costs.

The report argues responsible AI requires full value-chain governance, from mineral sourcing to recycling and safe disposal.

It calls for a twinning of capability and environmental stewardship — thinking about both what AI can do for us and the protection of the natural environment.

This would mean making environmental disclosures a routine part of AI development, at both the model and task level, and incorporating projected AI demand in climate and energy planning.

Responsible AI is crucial as countries are promoting and adopting AI across government and the public sector.

In Aotearoa New Zealand, the government has launched a national AI strategy and a public service AI framework.

While the framework was informed by the OECD's values-based AI principles, including inclusive and sustainable development, there is no requirement for environmental disclosures and no regulator compiling energy use or emissions.

Likewise in Australia, improving public services is part of the national AI plan. For example, the National Film and Sound Archive of Australia has created Bowerbird, a machine learning-enabled mass audio and video transcription engine, to document material. The Department of Veteran's Affairs has developed a proof-of-concept tool to see whether AI can help speed up the processing of claims.

Both countries take a deliberate "light touch" and principles-based regulatory approach to AI. But this approach risks overlooking the growing environmental cost of AI that can't be solved by improving it.

The natural environment is foundational to the economy, culture and wellbeing. It should be at the center of our thinking. It’s time to rethink the AI innovation playbook and shift focus toward a sustainable tech future.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Around 1 in 5 Americans say they've seen a ghost. I'm not one of them, and I probably never will be. I blame my brain.

Let me explain. No one can say definitively that ghosts exist, but many people believe they do. Roughly three-quarters of Americans believe in some form of paranormal activity — not only ghosts, but psychic abilities, precognitive dreams, mediums and anything else that conventional explanations can't account for.

As a psychology professor, I often think about the subjectivity people use when interpreting experiences. I wonder, then, if there are perfectly ordinary explanations for seemingly extraordinary experiences. Maybe a perfect storm of everyday factors can converge and trigger the sensation of a paranormal experience.

In my new book, "Science of the Supernatural," I explore the idea that the human brain might be creating an experience of the supernatural by misinterpreting the external world. Here are three factors that might trick your brain into creating a fake ghost:

Haunted factor #1: Environmental stimuli

Anyone who's ever watched a ghost hunting show has seen the paranormal investigator mutter something like "The EMF's going crazy" when there's purported supernatural activity afoot. Electromagnetic fields, or EMFs, are invisible areas of energy created by electrically charged particles.

At present, there is no direct evidence that humans can consciously sense EMF the same way we can touch, see or hear things in our environment. But with a handheld device purchased at a local hardware store, you can measure them anywhere. An EMF detector picks up electrical or magnetic activity, whether human-made or otherworldly. But do EMF fluctuations relate to paranormal activity?

The scientific method might help answer this question. In one study, conducted in the South Street vaults underneath Edinburgh, Scotland, EMFs fluctuated more in areas with a history of ghostly happenings. Another study found greater variability of EMFs in the more "haunted" areas of Hampton Court Palace in England.

People might unknowingly be detecting changes in environmental stimuli, like electromagnetic fields. The question then becomes: Did the ghost cause the EMF, or did the EMF cause the ghost?

To date, only one research group has attempted to experimentally manipulate environmental factors, including complex EMF, and measure subsequent perceptions of the paranormal.

Participants did report many peculiarities, ranging from feeling dizzy to feeling like they were detached from their bodies and even sensing a presence — but these experiences didn't correspond to how the researchers varied environmental conditions, like EMF intensity. Interestingly, the people who described anomalous experiences were the same people who believed more strongly in the paranormal.

Do environmental factors like EMF lead to perceptions of the paranormal? On the one hand, there is a correlation between reportedly haunted places and EMF variability. And there are some indications that humans can detect magnetism. On the other hand, experimental manipulation of EMF did not relate to weird perceptions in a lab setting.

I think we need to look into other haunted factors.

Haunted factor #2: Neurological mix-ups

By applying a small electrical current to the side of the head, usually to evaluate a patient for a clinical procedure, researchers have observed some strange effects. One case study described a patient who experienced an "illusory shadow figure" that was mimicking, and even interfering, with their movements. Other people have reported out-of-body experiences.

Experimental evidence suggests that this brain area, the temporoparietal junction, is probably crucial for the feeling of embodiment — that you inhabit your own body. Disrupting this brain area seems to trigger a sensation of disembodiment.

Neuroscientists aren't completely sure how the sense of embodiment is built in the brain. The brain probably integrates bodily senses, like balance and position, with other internal processes, like a sense of self and agency. When this integration is altered, a person will experience very strange sensations.

Sometimes, misinterpretation of sensations from the body can happen during sleep, when your brain shuts out the external world. During rapid eye movement, or REM, sleep, when most vivid dreams occur, the brain sends messages that prevent movement of skeletal muscles. This inhibition causes complete paralysis during REM sleep. It is a neurological safeguard; without it, you would be likely to act out your dreams.

Some people, though, wake up during REM sleep and find that they cannot move. They may simultaneously experience rich hallucinations — the remnants of their dream. This experience passes quickly. But in that moment of sleep paralysis, the neural signals that control skeletal muscle movement are inhibited, resulting in a mismatch of feedback from the body to the brain. Most people respond to the missing sensory information with fear, which makes them more likely to experience the sights and sounds from their dreams as reality.

Haunted factor #3: Personality traits

Living through a paranormal encounter requires that a person label their experience as such. If a believer were exposed to fluctuating EMFs, for example, they might be quick to categorize the strange sensation as paranormal. A skeptic might note they felt weird or off, but probably not point to a paranormal explanation.

There's a growing body of research that suggests people with certain personality traits are more likely to believe in the paranormal.

For instance, some people are hyperaware of unconscious perceptions and ideas, which then permeate their consciousness. Often, these traits are associated with magical thinking, distorted or unusual thoughts, disorganized behavior and, sometimes, trouble forming close relationships.

Psychologists refer to this set of traits as schizotypy. They're related to schizophrenia, although being high in schizotypy doesn't mean you will be diagnosed with the disorder of schizophrenia. People with high levels of schizotypy are more likely to believe in the paranormal. They're also more likely to experience disembodiment and spontaneous sensory perceptions and have trouble discriminating between self and others.

All of these traits relate to the function of the temporoparietal junction — the brain area that helps you know you're located within your own body.

When haunted factors add up to a ghost

While I cannot say for sure whether ghosts exist, I can propose a plausible explanation for why some people might be more prone to apparent paranormal experiences than others.

Consider a person who believes in paranormal phenomena who experiences a natural change in electromagnetic fields or an episode of sleep paralysis. Those experiences induce unusual sensations that this person cannot explain. Searching for meaning in ambiguity, this person distorts their distinction between internally and externally generated sensations. They settle on the only explanation that makes sense to them — that this strange feeling they experienced was a ghost.

My guess is that belief in the paranormal is the glue that holds the haunted factors together to create the (mis)perception of a ghost.

One experiment asked participants to walk through a disused theater in Decatur, Illinois. Some were told that the theater was haunted, and some were not. Several participants noted weird sensations that they attributed to paranormal activity — but only those who believed that the theater was haunted reported these sensations.

Belief alone might not create a ghost, but belief combined with at least one haunted factor — environmental stimuli, neurological hiccups or psychological conditions — might be enough to make a ghost real.

This becomes a chicken-or-the-egg riddle — or in this case, the ghost or the EMF. Someone who is more likely to be sensitive to environmental factors or who experiences sleep paralysis might create belief from their experiences. When someone cannot explain these experiences with any "natural" explanation, a supernatural explanation might be the only one that makes sense.

I've never noticed EMF. I've never experienced sleep paralysis. I'm pretty sure I don't have personality traits like schizotypy. I don't believe in the paranormal. And I don't think I'll ever see a ghost.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Imagine receiving a test result that tells you your body is biologically five years older than your chronological age. You exercise regularly, get good sleep, eat healthy meals and have a happy personal life. What have you been doing wrong? Can this test be trusted?

Dozens of companies are marketing products that promise to reveal a person’s "true" biological age — that is, how well your body is functioning — for a price ranging from around US$30 to over $1,000. These products are based on epigenetic aging clocks, which are research tools that estimate age based on a person's DNA. These clocks are reshaping how scientists study aging and how the public thinks about it.

But while epigenetic clocks are highly effective research tools to study aging at the population level, they aren't designed to make claims about the health of individuals.

We are biobehavioral health scientists who study how early development and environmental factors across the lifespan shape biological aging, influencing health and disease decades later. As researchers who use epigenetic clocks in our work, we have found them to be highly informative tools when studying large numbers of people. But these clocks can provide faulty results at the individual level, and they do not meet the standards required of common medical tests.

What are epigenetic clocks?

Measuring reversible chemical changes to DNA, known as epigenetic marks, can provide information about how your body is aging.

Using DNA obtained from routine blood draws, researchers can measure millions of these epigenetic marks in an individual. Running statistical algorithms on this information can produce a single value that represents that person's epigenetic age, analogous to chronological age.

Epigenetic clocks work because the chemical marks on DNA can shift over time and are influenced by lifestyle, stress and the environment. These changes capture aspects of aging that chronological age alone may not reflect.

In this way, epigenetic clocks help scientists identify the experiences, exposures and behaviors that may accelerate or slow biological aging.

Not for individual health decisions

Why can't epigenetic clocks provide reliable results about biological age for individual people?

First, there are dozens of different types of epigenetic clocks, each designed for a specific purpose. Some are used to predict a person's age, while others are used to predict how fast someone is aging or how many years until they die. These different clocks do not always agree with one another, even when used on the same person.

Second, epigenetic changes are dynamic, making age predictions sensitive to short-term fluctuations in diet, environmental exposures, illness, time of day and other transient factors. As a result, estimated age could vary substantially depending on when someone is tested.

Third, constructing epigenetic clocks is technically challenging, and there is no established gold-standard method for generating clocks across laboratories. For example, testing epigenetic age in saliva versus blood samples can yield substantially different results for the same person. The technologies used to measure epigenetic marks have also evolved over time and will likely continue to improve. As these methods change, the original algorithms designed for specific measurement platforms may not perform the same way.

Fourth, scientists do not universally agree on what aging means, in part because it is a very complex process. Reducing that complexity to a single number, such as an epigenetic age, can be misleading.

Finally, epigenetic clocks are influenced by a person's history of trauma, discrimination and early life adversity. This makes their use at the individual level potentially problematic. On average, marginalized communities tend to show signs of accelerated aging when assessed with epigenetic clocks. If insurance companies began using epigenetic age estimates to set premiums, many people could face higher costs for biological differences shaped by circumstances beyond their control, potentially deepening existing health disparities.

Studying how aging unfolds over time

While epigenetic clocks are not appropriate tools for individual health decisions, this does not mean they lack value.

Researchers have used epigenetic clocks to discover lifestyle habits that can, on average, slow down aging. Some examples include reducing daily calorie intake, exercising regularly, maintaining a healthy diet, getting enough sleep and avoiding smoking.

Epigenetic clocks can also help test new drug therapies aimed at slowing down specific aging processes. For example, researchers have shown that rapamycin, a drug connected to various aging processes, can reduce the epigenetic age of human skin cells. There is also some evidence that a treatment designed to regenerate the thymus may slow or even reverse epigenetic aging after one year of treatment. However, researchers have seen these effects only when looking at groups rather than individuals.

Epigenetic clocks are helping scientists advance scientific research on the aging processes, but they aren't medical tests to measure individual health. In the future, epigenetic measurements may play a useful role in guiding personal health decisions. But for now, epigenetic clocks sold as biological age tests are best used and refined by researchers who are studying populations rather than individual people.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

If you have ever tried to repair something, realized that it was beyond your financial or technical means, and ended up buying a new one, you are not alone. Repairing electronics and household appliances has not been a real option in the United States for decades now, particularly for items that have proprietary software in them.

Absurd situations have proliferated. It can cost about the same to buy a new printer as it does to replace the ink cartridge. The U.S. Department of Defense cannot repair the weapons systems it purchases because the intellectual property rights remain with the manufacturer. John Deere, the farming equipment company, doesn't allow farmers to access the software needed to repair their own combines and tractors because, while the purchase covers the physical machinery, it does not cover the software.

One consequence, in addition to cost and frustration for consumers, is environmental harm. The U.S. is the world's second producer of electronic waste after China, to the tune of about 43 lbs (19.5 kg) of electronic waste annually per person. Only 25% of this e-waste is recycled.

The right-to-repair movement emerged in response, calling for people to be able to repair what they purchase, or have third parties do the repair work, without unnecessary financial, legal or technical barriers. Right to repair seems to be a rare area of bipartisanship in Congress. The Warrior Right to Repair Act — introduced in 2025 by a Democrat —and the Repair Act — introduced by a Republican — are two ongoing legislative initiatives to create a federal legal framework that would make it easy and cheap for American users to repair their devices. Both bills are fiercely opposed by industry groups.

As a scholar of American culture, I found through my research that the origins of the legal and technical obstacles to product repairs lie in debates in the 1980s over new media and copyright guardrails.

Hollywood and VCRs

The rapid rise and popularity of video cassette recorders, or VCRs, in the late 1970s transformed films and TV shows from transient experiences into tangible consumer goods. As I show in my book, "Videotape," despite the potential for extra revenue, Hollywood was alarmed by the fact that users were now able to copy films on videotape, and tried to stop the technology. Today's repair bans are part of that story.

The first U.S. copyright provisions were embedded in the 1790 Constitution. Over time, the law was amended to include new technologies, but at the core of future legal arrangements remained the initial intent: to protect the financial rights of creators while giving enough access to information for society as a whole to progress.

Until the second half of the 20th century, the American doctrine of fair use, which allows the unlicensed use of protected works under specific conditions, allowed judges to prevent copyright law from negatively affecting public interest. Organizations such as public libraries, book clubs, universities and news organizations benefited from this legal approach. The concept was codified into American law in the Copyright Act of 1976.

When the film studios took Sony to court to stop the production and sale of video recorders in 1976, they argued that Sony's product encouraged copyright infringement. But the U.S. Supreme Court ruled in 1984 that taping TV content for personal use did not violate copyright law, expanding the understanding of fair use.

The industry then focused on finding a technological solution to the piracy problem and on securing stricter legal protections for its products.

They identified the digital versatile disc, or DVD, as a safer alternative to the VHS tape. Initially, the DVD was a read-only format. It took a few more years of engineering before affordable recording was possible. Even then, the process was far more complicated for users than videotape recording. In 1997, barely one year after the video disc was launched, all of the Motion Picture Association of America member studios joined the DVD Forum, collectively adopted the new format and started to phase out films released on videotape.

Copyright and virtual locks

Then came digital rights management. Collectively, the term refers to the battery of technological tools that the industry developed in order to control user access to content. These include encryption software and various forms of authentication or enforcement software that limit which types of digital activities users can perform. For instance, some mechanisms block the option to download or share a digital file.

The Digital Millennium Copyright Act, or DMCA, signed into law by President Bill Clinton in 1998, provided the broad legal framework that allowed these technological locks to expand far beyond entertainment, including to software. The Digital Millennium Copyright Act reflected a new alignment in interests between the entertainment and software industries. It increased existing penalties for copyright infringement online and criminalized any technology used to bypass technological locks. The law was adopted although at the time — and since then — critics warned that it could stifle innovation and increase costs for consumers.

Since 1998, more and more consumer products, from toys to dishwashers, use microchips and proprietary software protected by copyright. Because of the Digital Millennium Copyright Act, third party repairers cannot alter or bypass the proprietary software. If they did so, they would be liable for infringing the manufacturer's intellectual property rights, as is the case for John Deere farm equipment. Some electronics are even designed to make tampering with the product impossible.

Manufacturers maintain that only they or authorized personnel can and should repair their products. These repairs are often quite costly. When getting a product repaired becomes almost as expensive as buying a new one, many consumers will choose to buy and throw repairable items away.

Rising resentment over repair bans

Technology tends to outpace existing legal arrangements. With over 80% of Americans supporting the right to repair, it remains to be seen when or if American law will catch up with the unexpected consequences of a law meant to protect the intellectual rights of the creative industries, but which is now hurting consumers' pocket books.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Fingerprinting transformed police investigations by making it possible to place a suspect at a crime scene with physical evidence. Similarly, genome sequencing has changed how disease detectives study outbreaks by allowing them to read a pathogen's genes as a biological record of where it came from and how it spread.

One way to think about sequencing is to imagine a virus or bacteria's genome as a recipe book. Each gene is a recipe for making a protein. When scientists sequence a pathogen, they read the order of the genetic letters in those recipes.

Over time, small changes appear in the recipes as the pathogen mutates. By comparing those changes in samples collected from different places and times, researchers can determine which infections are related and estimate when and where the pathogen entered a population.

Scientists have used sequencing in this way to track outbreaks of COVID-19, Ebola, mpox and foodborne illnesses. This information helps public health investigators connect cases that might otherwise seem unrelated.

Still, genomic sequencing has limits. It can show that different pathogen strains are related, but it cannot fully explain why an outbreak began in one place, why it spread in a particular direction, or how human behavior shaped its course. Answering those questions requires combining genomic data with historical records, archaeological artifacts, trade records and epidemiological investigations.

I am a chemist and the author of "Diseases Without Borders: Plagues, Pandemics, and Beyond," a book for young adults on infectious disease and the ways it has shaped human history. In my research, I've found that while the genome can help researchers trace the evolutionary trail of a pathogen, other fields are needed to explain the environmental conditions that allowed this trail to become an outbreak.

Ancient DNA tells only part of the story

Advances in DNA sequencing and extraction over the past decade have made it possible to recover fragments of ancient DNA from bones and teeth. Researchers can use these genomes to study a metaphorical molecular fossil record of microbial evolution.

The Black Death, one of the deadliest pandemics in history, shows both the power and the limits of sequencing.

The infectious disease behind the Black Death, plague, is caused by the bacterium Yersinia pestis. DNA recovered from the teeth of people buried more than 5,000 years ago in what is now Sweden revealed the existence of an ancestral form of Y. pestis that had not yet adapted to fleas.

About 2,000 years later, the bacterium made an important evolutionary shift: It gained the ability to survive in fleas and pass back and forth between humans, rats and other mammals via flea bites. That change made the pathogen far more dangerous and helped pave the way for three great plague pandemics that followed: the Justinianic Plague from the sixth to eighth century; the Black Death and later waves from the 1300s into the 1700s; and the third pandemic from the 19th to mid-20th centuries.

But how and why did plague emerge and move through human societies with such devastating results? Genetic results alone are not enough to answer these questions.

When gravestones become genetic evidence

Geneticists needed archaeologists, paleoclimatologists and historians to complete the picture of the plague pandemics. The genome revealed the lineage. Other disciplines supplied the historical and environmental context.

Two 14th-century graveyards in what is now Kyrgyzstan provide a striking example of how historical evidence can guide genetic investigations into the origins of a pandemic.

Historian Philip Slavin noticed archival records pointing to an unusual number of gravestones from 1338 and 1339. Some of those tombstones explicitly referred to a pestilence as the cause of death.

That clue led to the next stage of the investigation, where archaeologist Maria Spyrou and her team extracted and sequenced ancient DNA from the skeletal remains of seven people buried in the graves and found genetic traces of Yersinia pestis in three of the skeletons. These strains were close precursors of the strain linked to the Black Death and ancestors of several modern Y. pestis lineages.

This major finding was still not the whole story. It could explain where the Black Death pandemic began but not how the disease spread across Asia to Europe. Researchers found a potential answer to this question in artifacts buried at the site, which included pearls from the Indian Ocean, Mediterranean coral and foreign coins. Those objects suggested that the region was connected to long-distance trade networks.

Once the gravestones, skeletal remains, written records and trade goods were considered together, a richer picture emerged. Researchers could place the pathogen in a specific time and place and connect it to the networks of human movement that may have carried plague westward.

Sequencing provided the biological clue, revealing the pathogen’s identity and ancestry. History and archaeology turned that clue into a plausible narrative.

From ancient DNA to modern outbreaks

Genomic sequencing isn't limited to examining outbreak cold cases. It is also researchers' tool of choice for understanding new diseases.

When the first reported COVID-19 cases emerged in 2019, researchers quickly sequenced the virus and found that it was closely related to the virus that caused the 2002 SARS outbreak. This placed the new virus within a known family of pathogens.

Later genomic sequencing helped reveal the scale of a major superspreading event: the 2020 Biogen conference in Boston.

The biotech company Biogen brought together about 175 European and American executives at a moment when COVID-19 was only beginning to spread in the United States. In Europe, COVID-19 was also escalating, with northern Italy reporting locally transmitted clusters just days before the meeting. After the meeting, many Massachusetts cases were linked to the conference.

Researchers then analyzed thousands of viral genomes from patients in Massachusetts and elsewhere. One viral genome carried a unique genetic signature traceable to a European attendee at the conference. It matched viruses circulating in Europe but also had an additional mutation that appeared to have arisen during the attendee’s travel to Boston or early in the conference.

Because that altered sequence appeared only in people with direct or indirect ties to the meeting, it served as a genetic marker for the COVID-19 strain originating at the Biogen conference. By comparing it with other viral sequences in national databases, researchers tracked the strain associated with the conference to 29 states and several other countries.

Interviews and contact tracing alone couldn’t have made that chain of infection so clear because people may not know exactly when they were exposed, especially when infections spread through brief encounters, via travel or large meetings.

When genomes join the investigation

Genome sequencing has rewritten the history of disease by giving scientists a way to read a pathogen's own record of change.

It can link ancient graves to later pandemics and trace a modern outbreak from one conference room to cases across a continent.

But the greatest strength of genome sequencing lies in partnership. Sequencing does not replace history, archaeology or public health investigation. It gives them a new molecular partner.

Combining work from these fields produces a fuller and more accurate account of how disease moves through the world.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Generative artificial intelligence (AI) is erasing the line between reality and illusion to the point where seeing is no longer believing. We need a social and legal framework that will separate real-world images from those generated by AI, as well as technical innovations, such as universal "AI watermarks," that will help viewers immediately distinguish real images from fake ones. Without such a framework in place, we risk losing the trust that real-world photography brings. And that would be a disaster for democracy.

On June 6, 1944, Allied forces stormed the beaches of Normandy. The photographs that emerged — grainy, blurred, chaotic — did more than document history; they shaped it. For millions who would never see the battlefield, those images became the war — visceral proof of sacrifice, courage and collective purpose. They transcended language, collapsing distance between the observer and the event.

The same can be said of other defining moments. The lone figure standing before tanks in Tiananmen Square. The falling man from the World Trade Center. The lifeless body of 3-year-old Alan Kurdi on a Turkish shore. These images are not merely records; they are cultural touchstones. They form a shared visual substrate upon which public understanding — and, often, political will — is built. They allow societies to coordinate emotion, judgment and action at scale.

But what happens when that substrate erodes?

Advances in generative AI make it possible to create images that are not only realistic but emotionally compelling and contextually plausible. Unlike earlier forms of manipulation, which required skill and often left detectable traces, today's synthetic images can be produced rapidly, cheaply and at scale. They can depict events that never occurred and people who never existed, in scenes that nevertheless feel uncannily authentic. And AI image generators are getting better.

This shift introduces a profound epistemological problem. Historically, photographs have occupied a privileged position in our hierarchy of evidence. "Seeing is believing" is not just a cliché; it reflects a deep-seated cognitive shortcut that also transcends written and spoken language. While we have always known that images can be staged or edited, the default assumption is that photographs bear some causal connection to reality. Generative AI severs that link.

The risks are not abstract. In the context of war, synthetic images are being deployed as propaganda — fabricated atrocities attributed to an enemy, or staged victories designed to boost morale. For example, an image of an American radar system allegedly damaged by an Iranian drone strike that was widely circulated turned out to be fake., In domestic politics, they are being used to inflame racial tensions, fabricate protests, or depict public figures in situations that never occurred. For example, a fake image of a mug shot of Donald Trump has been widely disseminated.

The speed and scale of digital dissemination via social media means these images shape perceptions before the images can be verified or discounted. For example, a picture of 250 poodle mixes in captivity posted by an animal charity was dismissed as being fake. Yet, it was real.

This example also highlights a more insidious consequence that may emerge in a second-order effect: Once the public becomes aware that images can be convincingly faked, genuine images lose their evidentiary force. This is the "liar's dividend" — the ability of bad actors to dismiss authentic visual evidence as fabricated. In such a world, even the most compelling photograph can be met with skepticism, its truth value perpetually contested.

Democratic societies depend on a shared baseline of facts and experiences. While disagreement over interpretation is inevitable — and often healthy — there must be some common ground regarding what has actually occurred. Images have long played a crucial role in establishing that. When their credibility collapses, so does the capacity for collective judgment.

This is not a problem that can be solved through technology alone. While detection tools and forensic methods will continue to improve, they operate in an adversarial dynamic with generative systems. Each advance in detection is met with a corresponding advance in evasion. Moreover, technical solutions often struggle to scale across platforms and jurisdictions, and they require a level of public understanding that cannot be assumed.

What is needed is a societal and legal response that reestablishes trust in visual media. There is a historical precedent. In the 20th century, the rise of photography prompted legal innovations around authorship and ownership. Copyright law did not prevent manipulation or misuse, but it created a framework for attributing images to identifiable creators, thus enabling accountability and recourse where necessary. Broadly speaking, this framework makes it possible to sue for defamation, libel, etc.

A similar approach could be adapted for the age of generative AI. One element would involve mandatory disclosure: AI-generated images would be required to be clearly labeled as such, both at the point of creation and in downstream distribution. This could be enforced through platform policies and, where necessary, regulatory mandates. This would mean even an inattentive viewer would immediately know whether an image were AI generated.

More importantly, there is a need for traceability. Advances in cryptographic watermarking and content provenance systems offer a pathway. By embedding metadata that records the origin and transformation history of an image, it becomes possible to verify whether a visual artifact is authentic, synthetic or altered. Crucially, such systems would need to be standardized, interoperable and resistant to tampering.

Legal frameworks would need to support these technical measures. They could include liability regimes for the malicious use of synthetic media, as well as obligations for platforms to preserve and transmit provenance information. Just as importantly, there must be institutional actors, including journalists, courts and civil society organizations that are equipped to interpret and communicate this information to the public.

None of these measures will fully restore the epistemic status or "truth value" that photographs once held. The age of naive visual trust is over. But the goal is not to return to a bygone era; it is to construct new mechanisms of trust that are robust to the realities of digital manipulation.

The images of Normandy, Tiananmen Square and countless other moments continue to resonate because they are widely accepted as reflections of reality. Preserving that capacity — for images to anchor shared understanding — is not merely a technical challenge. It is a democratic imperative.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

Over five decades ago, astronomer Frank Drake used one of Earth's largest radio antennas to beam a coded message into space, hoping that it might one day reach the eyes, ears or other inscrutable sensory organs of intelligent aliens. Slicing silently through the Milky Way at light speed, the now-famous Arecibo message has traveled roughly 50 light-years from Earth — about 10 times the distance to the nearest star, Proxima Centauri, but only one-five-hundredth the way to its intended destination in the Hercules constellation.

The search for extraterrestrial intelligence (SETI) is a waiting game — but for radio astronomer Emma Chapman, an astrophysicist at the University of Nottingham, whether humans will ever make contact with extraterrestrial life isn't a question of if but when. The universe is too vast and too plentiful with planets for humanity to be the only game in town, Chapman writes in her new book, "The Echoing Universe: How Radio Astronomy Helps Us See the Invisible Cosmos" (Basic Books, 2026). And when we do hear from our hypothetical alien neighbors, radio astronomers will be the first to know.

In this excerpt from Chapman's book, she tells us the intriguing story of Drake's message to the stars, the initial fears that it would awaken the attention of "malevolent or hungry" aliens, and why the search for extraterrestrial intelligence is still so valuable today.

During public lectures, I'm often asked, "Do you think aliens exist?"

I am always a little taken aback, as is the audience, when they hear my emphatic answer: "Absolutely. I have no doubts at all."

My surprise comes about because, as a radio astronomer, I have no doubt that life is out there, and I sometimes forget that there can even be a question about the matter.

There is little controversy amongst astronomers, not since the avalanche of exoplanet observations showed us that it was only a matter of time before we found Earth 2.0. Even if habitable worlds are scarce or the emergence of life is rare, the sheer number of planets in the Milky Way, let alone the universe, makes it implausible to think we are alone.

I am not engaging here in a willful misunderstanding of what we mean by "alien." When I say I believe there are aliens, I mean intelligent, complex lifeforms, not just basic, microbial life.

The audience is often silent for a beat after I have answered, not expecting such certainty. People expect heated debate over the question of alien life, I think, because there is a conflation, even in the scientific world, between a belief in alien life and a belief in UFOs, or alien abductions. "Have aliens visited our planet?" is a fundamentally different question, and one which I can answer just as emphatically: "Absolutely not. I have no doubts at all."

There is no evidence for interference by extraterrestrial life on Earth. No aliens building the pyramids, no UFOs creating intricate crop circles, and no secret government cover-ups. Many UFO sightings turn out to be Venus gleaming on the horizon, optical illusions or simply shaky camera work. One only needs note how UFO sightings have not increased in line with smartphone ownership and the ability to capture supposed otherworldly events. These claims belong firmly in the realm of conspiracy theories.

SETI, however, stands apart as a rigorous, science-based pursuit, almost exclusively led by radio astronomers. For SETI researchers, the question isn't whether life exists elsewhere ‪—‬ we take that as a given. We want to make contact. We want to find out where these aliens live and communicate with them across the light-years, using radio telescopes as our telephone.

Frank Drake makes the call

In 1974, Frank Drake was the director of the Arecibo Observatory. Drake lived and breathed SETI, and he had become impatient at the pace of the search. SETI is passive. It is about listening and intercepting signals that extraterrestrial life has sent, purposefully or not. Drake wanted to take the initiative, to beam a message out ourselves. And so, METI (messaging extraterrestrial intelligence) was born.

Drake decided to send his signal using the 305-meter dish's antenna as the transmitter, at a

celebration honouring the recent renovation of the dish.

The message consisted of 1,679 binary digits, each representing one of two possible values. Frank Drake envisaged encoding a picture in this way, much like a "paint by numbers" canvas. A radio tone at one wavelength would indicate a solid square, while a tone at a second wavelength would represent an empty square.

Since the message would be transmitted as a long sequence of radio bursts, the challenge for any receiving extraterrestrial intelligence would be to determine how to arrange this list into a meaningful 2D image. The image contains a wealth of information: heavily pixellated diagrams of a human and the Arecibo dish, for example, along with a representation of our Solar System, and the major chemical elements making up our DNA.

Drake selected the number 1,679 deliberately because it is a prime number and also the product of two other primes: 23 and 73. Prime numbers are significant within mathematics, and Drake hoped that any intelligent beings receiving the flow of data would experiment with reshaping the sequence in configurations involving these primes. If they did so, they would discover the intended image, unlocking the deeper meaning of the message.

Drake also converted the message into audio, allowing the audience gathered next to the dish in the Puerto Rican jungle to listen in real time as the two-toned signal was broadcast into space. For three minutes, Earth transmitted a signal 10 million times brighter than our radio sun, making us unmistakably visible to any extraterrestrial intelligence with their own Arecibo within the target area.

I've listened to the signal myself. The "Moonlight Sonata" it certainly is not, but if you close your eyes and reflect on the poignancy of us announcing our presence to the cosmos, it's deeply moving, and I can only imagine it brought a tear to the eye of more than one person in the crowd.

The message was aimed at M13, a dense cluster of stars (and presumably planets) about 21,000 light-years away, in the Hercules constellation. This system was chosen partly for the press release optics of its dense population of potential life-bearing star systems, but mostly because it was above the dish at the time of the ceremony. Awkwardly, by the time the Drake signal reaches the intended coordinates, M13 may have drifted out of the way of the tight beam of the signal. The act was symbolic but still, the first intended message is out there, and we cannot undo it now.

By the time the 1974 ceremony lunch was over, that signal had reached the orbit of Pluto, and by now it is over fifty light-years away, about as far from us as 51 Pegasi b, the first exoplanet to be discovered around a sun-like star.

"Malevolent or hungry" aliens

Drake did this all without needing anyone's permission, and many saw his act as setting a dangerous precedent. Why should the decision to contact alien life be autocratic when any risk is shared by everyone on the planet? England's Astronomer Royal, Sir Martin Ryle, reacted with scathing letters to the International Astronomical Union demanding a ban on any future messages, since "for all we know, any creatures out there might be malevolent ‪—‬ or hungry,"

Drake and, by this time, the majority of SETI scientists considered the argument moot. Electromagnetic radiation has been escaping Earth's atmosphere since radio and television were invented.

Whether we're at risk of invasion depends on two things: first, whether they manage to develop interstellar travel, and second, whether they decide such an endeavour is worth the colossal energy cost. Imagine our own situation ‪—‬ would humanity, in the midst of an energy crisis, unite to devote gargantuan resources into building and launching an interstellar colonisation fleet?

In his excellent book "Is Anyone Out There?" Frank Drake makes his position clear: "If I believed the ETs would come out of the sky, I wouldn't bother. I would just sit outside in a lawn chair and wait for them to show up." I am inclined to agree.

Far more likely than any invasion is contact by radio signal. In that case, my hunch is that, once the existence of extraterrestrial intelligence is confirmed, it would then quickly settle into the background of everyday life. After all, aliens have long been a fixture of our entertainment culture ‪—‬ we are primed to accept their existence.

In addition, the news cycle relating to any "conversation" would simply be too long for it to capture the popular imagination even sporadically. TRAPPIST-1, for example, is just over forty light-years away and a message sent there today will not receive a reply for eighty years ‪—‬ more like opening a letter from your grandmother's pen pal than having a lively chat.

For decades, the value of SETI has sparked lively debate among scientists, politicians, policymakers, journalists. Yet, despite harsh budget cuts and scepticism, SETI persists. Our longing to answer the question of whether we are alone in the universe burns so brightly in some that they dedicate their lives to the search, fully aware that only future generations may uncover the truth.

Whatever form that life takes, we know how we can expect to be contacted, because the laws of physics do not vary across the galaxy. Whether that planet has a yellow-green sky, whether it has five moons, or its people five legs, radio waves will be the form of light that is used for long- distance communication.

Perhaps, forty light-years away and forty years ago, a little green person on TRAPPIST-1 e switched on a shiny radio telescope and began to send messages towards the star systems all around, crossing all twenty fingers that someone out there would hear them. Perhaps one day we'll turn our dishes towards TRAPPIST-1, and tune in just as that alien message reaches us. It could be in a hundred years. It could be tomorrow. Until that fateful day, we look at the stars, we wait and we listen.

Excerpted from "The Echoing Universe: How Radio Astronomy Helps Us See the Invisible Cosmos," by Emma Chapman. Copyright © 2026 by Emma Chapman. Available from Basic Books, an imprint of Hachette Book Group Inc.

Last week, PCOS got a major rebrand.

Polycystic ovary syndrome (PCOS) will now be known as polyendocrine metabolic ovarian syndrome (PMOS). The main critique of the old name was that it inaccurately described the condition, which affects about 1 in 8 women worldwide. It implied that ovaries covered in many pathological cysts are a central feature of the syndrome, and that is not the case.

Studies have found that people with PMOS aren't more likely to have pathological ovarian cysts than people without the disorder. Instead, they often have underdeveloped eggs, called "arrested follicles," that accumulate in the ovaries due to the hormonal disruptions associated with the condition. The new name, experts say, better reflects the nature of the syndrome by focusing on these hormonal disruptions that then impact metabolic processes across the body — driving insulin resistance and weight gain, for instance — in addition to affecting the reproductive system, skin, and mental health.

What do you think of the new name? Tell us in the poll below, and let us know your thoughts in the comments. If you personally have PMOS, we'd love to hear your take, in particular!

(Fun fact: PMOS has actually undergone several previous name changes. Its original name was Stein-Leventhal syndrome, after the doctors who first described its features.)

This article is for informational purposes only and is not meant to offer medical advice.

We have been on a years-long campaign of satellite remote sensing of the vast desert landscapes in Eastern Sudan.

This involved using satellite aerial imagery to systematically and painstakingly search for archaeological features in Atbai Desert of Eastern Sudan, a small part of the much larger Sahara.

Our team — which includes archaeologists from Macquarie University, France's HiSoMA research unit, and the Polish Academy of Sciences — wanted to tell the story of this desert region between the Nile and the Red Sea, without having to excavate.

One mysterious archaeological feature stood out. We kept finding large, circular mass graves filled with the bones of people and animals, often carefully arranged around a key person at the center.

Likely built around the fourth and third millennia BCE, all these "enclosure burial" monuments have a large round enclosure wall, some up to 80 meters [262 feet] in diameter, with humans and their cattle, sheep and goats buried inside.

Our new research, published in the journal African Archaeological Review, reveals how we found 260 previously unknown enclosure burials east of the Nile River, across almost 1,000km of desert.

Who built them?

Already known from a few excavated examples in the Egyptian and Sudanese deserts, these large circular burial monuments have long puzzled scholars.

What seemed once isolated examples emerge now as a consistent pattern. It is suggestive of a common nomadic culture stretching across a vast stretch of desert.

Most are within the borders of modern Sudan on the slopes of the Red Sea Hills. Unfortunately, satellite imagery alone cannot communicate the whole story of these enclosure burial builders.

The carbon dates and pottery from the few excavated monuments tell us these people lived roughly 4000–3000 BCE, just before Egyptians formed a territorial kingdom we know of as Pharaonic Egypt.

But these "enclosure burial" nomads had little to do with urbane and farming Egyptians.

Living in the desert and raising herds, these were Saharan desert nomads through and through.

A new elite?

Some enclosures show "secondary" burials arranged around a "primary" burial of a person at the center —perhaps a chief or other important member of the community.

For archaeologists, this is important data for discerning class and hierarchy in prehistoric societies.

The question of when Saharan nomads became less egalitarian has plagued archaeologists for decades, but most agree it was around this time of the fourth millennium BCE that a distinctive "elite" class emerged.

This is still a far cry from the sort of huge divisions between ruler and ruled as seen in societies such as Egypt, with its pharaohs and farmers. However, it ushers in the first traces of inequality.

Animals held in high esteem

Cattle seem very important to these prehistoric nomads (a theory also supported by ancient local rock art in the area).

Burying themselves alongside their herd, these nomads show they held their animals in esteem.

Thousands of years later, local nomads chose to reuse these now "ancient" enclosures for their burial plots — sometimes almost 4,000 years after they were first built.

In other words, the prehistoric nomads created cemetery spaces that lasted for millennia.

What happened to these people?

No one can say for sure.

The few dates we have for these monuments cluster between 4000–3000 BCE, nearing the end of a period when the once-greener Sahara was drying, a phase scientists call the "African Humid Period".

From north to south, the summer monsoon gradually retreated, reducing rainfall and shrinking pastures. This led nomads to abandon thirsty cattle, increase the mobility of their herds, migrate to the south or flee to the Nile.

The monuments are overwhelmingly located near what were then favorable watering spots; near rocky pools in valley floors, lakebeds and ephemeral rivers.

This tells us that when the monuments were being built, the desert was already quite challenging and dry.

At some point, as grass and bush made way for sand and rocks, keeping their prized cattle became unsustainable.

Having large herds of cattle in this desert, at this period, may have been a way of showing off an expensive and rare possession — a prehistoric nomad's equivalent to having a Ferrari. This may help explain why cattle were frequently buried alongside their owners in enclosure burial monuments.

A bigger story

These enclosure burials are only one part of the greater story of human adaptation to climate change across North Africa.

From the Central Sahara, to Kenya and Arabia, keeping cattle, goats and sheep transformed societies. It changed the food they ate, the way they moved around, and community hierarchies.

It's no coincidence communities changed how they buried their dead at the same time as they adopted herding lifestyles.

These burial enclosures tell us even scattered nomads were extremely well-organized people, and expert adapters.

Our discovery reshapes the story of the Sahara deserts and the prehistory of the Nile.

They provide a prologue for the monumentalism of the kingdoms of Egypt and Nubia, and an image of this region as more than pharaohs, pyramids and temples.

Sadly, many of these enclosure monuments are currently being destroyed or vandalized as a result of unregulated mining in the region. These unique burials have survived for millennia, but can disappear in less than a week.

Maria Gatto (Polish Academy of Sciences) was an author on our paper. We also want to acknowledge Alexander Carter, Tung Cheung, Kahn Emerson, Jessica Larkin, Stuart Hamilton and Ethan Simpson from Macquarie University for their contribution. We are also grateful to the National Corporation of Antiquities and Museums (Sudan).

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Artificial intelligence (AI) chatbots are generating new forms of violence against women and girls and amplifying existing forms of abuse such as stalking and harassment. This is no accident: the platforms enable these forms of gender-based violence through deliberate design choices or by failing to implement sufficient safety features. We need to regulate AI chatbot providers now, to prevent abusive applications of such technology from becoming normalized.

The extent to which chatbots are changing violence against women and girls was laid bare in a research report I recently co-authored with colleagues. The findings are bleak. We found chatbots will initiate abuse, simulate abuse and help to enable abuse by offering personalized stalking advice. Some even normalize incest, rape and child sexual abuse by offering abusive roleplay scenarios.

Chatbots — AI systems capable of and designed to simulate human-like interaction and generate text, images, audio and video in response to user prompts — are everywhere. In the U.S., 64% of children ages 13 to 17 say that they use chatbots, with three in 10 doing so daily. Over half of adults use a chatbot at least once per week.

With these new technologies come new harms. Our report shows that chatbot design is instrumental in instigating violence against women and girls. While platform policies often prohibit harms such as harassment, grooming or sexual abuse, these scenarios can still be generated with many chatbots, and some companies do not proactively search for violations of these policies.

In one recent case in Massachusetts, a man was found guilty of cyberstalking after using AI chatbots to impersonate his victim and engage in sexual dialogue with users. One of the chatbots he used was programmed to invite users to her home address if they asked where she lived.

Training systems on user interactions risks reinforcing misogynistic and sexually violent content, while engagement-optimized and "sycophantic" design encourages chatbots to affirm harmful narratives rather than refuse them. Platform policies frequently place responsibility on users, framing abusive outputs as a user misuse issue rather than failures of chatbot safety and design.

This is why regulation of the chatbot providers is so important, to stop these practices becoming embedded. We've already seen what happens without regulation through "nudify" apps that create deepfake non-consensual intimate images. Regulation was left too late and the practice of creating deepfake images, and the harms caused to victims, had become normalized and widespread by the time governments moved to ban these tools. We argue that to avoid making the same mistakes with chatbots, the following actions need to be taken:

— Make it a criminal offense to create an AI chatbot that is designed, or can easily be used, to abuse or harass women, targeting companies or individuals who release tools that pose risks without taking reasonable steps to prevent harm. Just like reckless driving or owning a dangerous dog are punishable by law, creating a risk to the public by releasing a chatbot with insufficient protections should be brought within the scope of criminal law. Fines for companies and prison sentences for individuals responsible for creating this risk could make companies more careful to pre-empt and prevent potential harms before releasing products.

— Adopt specific AI Safety legislation. This would establish mandatory risk assessments and incorporate clear safeguards to prevent individual and societal harms, including a duty to act quickly when harms are identified, publish transparent safety information, and enable users to report incidents easily. Important state-level legislation, including in Utah, Colorado, and California, has expanded the ability for individuals, and state attorneys general, to sue AI providers that have failed to meet their obligations under the legislation. However, there has been a pushback against these state-level measures in recent years, with the U.S. government arguing they are barriers to innovation and national competitiveness.

Two main objections may be raised to our recommendations: the first, led by AI providers, is that these forms of abuse are a "user misuse" problem, and that responsibility should lie with users rather than the providers of these services. But our research shows that abuse is structurally produced by features of how chatbots are built or governed, and what they are optimized to do.

For example, to bolster engagement, some chatbots have continually driven users (including underage users) to engage in unwanted sexual messages. If a human were doing this, it would constitute grooming and/or sexual harassment. Some of the companion chatbots even offer "violent rape" or "loli" (a term for an underage girl) as options that users can choose from, legitimizing these criminal forms of abuse as mere sexual preferences. Abuse is built into the DNA of these chatbots.

The second objection — one reflected by the U.K. government’s recent announcement that it is exploring a ban on AI chatbots for under 16s — is that AI chatbots mainly pose a danger to children, and they should be the focus of regulation. But our research shows that AI chatbots can intensify abuse against adults, such as stalking or harassment, with detailed and personalized guidance and encouragement.

In the Massachusetts case, James Florence had provided AI chatbots his victim's personal information, including her employment history, her hobbies, her husband's name and place of work. The harms here are not to the user but to society at large — a ban on children’s use of chatbots would not have prevented them.

This broader societal harm does not stop when the user turns 18. We urgently need specific AI safety legislation that would protect against these harms by requiring rigorous testing and risk assessment prior to the public release of such products, and continually thereafter.

Changing the law around AI chatbot development would not only protect children but would also ensure that when those children become adults, they enjoy an AI environment that is free from bias, misogyny and violence against women and girls. That is a world we all deserve to live in.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

Polar bears are intensely curious animals. That curiosity often brings them into contact with people and can put both species at risk from one another.

As the Arctic climate warms, some polar bears are spending more time on shore, away from the sea ice habitats they rely on to hunt seals. As the bears are under nutritional stress due to ice loss, some wonder if they're being forced to take more risks around people as they seek food, increasing interactions and conflicts between polar bears and people. But until now, there're been little research into this relationship.

Between 2011 and 2021, research colleagues and I placed trail cameras at three camps in Wapusk National Park in Manitoba and, later, at the nearby Churchill Northern Studies Centre (CNSC) to see how often polar bears visited these sites on the west coast of Hudson Bay.

The project began at the invitation of Parks Canada when their newly constructed field camps at Broad River and Owl River turned out to receive more bear visits than they expected. Those camps had been located away from the coast to reduce the likelihood of polar bear encounters, so answering this immediate question was a priority.

We investigated whether human activity, the length of the ice-free season — or both — were influencing polar bear visits. In approximately 80% of the bear visits, our photos showed enough of the animal that we could rate their body condition using an established fatness index.

We observed 580 bear visits with our cameras, mostly between July and November, when bears are well-known to be abundant in the area. What we found was that human presence at the camps and the CNSC didn't have any effect on the number of bear visits. The length of the ice-free season each year, however, had a notable effect.

It’s all about ice

The ice-free season can be longer if sea ice breaks up earlier in spring than normal, forms later in fall than normal, or both. During our study period, there was no long-term trend in the ice-free season's length, but it did vary a lot year to year. We found that the longer western Hudson Bay remained ice-free in a year, the more frequently bears visited our study sites.

Poor body condition is considered an indicator of nutritional stress, and a healthy body condition to survive on-shore fasting is critical for polar bear survival.

But rather than getting visits from hungrier bears that were detectably thinner — which is what we had expected — we found that the more time bears were off the ice, the more likely all bears were to approach our study sites, regardless of their nutritional health.

This result was unexpected since other research shows underweight polar bears are more likely to attack people, which has been taken to mean that those particular bears would take more chances to find food and so be more likely to approach or prey on people.

Instead, what we're seeing is that body condition may play a different role. Rather than influencing the bears to seek human interactions, body condition might instead influence whether interactions between people and polar bears escalate.

In other words, if polar bears are around people to begin with, a skinny bear might be more likely to aggressively try to obtain human food sources, or even prey on people, than a bear under less nutritional stress.

We were also surprised not to see many lone sub-adult bears in our photos. Those other studies have also shown that they're usually the ones most likely to come into conflict with people.

These observations, though, are consistent with other research on this sub-population. As the ice-free season has on average lengthened in western Hudson Bay, the production and survival of juvenile bears has dropped. Our unexpected results, then, are probably due to there simply not being many young bears in the population during our study.

Scientific and Indigenous observations

Our findings suggest that sea ice loss probably doesn't lead to more interactions with people just because polar bears are thinner or hungrier, so we need to better understand what can cause interactions to worsen into attacks.

What does this mean for current approaches to reducing the risk of polar bear-human conflicts? Bringing it back to the Parks Canada's original question, it appears that the likelihood of bear visits to their camps isn't affected by anything under human control, but the outcomes of any bear visits that do take place certainly are.

What we found may also help explain why scientific explanations and Indigenous and local observations of polar bear-human interactions have differed. Scientific literature has long maintained that poor body condition drives polar bears into northern communities.

However, documented observations from those communities themselves indicate bears who come into communities are not necessarily in poorer condition than would be expected.

Our findings align more closely with Indigenous observations, highlighting how untested assumptions can, through repetition in scientific literature, solidify into accepted wisdom.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

There is a troubling contradiction at the heart of the global transition to a cleaner, greener, tech-driven future: Modern technologies — everything from AI to wind turbines, as well as cellphones, electric vehicles and defense systems — depend on critical minerals. But many of the communities where those minerals are mined end up with polluted water and poorer health because of the mining.

Lithium powers batteries. Cobalt stabilizes them. Copper carries electricity. Rare earth elements make wind turbines and digital devices efficient and durable. Each of these are essential to the technologies of the fourth industrial revolution, but they are also toxic and require enormous amounts of water to extract.

As researchers at the United Nations University Institute for Water, Environment and Health, we have been studying the impacts of critical mineral mining on communities around the world. Our new report shows why mining will end up worsening the lives of some of the world's poorest people if critical mineral supply chains are not monitored and regulated.

One of us is from the Middle East, a region still suffering from the long-term consequences of supplying the fuel consumed for the remarkable economic developments of the 20th century. And one of us comes from Africa, the continent that is now serving as a major supplier of the critical minerals that fuel technological advancements in the 21st century.

Based on our experiences and our research, we believe that if there aren't major changes in how countries, corporations and communities manage critical minerals, humanity risks reproducing the injustices of the oil extraction era, this time with the technological advancements meant to address the problems fossil fuels created.

Mining contributes to growing water bankruptcy

One of the most significant impacts of critical minerals extraction is its effect on water.

In 2024 alone, global lithium production required an estimated 456 billion liters of water. That is equivalent to the annual domestic water needs of roughly 62 million people in sub‑Saharan Africa. At the same time, much of the world is facing water bankruptcy, meaning people and industries are using more fresh water than nature can replenish, leading to irrecoverable ecosystem damages.

In arid regions such as Chile's Salar de Atacama, mining activities account for up to 65% of total regional water use, competing with agriculture and ecosystems. Groundwater levels have dropped, salt lagoons have shrunk, and freshwater aquifers are increasingly at risk of being depleted and contaminated.

Water pollution compounds problems like this. Mining generates large quantities of toxic waste and wastewater containing heavy metals, acids and radioactive residues.

Rare earth mineral production, for example, generates up to 2,000 metric tons of waste for every metric ton of usable material. Rare earth minerals are often extracted by creating leaching ponds and adding chemicals to separate the metals. When the effluent isn't treated or is improperly stored, the chemicals can seep into groundwater and waterways, contaminating aquifers and rivers.

In some parts of the world, rivers near cobalt and copper mines have become so acidic that communities can no longer drink water from them. Fish stocks have collapsed, and farmlands have been poisoned. Water insecurity is no longer a side effect of mining; it is a systemic cost.

Health crises hidden in supply chains

Communities living near these extraction sites report people suffering from skin diseases, gastrointestinal illnesses, reproductive health problems and chronic health conditions associated with long‑term exposure to heavy metals in polluted water and soil.

Evidence from mining regions in the Democratic Republic of the Congo is particularly stark.

Studies document high rates of miscarriages, congenital malformations and infant mortality among populations exposed to environments contaminated with cobalt and other metals. Maternity wards in southern Democratic Republic of the Congo that are close to mining operations report significantly more birth defects than those farther away.

In communities near mining operations, residents talk about how women and girls living near cobalt and copper mining sites have been experiencing gynecological health problems, including infections, menstrual irregularities, miscarriages and infertility. These risks are linked to prolonged contact with contaminated water, compounded by limited access to sanitation and healthcare.

In Chile's Antofagasta region, cancer mortality is the highest in the country. Lung cancer rates there are nearly three times the national average. Physicians in the region also report rising cases of neurological and developmental disorders, which they link to early exposure to contaminated water and air.

Thousands of children are estimated to be employed in artisanal cobalt mines in the Democratic Republic of the Congo. In the informal mines, they may be exposed to cobalt dust and other hazardous materials without protective gear.

These health risks are heightened by weak systems for water, sanitation and healthcare. As of 2024, only about one-third of people in the Democratic Republic of the Congo had at least basic drinking water services.

Food costs of the energy transition

The water problems caused by critical minerals extraction also pose a major threat to local food systems. In Peru, zinc mining has contaminated the Cunas watershed. Runoff pollutes water used to irrigate crops and provide water for livestock.

In Bolivia's Uyuni region, lithium mining has led to persistent water shortages that are making it increasingly difficult to grow quinoa, a staple crop central to local diets and economies. Across the wider "lithium triangle" of Argentina, Chile and Bolivia, mining has reduced water availability for crops and farm animals.

Similar patterns are evident in parts of the Democratic Republic of the Congo and Zambia. In both countries, polluted rivers have contributed to declining fish stocks and livestock illnesses, harming households that are already struggling to feed themselves.

Ways to protect mining communities

Innovation and technological advances have the potential to do good. But we believe a fair and sustainable energy and digital transition requires deliberate actions to avoid creating "sacrifice zones," places where human and ecological well-being are traded away for technological breakthroughs.

One option is to create stronger international governance. Moving beyond voluntary guidelines toward binding international rules, such as treaties, enforceable supply chain due-diligence laws, mandatory environmental and human rights standards for mining operations, and potentially establishing a global mineral trust that would manage critical minerals as shared planetary assets, could improve water protection, pollution control and human rights across mineral supply chains.

Companies can also invest in less water-intensive mining technologies. Countries can tighten their wastewater controls and expand independent environmental monitoring and reporting.

Governance arrangements that give local and Indigenous communities a stronger voice, a fair share in the benefits and genuine co-governance of resources could further rebalance who has power and who bears risk.

On the consumption side, extending product lifespans, expanding recycling and encouraging less reliance on newly mined minerals would ease pressure on water‑stressed regions.

For the people who use these technologies, the social and environmental costs embedded in critical minerals supply chains are often out of sight and out of mind. Making these impacts visible can enable consumers to make informed choices and engage in greater scrutiny of corporate practices.

Critical minerals are essential to advancing sustainability. But if cleaner technologies are built in ways that result in polluted rivers, sick children and dispossessed communities, the transition will fall short of its promise.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Drilling has begun at Pe' Sla, a sacred site in South Dakota, following the U.S. Forest Service's decision to permit exploratory sites — despite the land falling under federal protection. Authorizing mining activity in this sacred place is a direct attack on protected Indigenous lands and the fundamental right to religious freedom. It also threatens ecosystems and waterways, and could cause permanent environmental degradation.

At least two drill pads are now operating on tribal lands within the 2-mile (3.2 kilometers) buffer zone promised to be protected by the Forest Service and tribes. This should ring alarm bells everywhere, because it means that even lands protected by the U.S. government are not safe from the threat of destruction.

This project began in February when the Forest Service quietly issued a permit allowing exploratory drilling for graphite at Pe' Sla — a place in the He Sapa (Black Hills) of South Dakota that holds profound spiritual, cultural and ecological significance for the Oceti Sakowin (often called Great Sioux Nation).

That's why on April 2, NDN Collective, Black Hills Clean Water Alliance, and Earthworks sued the Forest Service, citing violations of the National Environmental Policy Act (NEPA) and threats to lands long recognized for their religious and cultural importance.

The permit to drill for graphite at Pe' Sla must be rescinded and drilling stopped immediately. Not only does drilling pose serious environmental risks, it sets a dangerous precedent for Indigenous lands across the country.

The two drill pads currently in operation are just the start. The proposed project by Pete Lien & Sons includes 18 drill pads, each reaching depths of up to 1,000 feet (300 meters). Operations like this typically require vegetation and topsoil removal, the creation of toxic drilling mud pits, and the disruption of fragile ecosystems. The site sits within the Rapid Creek watershed, a vital source of surface and groundwater for communities including Rapid City, Ellsworth Air Force Base, and tribal and rural populations downstream.

The Forest Service claims the contaminants and runoff from the drill operation will be contained using lined, impermeable pits and potable water brought in from the municipal supply. However, many similar operations have led to contamination even with such measures in place. Contamination at Pe' Sla would likely ripple outward, affecting drinking water, agriculture and ecosystems across the region.

The health impacts of water contaminated by mining are severe, causing cancer, developmental and neurological damage, kidney failure, gastrointestinal illnesses, and skin lesions through the release of heavy metals, toxic runoff and acid mine drainage.

The threat is also cultural and constitutional. Pe' Sla has been used for ceremony for over 2,000 years. In 2016, Pe' Sla was granted federal trust status, giving local tribes permanent stewardship over the land for religious use. And in 2024, the Forest Service itself acknowledged Pe' Sla's religious and cultural importance in a memorandum of understanding — a formal agreement — with tribal nations, even establishing a 2 mile protective buffer zone around the tribal land.

Now, within the buffer zone, drilling is being authorized under a "categorical exclusion," a form of NEPA compliance for projects deemed not having a "significant effect on the human environment." In other words, this project gets to skip the environmental assessment and/or environmental impact statement that would normally be required for a drilling project.

As outlined in the lawsuit against the Forest Service, the project's scale and its impact on Indigenous religious practices should disqualify it from such an exemption. Moving forward without environmental review is a violation of both federal law and the government's own commitments.

If drilling can be permitted here, on land acknowledged by the government as sacred, within a sensitive watershed, and with limited economic benefit, then what protections truly remain elsewhere? What prevents similar decisions at other sacred sites, in other fragile ecosystems, in communities whose voices are too often dismissed?

Supporters of the project may argue that it brings jobs and economic opportunity. But even that claim quickly falls short. Graphite is used for lithium batteries, car parts and electronics. But the graphite deposits in question are reportedly small and low-grade, making it unlikely to be profitable to mine them. This project, which is estimated to last a year according to the Black Hills Clean Water Alliance, is a short-sighted venture that would cause permanent damage. Once the drilling ends, whatever few jobs are associated with the project would disappear. The environmental and cultural harm, however, would remain.

This is a familiar pattern of extractive industry: short-term gain for a few, lasting harm for many. Just look at the Gold King Mine in Colorado, where nearly 100 years after operations shut down, 3 million gallons (11 million liters) of contaminated water from the site leaked into a nearby creek. This spill impacted rivers in three states and the Navajo Nation, countless farms, and cost tens of millions of dollars to fix. In the case of Pe' Sla, the costs are especially high — measured not only in environmental degradation but in the continued erosion of Indigenous sovereignty and rights.

From the beginning of this fight over a year ago, community members and advocates responded by mobilizing thousands of public comments, gathering petition signatures, offering testimony at town halls and hearings, and raising awareness through social media and the LANDBACK For the People podcast. The fight for Pe' Sla is a growing movement of people who recognize that what happens in the Black Hills has ripple effects across Turtle Island (the U.S.. Mexico and Canada).

It's not too late for people across the country to take action to protect Pe' Sla by calling the Mystic Ranger District Office to express their opposition to the drilling project, and by signing the petition to rescind the permit.

We will defend Pe' Sla in the courts. But as the original people of this land, our sovereignty is inherent here. The U.S. has a legal obligation under Article VI of the Constitution, which states that "treaties are the supreme law of land," and thus the terms of the 1868 Ft. Laramie Treaty, which recognizes the Black Hills as Lakota lands. This project does not have the consent of the Great Sioux Nation.

Right now, there is still time to act — to raise objections, to demand accountability, to insist that Pe' Sla be protected. Because in the end, this is not just about one sacred site in South Dakota. It is about all of us and our collective responsibility to protect our shared planet.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

On a Saturday morning, you head to the hardware store. Your neighbors' Ring cameras film your walk to the car. Your car's sensors, cameras and microphones record your speed, how you drive, where you're going, who's with you, what you say, and biological metrics such as facial expression, weight and heart rate. Your car may also collect text messages and contacts from your connected smartphone.

Meanwhile, your phone continuously senses and records your communications, info about your health, what apps you're using, and tracks your location via cell towers, GPS satellites and Wi-Fi and Bluetooth.

As you enter the store, its surveillance cameras identify your face and track your movements through the aisles. If you then use Apple or Google Pay to make your purchase, your phone tracks what you bought and how much you paid.

All this data quickly becomes commercially available, bought and sold by data brokers. Aggregated and analyzed by artificial intelligence, the data reveals detailed, sensitive information about you that can be used to predict and manipulate your behavior, including what you buy, feel, think and do.

Companies unilaterally collect data from most of your activities. This "surveillance capitalism" is often unrelated to the services device manufacturers, apps and stores are providing you. For example, Tinder is planning to use AI to scan your entire camera roll. And despite their promises, "opting out: doesn't actually stop companies' data collection.

While companies can manipulate you, they cannot put you in jail. But the U.S. government can, and it now purchases massive quantities of your information from commercial data brokers. The government is able to purchase Americans' sensitive data because the information it buys is not subject to the same restrictions as information it collects directly.

The federal government is also ramping up its abilities to directly collect data through partnerships with private tech companies. These surveillance tech partnerships are becoming entrenched, domestically and abroad, as advances in AI take surveillance to unprecedented levels.

As a privacy, electronic surveillance and tech law attorney, author and legal educator, I have spent years researching, writing and advising about privacy and legal issues related to surveillance and data use. To understand the issues, it is critical to know how these technologies function, who collects what data about you, how that data can be used against you, and why the laws you might think are protecting your data do not apply or are ignored.

Big money for AI-driven tech and more data

Congressional funding is supercharging huge government investments in surveillance tech and data analytics driven by AI, which automates analysis of very large amounts of data. The massive 2025 tax-and-spending law netted the Department of Homeland Security an unprecedented US$165 billion in yearly funding. Immigration and Customs Enforcement, part of DHS, got about $86 billion.

Disclosure of documents allegedly hacked from Homeland Security reveal a massive surveillance web that has all Americans in its scope.

DHS is expanding its AI surveillance capabilities with a surge in contracts to private companies. It is reportedly funding companies that provide more AI-automated surveillance in airports; adapters to convert agents' phones into biometric scanners; and an AI platform that acquires all 911 call center data to build geospatial heat maps to predict incident trends. Predicting incident trends can be a form of predictive policing, which uses data to anticipate where, when and how crime may occur.

DHS has also spent millions on AI-driven software used to detect sentiment and emotion in users' online posts. Have you been complaining about Immigration and Customs Enforcement policies online? If so, social media companies including Google, Reddit, Discord, and Facebook and Instagram owner Meta may have sent identifying data, such as your name, email address, phone number and activity, to DHS in response to hundreds of DHS subpoenas served on the companies.

Meanwhile, the Trump administration's national policy framework for artificial intelligence, released on March 20, 2026, urges Congress to use grants and tax incentives to fund "wider deployment of AI tools across American industry" and to allow industry and academia to use federal datasets to train AI.

Using federal datasets this way raises privacy law concerns because they contain a lifetime of sensitive details about you, including biographical, employment and tax information.

Blurring lines and little oversight

In foreign intelligence work, the funding, development and controlled use of certain AI-driven gathering of data makes sense. The CIA's new acquisition framework to turbocharge collaboration with the private sector may be legal with proper oversight. But the line between collaborating for lawful national security purposes versus unlawful domestic spying is becoming dangerously blurred or ignored.

For example, the Pentagon has declared a contractor, Anthropic, a national security risk because Anthropic insisted that its powerful agentic AI model, Claude, not be used for mass domestic surveillance of Americans or fully autonomous weapons.

On March 18, 2026, FBI Director Kash Patel confirmed to Congress that the FBI is buying Americans' data from data brokers, including location histories, to track American citizens.

As the federal government accelerates the use of and investment in AI-driven spy tech, it is mandating less oversight around AI technology. In addition to the national AI policy framework, which discourages state regulation of AI, the president has issued executive orders to accelerate federal government adoption of AI systems, remove state law AI regulation barriers and require that the federal government not procure the use of AI models that attempt to adjust for bias. But using advanced AI systems is risky, given reports of AI agents going rogue, exposing sensitive data and becoming a threat, even during routine tasks.

Your data

The surveillance capitalism system requires people to unwittingly participate in a manipulative cycle of group- and self-surveillance. Neighborhood doorbell cameras, Flock license plate readers and hyperlocal social media sites like Nextdoor create a crowdsourced record of all people's movements in public spaces.

Sensors in phones and wearable devices, such as earbuds and rings, collect ever more sensitive details. These include health data, including your heart rate and heart rate variability, blood oxygen, sweat and stress levels, behavioral patterns, neurological changes and even brain waves. Smartphones can be used to diagnose, assess and treat Parkinson's disease. Earbuds could be used to monitor brain health.

This data is not protected under HIPAA, which prohibits health care providers and those working with them from disclosing your health information without your permission, because the law does not consider tech companies to be health care providers nor these wearables to be medical devices.

Legal protections

People have little choice when buying devices, using apps or opening accounts but to agree to lengthy terms that include consent for companies to collect and sell their personal data. This "consent" allows their data to end up in the largely unregulated commercial data market.

The government claims it can lawfully purchase this data from data brokers. But in buying your data in bulk on the commercial market, the government is circumventing the Constitution, Supreme Court decisions and federal laws designed to protect your privacy from unwarranted government overreach.

The Fourth Amendment prohibits unreasonable search and seizure by the government. Supreme Court cases require police to get a warrant to search a phone or use cellular or GPS location information to track someone. The Electronic Communications Privacy Act's Wiretap Act prohibits unauthorized interception of wire, oral and electronic communications.

Despite some efforts, Congress has failed to enact legislation to protect data privacy, the use of sensitive data by AI systems or to restore the intent of the Electronic Communications Privacy Act. Courts have allowed the broad electronic privacy protections in the federal Wiretap Act to be eviscerated by companies claiming consent.

In my opinion, the way to begin to address these problems is to restore the Wiretap Act and related laws to their intended purposes of protecting Americans' privacy in communications, and for Congress to follow through on its promises and efforts by passing legislation that secures Americans' data privacy and protects them from AI harms.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article. This article is part of a series on data privacy that explores who collects your data, what and how they collect, who sells and buys your data, what they all do with it, and what you can do about it.

Recently, a cheerful 100-year-old message in a bottle was found on the south-west coast of Australia. In it, a world war one soldier proclaimed to be "as happy as Larry."

If you're a betting person, you probably wouldn't expect great odds of this happening. A bottle cast into the ocean could end up absolutely anywhere.

If it floats to a remote location, there is little chance of somebody stumbling upon it. And if it lands somewhere more favorable where people could potentially find it, there are other issues. The message itself will deteriorate over time as light degrades it. If the bottle fills with water, it will sink and almost certainly never be found.

So, what are the chances of a message in a bottle being found and it being over 100? And what are your chances of finding this bottle?

Despite these many possibilities during a bottle's lifetime, the probability we are after is a straightforward calculation. Just count up the number of bottles with messages that have been found and are over 100 years old, and divide by the number of messages that have been sent this way (assuming we know how many are sent):

Our diagram below shows a hypothetical situation where 20 bottles are sent in total, of which six are found (indicated in gold) and one of these is over 100 years old (indicated by the "100" stamp). So, one in 20 bottles are found and over 100 years old. (Note: This is only a hypothetical calculation, not the real data.)

Instead of calculating the probability directly, another way to do it is by breaking the problem into two parts: (A) a bottle with a message is found, and (B) the found bottle is over 100. These two probabilities can be calculated separately and multiplied together to get what we want:

This is known as the "multiplication rule" of probability, and we confirm from our hypothetical numbers that (6/20)×(1/6) = 1/20, as before.

Both approaches to calculating this probability are simple. However, the direct calculation requires knowing the total number of bottles sent out, which is very difficult to know in the real world.

The multiplication rule has the advantage that it breaks the calculation into two parts. We can tackle each separately, then bring the two results together to get the probability we want. This is useful in the real-world situation where we can draw information from different sources.

First, we'll deal with the probability that a bottle with a message is found, irrespective of its age.

Experts from the Federal Maritime and Hydrographic Agency of Germany suggest a 1 in 10 chance that a message in a bottle will be found. This aligns broadly with various historical "drift bottle" experiments, where oceanographers released large numbers of bottles to understand ocean currents.

For example, studies from the 1960s and '70s in the North Atlantic Ocean led to recovery rates of 14% from the Gulf of Mexico, 8% from the Caribbean Sea and 7% from the northern Brazilian coast. A more recent and more northerly study (between Canada and Greenland) from the 2000s led to a 5% recovery rate.

We would expect the results to vary naturally from different experiments in different parts of the world. But to keep things simple, we will stick with 1/10 as the probability that a bottle with a message is found.

Now for the second piece of the calculation: of the bottles that are found, what proportion are over 100 years old?

The table below summarises data from news articles collected on Wikipedia about very old bottles with messages that have been found. However, only data on bottles over 25 years old has been collected, presumably because older bottles are more newsworthy.

So, we needed to estimate the number of 0- to 25-year-old bottles with messages ourselves — here’s how we did this.

The table shows that fewer bottles with messages are found as they get older. Messages in bottles degrade over time, which means the bottles have an increased chance of breaking and sinking, or just getting covered in layers of sediment. Plotting this data in the graph below helped us see the trend in the ages of found bottles more clearly.

We drew a line to match this observed trend in the ages of found bottles. This red line in the graph corresponds to the equation:

This equation provides an estimate of how many bottles have been found for any specific age range (where 25 = 0-to-25, 50 = 25-to-50 and so on). We are interested in the the 0- to 25-year-old bottles, so the equation suggests 46 bottles have been found in this range.

Adding up this and all of the numbers in the table gives a total of 106 bottles found, of which 12 are over 100 years old, and 12/106 is about one in ten.

Recapping the above, we have that: (A) one in ten bottles with messages are found, of which (B) one in ten are over 100 years old. Bringing these results together using the multiplication rule, we estimate the chance of a message in a bottle being found and it being over 100 years old to be (1/10)×(1/10) = 1/100.

So, if there are 100,000 bottles with messages floating around the oceans waiting to be found, we’d expect 1,000 of these to be found and be 100 or more years old. Assuming anybody in the world is equally likely to find one of these, with 8 billion people currently, that’s about a 1 in 8 million chance of you finding one – pretty unlikely.

However, some people are more persistent at message-in-a-bottle hunting than others. Following the paths of ocean currents (known as gyres) could provide clues on where to look.

Specifically, peninsulas or islands intersecting with these gyres could be good spots. For this reason, it has been suggested the Caribbean islands are ideally placed for finding bottles as they lie on the path of the North Atlantic Gyre. Which seems like a great reason to travel to the Carribean!

But let's also spare a thought for the poor soul stranded on their desert island, who surely won't appreciate the low odds of their SOS being found.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Loneliness is something most of us will experience at some point. It is a normal emotion, not a character flaw. But it is also something that can quietly affect how we think and remember, and researchers have long debated whether it might even raise the risk of dementia.

A new study, published in [the journal] Aging and Mental Health, suggests the picture is more complicated than either side of that debate has allowed for.

First, it is worth being clear about what dementia actually is. It is not a single diagnosis but an umbrella term covering a range of conditions — the most familiar being Alzheimer's disease — that cause memory loss, confusion, difficulties with language and a gradual loss of independence.

Cognitive decline, meaning a general slowing or weakening of mental function, is not the same thing. The two terms are often used interchangeably, but they should not be: you can experience cognitive decline without ever developing dementia.

We do not fully understand what causes Alzheimer's. We know that a healthy lifestyle lowers the risk, but it is no guarantee. Plenty of people who have done everything right still develop it. The disease is shaped by genetics, aging and biological factors we are still working to understand.

The new study followed just over 10,000 adults aged between 65 and 94 over six years. All were in good health at the outset, fully independent and free of dementia. Researchers tracked their memory over that period and asked whether loneliness played a role in how it changed.

The answer was nuanced. Loneliness did appear to contribute to memory difficulties — but there was no evidence that it led to dementia itself. That is an important distinction. Memory problems and dementia are not the same thing, and conflating them causes unnecessary alarm. This distinction is crucial, and while the researchers did not conflate the two, this nuance is often lost in interpretation.

Not the whole story

It is also worth noting that loneliness rarely travels alone. Many participants in the study also had diabetes, high blood pressure, depression or low levels of physical activity — all of which affect the brain independently. Diabetes, for instance, can interfere with how the brain processes glucose, the fuel it runs on, which in turn affects memory. Depression has a similar effect. Unpicking loneliness from these other factors is genuinely difficult, and the study does not fully resolve that problem.

One finding that stood out was the high rate of loneliness reported in southern Europe — a region often assumed to have strong social networks. It is a reminder that loneliness is subjective. Feeling lonely is not simply about how many people surround you — it is about how connected you feel to them.

There is also a methodological limitation worth noting. The study treated loneliness as a fixed state, when in reality it shifts — sometimes day to day — across the whole of a life. A single snapshot cannot capture that.

The broader research on loneliness and cognitive decline remains genuinely mixed, and this study does not settle it. What it does suggest, usefully, is that health services might benefit from screening for loneliness alongside routine cognitive testing: treating social connection as part of preventative medicine rather than a soft concern left to one side.

And there is reason for optimism. The brain is resilient. Research suggests that memory difficulties linked to loneliness can improve once that loneliness lifts and that staying socially active may boost cognitive performance more broadly. Loneliness, on its own, is unlikely to be the deciding factor in whether someone develops dementia.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

The successful Artemis II trip around the Moon was a historic achievement — the first crewed lunar fly-by in more than 50 years, and the greatest distance yet travelled by humans from our "pale blue dot".

The mission was marked by engineering, scientific and technical feats, by the astronauts and team at NASA and beyond, who got the crew there and back safely.

With the technical achievement came symbolic firsts, too. The first woman and the first person of color to orbit the moon. As astronaut Victor Glover put it, "people need to be able to see themselves in the things that they dream about".

Artemis II deserves celebration. But the celebration should not crowd out political scrutiny.

Power and resources on the moon

Artemis II is one mission in a broader US program to start establishing a permanent moon base by 2030.

This is about more than exploration. As US President Donald Trump has said, it is about asserting "American space superiority", establishing a "sustained American presence" and developing a lunar economy. The US colonial thinking of a "manifest destiny to the stars" returns.

The bigger picture is that the US sees itself in a "space race" with what NASA Administrator Jared Isaacman has called its "geopolitical adversary", China.

One point of conflict is access to finite, valuable resources at the lunar south pole, where water ice could sustain life and provide rocket fuel for missions to Mars. More speculative, profit-driven visions also play a part, from mining helium-3 to extracting resources from asteroids and bringing them to Earth.

Global rules — beyond the globe

International space treaties, largely forged during the 20th century Cold War, have little to say about appropriating resources off-Earth.

The US wants to shape the rules, and the US-led Artemis Accords are part of that effort. They are non-binding principles, but consequential.

Grounded in the Outer Space Treaty of 1967, they offer a "blueprint" for how resource activities, and other unsettled topics, may be governed.

Many observers see the Artemis Accords as more transparent and open than China's counterpart, the International Lunar Research Station. However, critics argue the Artemis Accords undermine multilateral, consensus-based processes.

Sixty-one countries have signed the Artemis Accords. Only nine new signatories have joined since Trump's return as US president, versus 19 in the year prior. It remains to be seen if the trend continues.

Why US leadership in space demands scrutiny

US leadership in space is often discussed only in contrast to China. This binary view can help the US escape scrutiny, especially in allied nations.

Consider America's recent actions here on Earth. As Artemis II drew our gaze skyward, the US–Israel war on Iran was intensifying.

In an expletive-filled post on Truth Social, Trump hinted at a nuclear attack with a threat that "a whole civilization will die tonight" unless Tehran reopened the Strait of Hormuz.

The US also threatened to target civilian infrastructure, after one strike hit a school, reportedly killing more than 150 people.

All of this occurred amid the ongoing crisis and civilian casualties in Gaza, where Trump's "Board of Peace" has faced criticism for seeking to function as an "alternative UN".

Trump has also revived territorial ambitions toward Greenland, saying: "We need it". He floated annexing Canada as the fifty-first US state. He spoke of the "honor of taking Cuba". He declared he would "run" Venezuela.

All of these places have natural resources that would give the US strategic advantages, including in critical minerals and oil.

This conduct has raised concerns from international lawyers and international organizations. Even US allies have spoken up, whom Trump criticized for not joining the Iran war.

Hard questions about a US-led future in space

A disregard for international law on Earth leads us to question how the US will ultimately act in space.

Scholars from the Global South, notably law professor Antony Anghie, have long argued that the US uses international law selectively and in line with its own interests. This is not new with Trump, even if the pattern has now become more visible and more intense. What may be changing is that more of the world is taking notice, including states that once benefited from that status quo.

At the World Economic Forum in Davos this year, Canadian Prime Minister Mark Carney described the "rules-based order" as "partially false", in which "international law applied with varying rigor depending on the identity of the accused or the victim". He was not speaking about space — but his point applies here too.

This puts question marks over US leadership in space — and whether it will abide by agreed rules when control over lunar resources is no longer just a hypothetical question. Even America's own Artemis Accords principles may prove optional if they stop being convenient to US interests.

That question is worth considering, given Trump has already justified withdrawing from many international instruments and organisations for this reason. Even NATO may be next.

No superpower should be immune from scrutiny — on Earth or beyond.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Imagine a creature nearly twice the size of a modern African elephant (which can weigh up to 6,000kg [13,000 lbs]). This was Elephas (Paleoxodon) recki, a prehistoric titan that roamed the landscape of what is now Tanzania nearly two million years ago. Now, imagine a group of our ancestors standing over its carcass, then butchering it and eating it.

For decades, archaeologists have debated when the hominin ancestors of humans first started eating megafauna — animals weighing more than 1,000kg [2,200 pounds].

In a new study, our team of archaeologists studying the evolution of the earliest humans in Africa has identified one of the earliest cases of elephant butchery.

This was at Olduvai Gorge in Tanzania, a site famous for containing some of the oldest and best preserved remains of our human ancestors. Dating back to 1.80 million years ago, this discovery at the site known as EAK reveals that our ancestors were engaging with megafauna substantially earlier than previously thought (about 1.5 million years ago was the previous estimate at Olduvai), and in a more sophisticated way.

This finding suggests that hominins (most likely, Homo erectus) may have been living in large social groups at this period, probably because their brains were developing and demanding higher-calorie diets rich in fatty acids.

"Smoking guns"

Part of the reason our ancient diet has been debated is that it is not easy to find evidence of how much animal food early humans were eating and how they were acquiring it.

In traditional archaeology, the "smoking gun" for butchery (cutting up carcasses) is a cut mark left on a bone by a stone tool. However, when dealing with big animals like elephants, these marks are difficult to find. An elephant's skin is several centimeters thick, and its muscle mass is so vast that a butcher's tool might never touch the bone. Furthermore, millions of years of burial can weather the bone surface, erasing any subtle traces. And if a bone is deposited in an abrasive sediment, trampling by other animals may generate marks on bones that look like cut marks.

At the EAK site, we found the partial skeleton of a single Elephas recki individual in the same place as Oldowan stone tools. But to prove that this wasn't just a natural death or the work of scavengers, we couldn't rely on bone marks. Instead, we turned to a new kind of detective work: spatial taphonomy. This is the study of how stone artefacts and bones occur spatially on the same site. We also turned to more direct evidence: bones from those fossilized elephants that had been splintered while they were fresh ("green breaks").

The geometry of a carcass

To solve this 1.8-million-year-old mystery, we analyzed the way the bones were scattered across the site. Every agent that interacts with a carcass — whether it’s a pride of lions, a group of hyenas, or a band of humans — leaves a unique "spatial fingerprint". Lions and hyenas tend to drag bones away, scattering them in predictable patterns based on their weight and the amount of attached meat. Natural deaths, like an elephant dying in a swamp, result in a different, more localised skeletal "collapse".

By using advanced spatial statistics, and later comparing the EAK site to several modern elephant carcasses that we studied in Botswana (not yet published), we found that the spatial configuration at EAK was unique. The clustering of the bones and the density of the stone tools among them did not match the "random" or "scavenger-driven" models. Instead, it reflected a focused, high-intensity processing event. The spatial signature was a match for hominin butchery, which has also been documented at Olduvai sites that are half a million years younger.

This was confirmed by the presence of green-broken long bones not just at EAK, but in several locations in the landscape where other elephant and hippopotamus carcasses were butchered. Today, only humans can break elephant long bone shafts; not even spotted hyenas, which have very powerful jaws, can do it.

Glimpses of this behavior can be detected at other sites too. For example, a cut-marked bone fragment of a large animal (probably a hippopotamus) was documented at El-Kherba (Algeria) dated to 1.78 million years ago.

This intensive and repeated discovery of multiple elephant and hippopotamus carcasses butchered at different landscape locations indicates that humans were butchering the remains of large animals, whether hunted or scavenged.

Why does an elephant meal matter?

This discovery isn't just about a prehistoric menu; it's about the evolution of the human brain and social structure. There is a long-standing theory in paleoanthropology called the "expensive tissue hypothesis". It suggests that as our ancestors’ brains grew larger, they required a massive increase in high-quality calories, specifically fat and protein. Large mammals like elephants are essentially giant "packages" of these calories. Processing even a single elephant provides a caloric windfall that could sustain a group for weeks.

Butchering an elephant is a monumental task, however. It requires sharp stone tools and, most importantly, social cooperation. Our ancestors had to work together to defend the carcass from predators like saber-toothed cats and giant hyenas, while others worked to extract the meat and marrow.

This suggests that even 1.8 million years ago, our ancestors already possessed a level of social organization and environmental awareness that was truly "human".

The discovery also has another dimension. Humans at that time, like modern carnivores, consumed animals whose size was related to their own group size. Small prides of lions eat wildebeests; larger prides eat buffalo and in some places even juvenile elephants. The evidence that those early humans were exploiting large animals comes in parallel with evidence that they were living in much larger sites than before, probably reflecting bigger group sizes.

Why early humans started living in large groups at that time remains to be explained, but this indicates that they certainly needed more food.

A shift in the ecosystem

The EAK site also tells us about the environment. By analyzing the tiny fossils of plants and microscopic animals found in the same soil layers, we reconstructed a landscape that was transitioning from a lush, wooded lake margin to a more open, grassy savanna. Our ancestors were already eating smaller game. There is evidence that two million years ago, they were hunting small and medium-sized animals (like gazelles and waterbucks). A little earlier, they began using technology (stone tools) to bypass their biological limitations.

The evidence from Olduvai Gorge shows that our ancestors were remarkably adaptable, capable of thriving in changing climates by developing new behaviours.

As we look at the spatial layout of these ancient remains, we aren't just looking at the bones of an extinct elephant. We are looking at the traces of a pivotal moment in our own history — when a small group of hominins looked at a giant and saw not just a threat, but a key to their survival.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Editor's note: This story was updated at 12:49 p.m. ET on April 13 to change hominids to hominins in the strapline. Hominins are a group that includes humans and our most closely related relatives.

What do you know about elephants? Test your knowledge with our elephant quiz!

Across the Earth, every night, thousands of automated stargazers are waiting to take pictures of shooting stars. I am one of the scientists who study these meteors.

Most movies and news alerts focus on large asteroids that could destroy the Earth. And your phones notifies you every few months that an object nine washing machines wide is going to just narrowly skim past. However, the small dust and rubble that enter our atmosphere daily tell an equally interesting story.

My planetary science colleagues and I use camera observations of the night sky to better understand dust, car-sized asteroids and debris from comets in our solar system.

In a study published in March 2026, I searched through millions of meteor observations collected by all-sky camera networks based in Canada, Japan, California and Europe and found a small, recently formed cluster. The 282 meteors associated with this cluster tell the story of an asteroid that got a little too close to the sun.

Meteor formation

When a sand-sized crumb of space rock hits our atmosphere, it heats up almost instantly, vaporizing its surface layer and turning it into an electrically charged gas. The whole fragment starts to glow — this is what we call a meteor. If the object is larger, like a boulder, and brighter, it's called a bolide or a fireball. On average, these objects hit our atmosphere going over 15 miles per second. For small dust or sand-sized objects, the whole process lasts only a fraction of a second before they completely disappear.

Most of these sand-sized fragments in the solar system originate from comets — cold, icy objects from the outer reaches of the solar system. As comets pass by the sun, their icy components turn to gas, releasing tons of dust. This is why comets are often called "dirty snowballs" and appear fuzzy in telescopic images.

Asteroids, on the other hand, are leftovers from the early solar system that formed closer to the sun. They are dry and rocky, and do not have the same ices that give comets their characteristic tails.

What does it mean to be active?

Astronomers call an asteroid or comet "active" when it sheds dust, gas or larger fragments. This activity is caused by some external force on the object in space, like heat from the sun, a small impact, or when asteroids spin too fast and fly apart.

Understanding and identifying activity helps scientists better understand how these objects change over time.

For comets, sublimation of ices — when solid ice turns directly into gas, skipping the liquid phase — is the primary culprit. However, for asteroids, the reason for activity can vary greatly.

For example, NASA's OSIRIS-REx mission, which launched into space to study an asteroid named Bennu, saw activity from its surface, with heat stress and small impacts among the leading explanations.

Other sources for asteroid activity include breakup when an asteroid spins too fast, tidal forces ripping apart asteroids during close encounters with a planet, or gas release.

Researchers most commonly search for activity using telescopes. Astronomers can look for a "tail" or fuzziness around the object. This tail is a clear sign that there is gas and dust around the body. But there is another way to search for activity — meteor showers.

Finding hidden asteroids via meteor showers

The most famous active asteroid is 3200 Phaethon. It is the parent body of the Geminid meteor shower that occurs every year in mid-December. During past close approaches with the sun, Phaethon released vast amounts of dust and larger fragments. These morsels of Phaethon have spread out along its entire orbit over time, leading to the present Geminid meteor stream.

Each meteor shower we observe occurs when the Earth passes through one of these debris streams. So if astronomers can detect meteor showers, they can also be used to find active objects in space.

At first, debris shed by an asteroid or comet travels closely together. Imagine squeezing a single drop of food dye into a moving stream of water: Initially, the dye stays in a tight, concentrated cloud. But as it flows, the water's swirling currents pull at the dye, causing it to spread out and fade.

In space, the gravitational tugs from passing planets act like those currents. They pull on the individual meteor fragments in slightly different ways, causing the once-tight stream to gradually drift apart until it completely dilutes into the background dust of our solar system.

The discovery of a rock-comet

In a study published in March 2026 in the Astrophysical Journal, I used millions of observations of meteors to search for recent, unknown activity from asteroids near the Earth. I found one clear cluster of 282 meteors that stood out.

What makes this discovery so exciting is that we are essentially witnessing a hidden asteroid being baked to bits. This newly confirmed meteor stream follows an extreme orbit that plunges almost five times closer to the Sun than Earth does.

Based on how these meteors break apart when they hit our atmosphere, we can tell they are moderately fragile, but tougher than stuff from comets. This finding tells us that intense solar heat is literally cracking the asteroid’s surface, baking out trapped gases and causing it to crumble. This is likely a major source of past Phaethon activity and the main reason the meteorites on Earth are so diverse.

The search for the source

Why does finding a hidden, crumbling asteroid matter? Meteor observations act as a uniquely sensitive probe that lets us study objects that are completely invisible to traditional telescopes.

Beyond solving astronomical mysteries, analyzing this debris helps us understand the physical evolution of asteroids and comets in our solar system. More importantly, it reveals hidden populations of near-Earth asteroids, which is vital information for planetary defense.

The new meteor shower's parent asteroid remains elusive. However, NASA's NEO Surveyor mission, launching in 2027, offers a promising solution. This space telescope, dedicated to planetary defense and the discovery of dark, hazardous, sun-approaching asteroids, will be the ideal tool for searching for the showe's origin.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Cars on the road today are 99% cleaner than they were in 1970. Air quality in the United States is much, much better as a result. In Los Angeles, where I live, lead levels in the air were 50 times higher in the 1970s than today, and the amount of lead in kids’ blood has plummeted.

What made that drop possible is arguably the most important environmental technology ever invented: the catalytic converter.

California has long had the authority under the federal Clean Air Act to set emissions standards for cars and trucks that are higher than the nation's, and its early use of that authority is a major reason why catalytic converters are now standard in vehicles and people are healthier across the country.

At a time when the Trump administration is attacking California's ability to cut air and climate pollution and revoking its Clean Air Act waivers, it's helpful to remember just how important the state's leadership has been in making the air Americans breathe so much healthier.

As I recount in my forthcoming book, "Smog and Sunshine: The Surprising Story of How Los Angeles Cleaned Up Its Air," California's role in the emergence of catalytic technology is often downplayed. The passage of the 1970 Clean Air Act is typically given the credit. That law deserves accolades for its key role. So does William Ruckelshaus, the first administrator of the U.S. Environmental Protection Agency.

But without California's willingness in the early 1970s to push automakers to meet tough standards, the technology would have developed more slowly and the air would have remained dirtier for many more years.

Birth of the catalytic converter

Eugene Houdry invented the first catalytic converter technology in the 1950s. Years earlier, he had developed the Houdry process for catalytic cracking, which makes converting crude oil into gasoline much easier. That invention in the mid-1930s helped spur the mass adoption of cars and trucks in the U.S.

Widespread car ownership altered American life, changing where people lived, worked and vacationed. But cars also brought terrible smog as their use skyrocketed. When Houdry realized his life's work was choking the air of Los Angeles, he decided to do something about it. By the late 1950s, Houdry had invented a rudimentary catalytic converter.

You might think that this invention, which Houdry said could make "the lung cancer curve dip," would lead carmakers to install the technology on their new vehicles.

But that is not what happened. Instead, auto manufacturers engaged in what the government described as a yearslong conspiracy to keep emissions-limiting technology off the market, ultimately leading to an antitrust legal settlement.

It wasn't until the passage of the 1970 Clean Air Act that carmakers got serious about improving upon Houdry's invention for mass market installation.

The Clean Air Act's ambition

The 1970 Clean Air Act is a remarkable piece of legislation. Passed with only one negative vote and signed into law by President Richard Nixon, the act set wildly ambitious goals. They included a requirement that carmakers cut auto pollutants by 90% by 1975.

Congress passed this requirement knowing that the technology to cut emissions wasn't ready for prime time. Houdry's catalytic invention couldn't work with leaded gasoline, and it hadn't been tested in tough conditions, such as freezing cold or sweltering heat.

The Ford Motor Co., with Lee Iacocca as its president, told Congress in 1970, "If such (pollution cuts) are established … the technology as we know it today would not permit us to continue to produce cars after January 1, 1975."

Congress ignored Ford's dire warning and passed the stringent cuts.

Automakers responded with two separate tactics. The first was to gear up — alongside companies like Corning Glass and the Engelhard Company — to develop technology to meet the 90% cuts. Most of their efforts focused on improving the catalytic converter, made more plausible when Engelhard determined that catalytic converters wouldn’t corrode with unleaded gasoline. The EPA's Ruckelshaus ordered gas stations to make unleaded gasoline available as of Jan. 1, 1975.

While the auto companies worked to meet the congressional mandate, they also pressured Congress and the courts to weaken or delay it. The U.S. Court of Appeals for the District of Columbia Circuit obliged, ordering Ruckelshaus to extend the deadline for compliance by a year. Congress eventually extended the deadline to 1981.

But California did not let up.

A gamble that paid off

California has the authority under federal law to issue its own automobile pollution standards, as long as the standards are stronger than federal standards and the state receives a waiver from the EPA. No other state has similar power, but states can adopt California's higher standards.

After the federal appeals court gave carmakers an extra year to comply with the federal rules, California decided it would not let car companies off the hook.

The state asked Ruckelshaus to grant a waiver for California to issue standards tough enough that carmakers would have to install catalytic technology to meet them.

Ruckelshaus faced enormous pressure to deny the waiver, with automakers arguing that the technology was neither effective nor available. But in a hint of the resolve he would later show in refusing Nixon's order to fire Watergate special prosecutor Archibald Cox, Ruckelshaus gave California the go-ahead in 1973, and the state's rules went into effect for the 1975 model year.

He reasoned that doing so would maintain "continued momentum toward installation of (catalyst) systems … while minimizing risks incident to national introduction of a new technology." In other words, California could serve as a guinea pig for the rest of the country by adopting tough standards.

The gamble paid off. Since California was the nation's largest auto market, companies had strong economic incentives to change their models to meet the state’s standards. Catalytic technology is now not only standard on American vehicles but also on vehicles around the world, and air quality in the U.S. is vastly improved.

With the adoption of the catalytic converter, leaded gasoline was banned and eventually phased out, and lead levels began to drop almost immediately.

Continuing California's legacy

Catalytic converters have removed 8 billion tons of pollution from the air in the U.S. They have saved hundreds of thousands of lives and led to the removal of a deadly neurotoxin, lead, from the atmosphere.

California's standards have spurred important technological innovations for vehicles, including new types of less-polluting gasoline and vehicles that emit no pollution at all.

But the state's ability to set higher standards is under attack. Congress — at the behest of the Trump administration — has overturned three waivers the state was granted to cut even more pollutants and the greenhouse gases that cause climate change. The Trump administration has also sued California to invalidate its mandates for automakers to sell zero-emissions vehicles.

Today, California officials are searching for alternative ways to continue to make cars and trucks cleaner. The state has set aside money to replace federal tax incentives for electric vehicles, and the Legislature is exploring creative ways to hold indirect sources of emissions, such as rail yards, ports and warehouses where vehicles are constantly running, accountable for air pollution.

But these alternatives aren't as powerful as the authority to exceed federal standards to make the air cleaner.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Freelance space writer Roger Guillemette has witnessed close to 100 rocket launches since 1975. On Wednesday (April 1), he was on the ground at NASA's Kennedy Space Center, reporting live on the Artemis II moon launch for Live Science. Here's what he saw at the historic liftoff:

There was palpable excitement at the Kennedy Space Center (KSC) press site for the Artemis II launch, unlike anything I've experienced in my many years of reporting on human spaceflight from this iconic location.

Journalists from all over the world — both grizzled veterans and wide-eyed newcomers — were positively giddy about witnessing astronauts returning to the moon after so many decades.

Bright television lights glowed atop the news organization trailers along "media row" as the major networks assembled their A-teams to cover the landmark event. Morning and evening national newscasts originated from KSC, with the Vehicle Assembly Building's huge American flag and NASA "meatball" logo (first unveiled in 1959) serving as a dramatic backdrop. What was old suddenly felt new again.

Those of us on the older end of the age spectrum have fuzzy, fading memories of the Apollo era. For me, the historic Apollo 11 lunar landing mission in July 1969 filled the week of my 10th birthday; a few years later, in December 1972, a buddy and I "camped out" in his finished basement, watching color (!) television until after midnight to see Apollo 17 light up the heavens over Florida's Space Coast on what would be the final crewed voyage to the moon for 50 years and counting.

After those heady years of the "moon race," the closest experience to Artemis II for me was the first flight of the space shuttle Columbia, STS-1, in April 1981. As a college senior, I stood just a few hundred yards from the spot where I watched Artemis II, witnessing a brand-new, never-flown space plane soar skyward into the dawn. I remember watching Columbia leap off the launchpad while I softly whispered, "Go, go," with tears welling in my eyes. I found myself unconsciously doing the same for Artemis II (now with a few added colorful epithets).

Artemis II's launch was impossibly bright to witness in person. Still images or video simply do not capture the sheer brilliance and intensity of the Space Launch System's ignition and liftoff. Seeing the brilliant white-orange plume concentrate beneath the rocket was like looking at the sun itself, and it appeared much more dazzling than any space shuttle launch I ever witnessed. You don't simply watch the mighty rocket rise — you feel it, shaking the ground beneath you, its powerful, staccato thumping reverberating through your chest.

More than five decades after Apollo 17 astronauts Gene Cernan and Harrison "Jack" Schmitt reluctantly departed the spectacular rolling hills and massive boulders of the lunar valley known as Taurus-Littrow, the United States (with its international partners) is once again taking the bold steps to continue exploring the strange new world it abandoned generations ago.

The goal has always been in sight. On a clear winter night, it rides high in the heavens, bringing light to barren, snow-covered landscapes. On a cool autumn evening, it hangs impossibly large on the eastern horizon, casting a warm orange glow on farmers and stargazers alike — each witness sharing the feeling that they can almost reach up and touch it.

Almost.

The goal has never been out of sight. It beckons us all to stop and renew an old acquaintance: our neighbor, the moon.

Think you know about the moon? Test your smarts with our moon quiz!

For decades, cars dictated urban planning in the United States.

Few could have predicted that they would one day also double as nodes for surveillance.

In thousands of towns and cities across the U.S., automatic license plate readers have been installed at major intersections, bridges and highway off-ramps.

These camera-based systems capture the license plate data of passing vehicles, along with images of the vehicle and time stamps. More recently, these systems are using artificial intelligence to create a vast, searchable database that can be integrated with other law enforcement data repositories.

As a scholar of technology policy and data governance, I see the expansion of automatic license plate readers as a source of deep concern. It's happening as government authorities are seeking ways to target immigrant and transgender communities, are already using AI to monitor protests, and are considering deploying AI systems for mass surveillance.

Eyes on the road

Using cameras to track license plates dates to the 1970s, when the U.K. was embroiled in a long-simmering conflict with the Irish Republican Army.

The Met, London's police force, developed a system that used closed-circuit television cameras to monitor and record the license plates of vehicles entering and exiting major roads.

The system and its successors were seen as useful crime fighting tools. Over the next two decades, they expanded to other cities in the U.K. and around the world. In 1998, U.S. Customs and Border Protection implemented this technology. By the 21st century, it had started appearing in cities across the U.S.

There are different ways for a jurisdiction to implement these systems, but local governments usually sign contracts with private companies that provide the hardware and service.

These companies often entice authorities with free trials of surveillance equipment and promises of free access to their data in ways that bypass local oversight laws.

AI thrown into the mix

Recently, AI has been incorporated into these camera systems, significantly increasing their reach.

The vehicle information that's captured is typically stored in the cloud, creating a massive web of data repositories. If a camera collects information from a suspect's car or truck — say, one also listed in the National Crime Information Center — AI can flag it and send an instant alert to local law enforcement.

In fact, that's a selling point of Flock Safety, one of the biggest providers of automatic license plate readers. The company uses infrared cameras to capture images of vehicles. AI then analyzes the data to identify subjects and quickly alert local authorities.

On the surface, automatic license plate readers seem like a logical way to fight crime. More information about the whereabouts of suspects can potentially help law enforcement. And why worry about cameras if you're following the law?

But there are few peer-reviewed studies on their effectiveness. Those that exist find little evidence that they've led to reductions in violent crime rates, though they seem to be helpful in solving some crimes, like car thefts.

Furthermore, installation and maintenance are costly.

For example, Johnson City, Tennessee, signed a 10-year, US$8 million contract with Flock in 2025. Richmond, Virginia, paid over $1 million to the company between October 2024 and November 2025 and recently extended its contract, despite opposition from some residents.

The Conversation reached out to Flock for comment and did not hear back.

Erosion of civil liberties in plain sight

The technology seems to highlight the pitfalls of what scholars call "technosolutionism," the belief that complex issues like crime, poverty and climate change can be solved by technology.

Even more disquieting, to me, is the fact that these camera systems have created a mass location tracking infrastructure knitted together by artificial intelligence.

The U.S. doesn't have a federal law like the European Union's General Data Protection Regulation that meaningfully limits the collection, retention, sale or sharing of location and mobility data.

As a result, data gathered through surveillance infrastructure in the U.S. can circulate with limited transparency or accountability.

License plate readers can easily be accessed or repurposed beyond their original goals of managing traffic, meting out fines or catching fugitives. All it takes is a shift in enforcement priorities — or a new definition of what counts as a crime — for the original purpose of these cameras to recede from view.

Civil liberties groups and digital rights organizations have been sounding the alarm about these cameras for over a decade.

In 2013, the American Civil Liberties Union published a report titled "You are Being Tracked: How License Plate Readers Are Being Used To Record Americans' Movements." And the Electronic Frontier Foundation has decried them as "street-level surveillance."

A counter-camera movement emerges

The promise of these cameras was simple: more data, less crime.

But what followed has been murkier: more data, and a significant expansion of power over the public.

Without robust legal safeguards, this data can possibly be used to target political opposition, facilitate discriminatory policing or chill constitutionally protected activities.

This has already happened during the current administration's aggressive deportation efforts. Automatic license plate reader databases were shared with federal immigration agencies to monitor immigrant communities. Recently, Customs and Border Protection was granted access to over 80,000 Flock cameras, which have also been used to surveil protests.

DeFlock's map of Flock cameras shows that Beverly Hills really went hard on Santa Monica Blvd, and only Santa Monica Blvd. Seems redundant?deflock.org/map

— @lemonodor.bsky.social (@lemonodor.bsky.social.bsky.social) 2026-03-27T20:03:38.116Z

Then there's reproductive health care. After the Supreme Court overturned Roe v. Wade in 2022, there were fears that people traveling across state lines to get an abortion could potentially be identified through automatic license plate reader databases. In Texas, authorities accessed Flock’s surveillance data as part of an abortion investigation in 2025.

Flock told NPR in February 2026 that cities control how this information is shared: "Each Flock customer has sole authority over if, when, and with whom information is shared." The company noted that it has made efforts to "strengthen sharing controls, oversight and audit capabilities within the system." But NPR also reported that many city officials around the U.S. didn't realize how widely the data was being shared.

In response, some states have sought to regulate the technology.

Washington state lawmakers are deliberating the Driver Privacy Act. The legislation would prohibit agencies from using the surveillance technology for immigration investigations and enforcement, and from collecting data around certain health care facilities. Protests would also be shielded from surveillance.

Meanwhile, grassroots initiatives such as DeFlock have also emerged.

DeFlock's online platform documents the spread of automatic license plate reader networks in order to help communities resist their deployment. The movement frames these systems not merely as traffic technologies, but also as linchpins of an expanding government data dragnet — one that demands stronger democratic oversight and community consent.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Endometriosis is a painful, debilitating condition affecting 10% of women worldwide. It occurs when tissue similar to the lining of the uterus (known as lesions) grows elsewhere in the body — usually within the pelvis.

Treating endometriosis can be difficult. Usually, treatment involves either preventing the growth of these lesions in the first place or removing lesions surgically. But even when lesions have been surgically removed, symptoms often don't go away.

Traditionally, endometriosis has been thought of as a gynecological condition. But mounting evidence suggests this characterization downplays the disease's complexity. Endometriosis appears to affect far more than just the reproductive system. According to a growing body of research, it influences immune function throughout the whole body.

Recognizing it as a whole-body, immune-driven disease could help explain why symptoms range far beyond pelvic pain. It would also explain why treatment is so challenging and often does little to reduce symptoms.

A disease of the whole immune system

Inflammation — the body's natural response to injury or illness – is a normal part of immune response. It also plays a key role in the menstrual cycle.

But if inflammation becomes chronic or uncontrolled, it can cause problems. This is seen in autoimmune conditions such as rheumatoid arthritis, where the immune system overreacts even when there is no threat.

Chronic inflammation is also known to play a central role in endometriosis. But the effects of this uncontrolled immune response may be far more widespread than previously thought. According to recent research, the immune response appears to extend into the bloodstream and other body systems. This may explain why endometriosis causes such far-reaching, whole-body symptoms.

In people with endometriosis, immune cells appear to be less able to clear lesions. Yet, at the same time, people with endometriosis have higher levels of immune proteins such as IL-6 and IL-1β in their blood. These immune proteins, known as cytokines, are a type of messenger released by cells to promote inflammation.

Together, these dysfunctional cells make it possible for lesions to grow and persist. This immune dysregulation also has ripple effects across the body, contributing to the wide range of symptoms sufferers experience.

For instance, many people with endometriosis experience debilitating fatigue, cognitive difficulties (such as "brain fog") and widespread pain. These symptoms are rarely emphasized in clinical guidelines, yet they're often as disruptive as pelvic pain itself.

Systemic inflammation offers a compelling explanation for these symptoms. Circulating cytokines, such as those mentioned earlier, are known to influence brain function and energy regulation. Higher levels of cytokines (including IL-6) have also been linked to poorer concentration, disrupted sleep and fatigue in some autoimmune and chronic pain disorders.

These same processes may be occurring in endometriosis. This suggests that invisible symptoms could be biological consequences of ongoing inflammation — not secondary effects of pain.

A dysfunctional immune system may also help to explain why emerging research hints at an overlap between endometriosis and autoimmune diseases.

In 2025, a large scale study looked at 330,000 patients with endometriosis and 1.2 million controls (people who didn't have the condition). The study found that compared to the controls, people with endometriosis had roughly twice the odds of being diagnosed with an autoimmune condition — such as rheumatoid arthritis, lupus, multiple sclerosis or Hashimoto's disease — within two years of their endometriosis diagnosis.

This doesn't mean endometriosis is itself an autoimmune disease. But it does suggest shared mechanisms — including chronic inflammation, dysregulated immune cell activity, and problems with the immune system recognizing the body’s own tissue properly.

These overlapping features strengthen the case for understanding endometriosis as a systemic immune disorder.

Reframing endometriosis

Viewing endometriosis in this way could transform how it's diagnosed, treated and understood. It could also help us get closer to finding a solution for the condition.

Current treatments primarily target the reproductive system. But if endometriosis involves widespread immune dysfunction, then therapies that modulate immune pathways may offer more effective long-term relief.

Seeing endometriosis as a systemic condition can empower patients, as well. This reframing may help them understand that symptoms such as fatigue, joint pain, cognitive difficulties and immune sensitivity are not imagined or unrelated. Rather, they’re part of the condition’s broader biology.

Seeing it this way may support patients in advocating for themselves in healthcare settings, where systemic symptoms are often dismissed or deprioritized.

A systemic framing also opens space for patients to explore complementary management strategies aimed at reducing inflammation or improving overall wellbeing. While not curative, some people find gentle movement, stress regulation techniques and heat–cold contrast therapy helpful for managing pain or inflammatory flares.

A growing body of research shows that endometriosis is not solely a reproductive condition or a "bad period." It's a multi-system, inflammatory disorder with far-reaching health effects throughout the body.

Understanding endometriosis as a systemic immune disease is a crucial step toward better treatments, better support and, ultimately, better health outcomes.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

President Donald Trump's war on Iran is the perfect embodiment of all that is wrong with our ongoing fossil fuel dependence. And it puts an exclamation mark on the case for a clean energy transition. Renewable energy promises a more secure, domestically sustainable and inexhaustible energy source — via wind, solar, geothermal and energy storage technology.

It doesn't lead to the further warming of our planet and the destabilization of our climate. And it doesn't lead to us fighting dangerous, often misguided, wars in far-flung lands.

This isn't the first time a global event has placed a huge, shining light on the benefits of moving away from fossil fuels. Five years ago I opined that there might be just the slightest sliver of a silver lining in the tragic COVID pandemic. Despite the devastating loss of life, perhaps it provided us with an occasion to rethink our unsustainable ways, an opportunity to choose a better path — a "green reset."

The pandemic, and lockdowns that ensued, saw oil prices dropping for the first time ever. We didn't need fossil fuels to get around because no one could go anywhere. Renewables, however, are largely unaffected by demand and proved resistant to the global economic shock.

As governments sought to jump start the economy, it seemed an opportune time to retire our dirty fossil fuel energy infrastructure and rebuild in its place a clean, green global economy, tackling the greatest challenge we face today — the climate crisis.

But it was not to be. As my co-author Dr. Peter Hotez and I detail in our recent book "Science Under Siege" (PublicAffairs, 2025), petrostates, plutocrats and bad actors who benefit from the fossil fuel status quo simply doubled down in their efforts to spread propaganda and disinformation, turning the idea of a "great reset" into a boogie man of the right-wing conspiracy theory fever swamps.

Another reason for this failed opportunity was that the connection between the immediate crisis and the underlying environmental factors was subtle. Habitat destruction and climate change both favor the conditions that allow for the type of zoonotic transmission (e.g. from bats or pangolins to humans) involved in the spread of novel coronaviruses. But look at how long that last sentence was.

In the case of Trump's war on Iran (and his previous attack on Venezuela for that matter), the connection is comparatively simple: It's about the fossil fuels, stupid!

The warming of the planet poses an unprecedented threat in the form of more dangerous storms, rising sea levels, coastal inundation and deadly, damaging extreme weather events. It is a direct consequence of the continued extraction and burning of fossil fuels. And Trump's war on Iran is fundamentally about fossil fuels.

The war against Iran advances the interests of petrostates like Saudi Arabia and Russia and supports the fossil fuel industry by attempting to seize from Iran control of the flow of oil and liquified natural gas through the Strait of Hormuz.

The U.S. itself is a petrostate under Trump and GOP rule — with the administration actively opposing green energy projects that could help make the country's energy supply self-sufficient. And our continued fossil fuel dependence poses a great threat to our nation. It's a double whammy. It makes us dependent on buying oil and gas from dangerous foreign nations, as epitomized by this unpopular war, expending tremendous amounts of blood and treasure in the effort to maintain access to fossil fuel reserves around the world. And it damages the climate, pushing us toward a dangerous, unstable planetary future.

We now understand the market instability associated with our continued reliance on fossil fuels, as the closure of the Strait of Hormuz causes gasoline prices in the U.S. spike to levels not seen in years, driving a broader increase in the cost of goods and services that is propagating through the economy and negatively impacting consumers.

Renewable energy is actually cheaper than fossil fuel energy now on a levelized basis (and that’s not even accounting for the tremendous cost of climate damages). They can be produced on a domestic level and provide something fossil fuels cannot — predictability and security.

That's why the fossil fuel-driven Trump administration has put its thumb on the scales to block, or at least slow down, the inevitable transition to clean energy. The absurdity of these efforts has reached new levels with the recent report that the Trump administration paid a major energy company $1 billion to stop a project to build wind farms off the U.S. East Coast and invest the money in a Texas natural gas facility instead.

Trump's assault on renewable energy, meanwhile, is raising energy prices, along with his tariffs. His war of choice against Iran is adding to the affordability crisis that, ironically, now threatens his presidency.

Fortunately, we are seeing progress at the state and regional level. Virginia, for example, with its Democratic, climate-forward governor Abigail Spanberger, is forging ahead with a new offshore wind farm that has just begun producing electric power, having prevailed against the Trump administration and its effort to block the project.

Elections have consequences, and the midterm election — less than a year from now — will be an opportunity to put a check on a misguided administration that is taking us down an ever-more-treacherous road of fossil fuel dependence, war and economic devastation.

We need, in the meantime, to envision a better future — a clean energy future with a livable climate, in which we don't start dangerous foreign wars in a desperate effort to extract every last bit of fossil fuel.

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

The seven U.S. states that make up the Colorado River basin are struggling to agree on how best to manage the river's water as its supply dwindles due to climate change and a period of prolonged drought. Their negotiations, which are not open to the public, missed a Feb. 14, 2026, deadline the federal government had established, after which federal officials said they would impose their own plan.

The federal government has not yet done so, but the prospect of such an action is not good news for the nearly 40 million people who depend on the Colorado River for water, energy, agriculture and recreation, nor for the estimated US$1.4 trillion in economic activity the river supports.

We have led or participated in complex water management discussions from the river's headwaters in Colorado to its delta in Mexico and elsewhere in the arid Southwest and around the world. Even on less contentious issues, the keys to success involve learning together, understanding one another's interests, working through conflict and developing inclusive solutions for diverse participants. And that works best with an outside facilitator.

The five most common sources of conflict between people are values, data, relationships, interests and structure. The current Colorado River negotiations include all five. We believe a process designed and facilitated by negotiation experts could help break the logjam.

We recognize it can be very hard to reach an agreement when what’s at stake are countless lives, massive amounts of money, enormous quantities of hydroelectric power and not nearly enough water.

But compromise on Colorado River management is possible and, in fact, was achieved to curb California's water use in the 2000s, to negotiate an interim agreement to coordinate operations at the Lake Mead and Lake Powell reservoirs in 2007, and to enact contingency plans to manage drought in 2019. But this time around, circumstances are different.

Previous negotiations

The negotiations leading up to those agreements were often facilitated by officials from the U.S. Bureau of Reclamation who focused on reaching broad agreements on general principles and concepts before delving into details. Federal staff also actively guided key agreements and provided the science and computer models to make well-informed decisions. And the states' negotiators knew the Department of Interior would act unilaterally to make damaging cuts to water supply if states couldn't come to their own agreement.

The negotiators for the states had long-standing relationships and built trust by frequently communicating outside formal meetings and seeking to listen to and understand other states' perspectives, even if they didn’t agree.

The states also agreed to use the bureau's computer model for analyzing scenarios of climate change and management decisions. That meant all the negotiators were looking at the same data when delving into possible options. And the political and social environment was less polarized than today.

The current situation

In this round of negotiations, federal leadership has been lagging. The Department of the Interior has not made clear what the consequences might be for the states if they fail to agree. The U.S. Bureau of Reclamation has been without a permanent commissioner since President Donald Trump retook office in January 2025.

And federal staff have only recently begun helping to facilitate the discussions.

The states are fractured into subgroups, according to whether they are in the river's Upper Basin – Colorado, Wyoming, Utah and New Mexico – or the Lower Basin, which includes Arizona, Nevada and California. Each basin group holds strong positions and has generally been unwilling to shift.

Each basin group is using a different set of assumptions for the bureau’s computer model to explore options. And the discussion often gets stuck on details, which prevents progress toward broader agreements.

In addition, the political context has shifted significantly, with increased polarization and politicization of the issues, creating barriers to effective dialogue and deliberation. Today, compromise can seem unattainable.

But those relatively new challenges to Colorado River compromise are not an excuse for failure.

A way forward?

The current negotiations have all been done behind closed doors. From talking with people involved in the negotiations, we understand the negotiators have been left to set their own agendas and meeting plans and conduct their own communications and follow-up, with no formal facilitators.

It's reasonable to expect the negotiators to be ready to represent their states' interests, working through an incredibly complicated landscape of hydrology, climate and management scenario modeling, water law and administration, and politics. But we believe it's unreasonable — and unrealistic and unfair — to expect them to also be experts at designing and facilitating an effective process for sorting out their differences.

Federal officials are not necessarily the best people to run the process either. And if the agency that ultimately needs to approve any deal is the one leading the process, real or perceived biases about the states or key issues in the agreement could further complicate the discussions.

We believe that agreement between the seven states is still possible. It may be less effective to bring in a third-party facilitator at this stage in the negotiation process, though, because of the degraded trust, hardened positions and shortage of time.

One possible outcome is that the Bureau of Reclamation will select and enforce one of the five management alternatives it outlined in January 2026. But that could lead to decades of litigation going up to the Supreme Court. No one wins in this scenario.

A more hopeful possibility is that the bureau adopts short-term rules that would give the states another chance to negotiate a longer-term deal — ideally with an unbiased third-party facilitator for support.

A collaborative and consensus-based planning process in the Yakima River Basin in Washington state in the early 2010s is evidence that while nobody gets everything they want in a negotiated agreement, "if they can (all) get something, that's really the basis of the plan," as a Washington state official told The New York Times.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Could ancient humans really have built the pyramids without extraterrestrial help? Or do such questions reveal more about modern anxieties than the past itself?

The idea that aliens assisted the builders of ancient monuments was promoted by the Swiss author Erich von Däniken in his bestselling book Chariot of the Gods — published in 1968. Von Däniken died in January 2026, but his vision of ancient astronauts still captivates millions.

The author had pointed to ancient structures such as the pyramids, along with enigmatic ancient artifacts, as supposed evidence that beings from beyond Earth shaped the civilizations of the past.

Though these ideas have been repeatedly debunked, television shows such as the History Channel's Ancient Aliens continue to air similar narratives.

Erich von Däniken's theories emerged at a distinct historical moment. They crystallized during the cold war, amid fears of nuclear annihilation, the space race and rapid technological change.

As humans prepared to leave Earth, while simultaneously confronting their own destructive power, the idea of ancient astronauts offered both cosmic reassurance and existential drama. The past became a stage for modern hopes and anxieties.

The reason some people feel able to believe in completely unfounded theories relates to the nature of archaeology itself. The discipline works with fragmentary evidence, layered deposits, and interpretations that rarely yield simple conclusions. Sites such as Giza in Egypt, Göbekli Tepe (a Neolithic settlement in modern Turkey known for its monumental pillars decorated with sculptural reliefs), and Troy — also in Turkey — are not unsolved enigmas but the result of decades of systematic excavation and analysis.

At Giza, archaeologists have uncovered planned worker settlements, bakeries and organized food supply systems, demonstrating how thousands of laborers could construct the pyramids over decades.

Göbekli Tepe shows that its monumental stone pillars were erected by hunter-gatherer communities millennia before the invention of writing — not through alien intervention, but through coordinated labor and ritual innovation. At Troy, successive settlement layers reveal centuries of rebuilding, adaptation and regional exchange rather than a sudden technological anomaly.

Archaeological conclusions are cautious, probabilistic and grounded in material evidence. To outsiders, however, caution can resemble hesitation. Pseudoscience fills that perceived gap with spectacle: aliens built the pyramids; mysterious forces raised Göbekli Tepe; forgotten super-technologies shaped Troy’s walls. Stripped of context, evidence becomes entertainment. Complexity is flattened into insinuation.

A typical "ancient aliens" argument illustrates the pattern: the pyramids are extraordinarily precise. Precision, the claim goes, requires advanced technology; therefore, humans without modern machines could not have built them.

The reasoning sounds logical — but it rests on a false dilemma. What disappears from view is precisely what archaeology studies: logistics, labor organization, tool assemblages, accumulated craft knowledge — and small imperfections that reveal human hands at work.

The lure of the extraordinary

Such explanations satisfy a deep psychological impulse. Where once religion explained purpose, science explains process. The "ancient astronauts" hypothesis exploits proportionality bias — the intuition that extraordinary achievements must have extraordinary causes.

Just as medieval legends framed the pyramids as protection against cosmic catastrophe, modern narratives cast humanity as part of a grand design guided by superior beings. Archaeological sites become props in a cosmic drama.

Humans cease to be creators; the past becomes extraordinary because it was "helped". The appeal is not confined to fringe audiences. Surveys suggest that many people consider extraterrestrial life possible or even likely.

Many scientists agree that, given the vast scale of the universe, such life is statistically plausible. But plausibility is not proof — and it is certainly not evidence for alien intervention in antiquity.

Distrust amplifies the effect. Universities, museums and academic journals are often portrayed as gatekeepers suppressing inconvenient truths. Scientific refutation becomes evidence of conspiracy.

Academic prose — careful, qualified and precise — struggles to compete with dramatic certainty. Questions such as: “How could humans have built this without modern technology?” already contain the insinuation.

Digital media turbocharge the pattern: visually striking claims circulate faster than methodological explanations. Archaeology emphasizes gradual change and cumulative knowledge; pseudoscience promises revelation.

Pseudoscientific archaeology is not just a set of beliefs — it is a lucrative industry. Books on ancient astronauts sell millions of copies worldwide. Television franchises generate steady revenue, and leading figures attract audiences in the hundreds of thousands online.

By contrast, scholarly work circulates in a radically different economy: monographs are printed in small runs and generate little profit. This is not only a battle of ideas but a battle for attention: spectacle is rewarded more visibly than caution.

Von Däniken's rhetorical genius lay in ambiguity. He rarely made definitive claims, preferring suggestive questions and selective juxtapositions that turned uncertainty into insinuation.

As he once remarked: "Chariots of the Gods was full of speculation — I had 238 question marks. Nobody read the question marks. They said: Mr von Däniken is saying … I did not say — I asked." The strategy is disarmingly simple: frame speculation as inquiry and criticism as misunderstanding.

Reclaiming the story

The popularity of pseudoscience is not simply ignorance. It reflects the difficulty of interpreting fragmentary evidence, a hunger for meaning, declining institutional trust and the dynamics of digital amplification.

Yet dismissal alone is not enough. Archaeology does more than recover artifacts; it constructs narratives about how humans organized labor, shared beliefs and transformed landscapes. Those narratives are shaped by contemporary questions — and acknowledging this strengthens rather than weakens the discipline.

Debunking alien claims matters. But so does telling richer, more compelling stories about how humans shaped their own past. Archaeology shows that uncertainty is intellectual honesty, that incremental knowledge is cumulative achievement, and that context deepens wonder rather than diminishes it.

Monuments, cities, and human creativity are achievements of our own making, not traces of lost cosmic visitors. Through cooperation, experimentation and resilience, humans created the extraordinary — without any extraterrestrial assistance.

Through rigorous scholarship and compelling storytelling, archaeology shows that the extraordinary was never alien. It was always human.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Ancient Egypt quiz: Test your smarts about pyramids, hieroglyphs and King Tut

In a single year, the secretary of Health and Human Services (HHS), Robert F. Kennedy Jr. (RFK Jr.), has done such comprehensive damage to the extraordinarily successful HIV prevention program as to leave the country almost defenseless against a brewing HIV pandemic, right when elimination seemed possible.

These unprecedented actions have stunned and frightened many who work in the field. But I know from past personal experience that strong science promoted by strong advocacy can return us to the path of HIV elimination.

I saw the AIDS epidemic play out firsthand. In my final year of medical school in 1983, I did a month-long practice internship at the San Francisco General Hospital AIDS ward, the first in the country. The cause of acquired immunodeficiency syndrome (AIDS) was unknown. No test or treatment existed, and the modes of transmission were controversial.

Gay men were the primary risk group. The number diagnosed with AIDS was exploding exponentially, and everyone died slow, lingering, excruciating deaths. Patients were blinded and emaciated, vomiting and asphyxiating and covered with sores, often abandoned by neighbors, family and friends out of the terror of contagion.

Stonewall had come and gone, Harvey Milk had been assassinated, and now fundamentalist preachers thundered from the pulpit that AIDS was God's justified vengeance on sinners.

Then there was the soft-spoken, low-expenditure, laissez-faire approach, with the implication that AIDS was nature's way of culling out undesirables.

Soon after my time on the AIDS ward, the cause of AIDS was identified: human immunodeficiency virus (HIV).

Supported by science, AIDS activists refused to accept that HIV was an inevitable death sentence and launched a hard-hitting campaign demanding research on treatments. Within years, there was a proliferating alphabet soup of anti-HIV medications, which ultimately ensured that most of those infected could live near-normal life spans.

Success produced a paradox: Increased years of potential infectivity meant an expanding epidemic. In 2010, I was working for the CDC on HIV prevention in Kenya, with a tiny role in an ongoing giant multi-national study examining whether it was possible to use anti-HIV treatment to stop HIV transmission. In a meeting room in the local public hospital, I was speaking to a group of health care workers who were going to carry out this study and others.

Almost all were women. They were being paid the standard princely salary of about $300 a month. They were our study workers because they came from the community most at risk. One-in-four women in their age group were HIV infected. Access to anti-HIV medication was fiscally and logistically limited. Only a third of those who needed treatment actually received it. That meant an unknown number of the women to whom I was speaking were ultimately going to die the same death as those in the San Francisco AIDS ward. But they went out to the villages and did the hard work to enroll study subjects and bring home the data.

Because of these women and others across the globe, the resulting 2016 scientific publication became one of the most cited and influential studies in medicine. For the first time, it demonstrated that HIV transmission was not inevitable. It could be stopped cold through anti-HIV treatment. Zero transmission — IF appropriate treatment is received.

Fast forward a decade, and RFK Jr., is an HIV skeptic, suggesting that a conspiracy of persons with personal ambitions had diverted attention away from other potential causes of AIDS, such as a "toxin." He's also claimed, without evidence, that anti-HIV medications were based on "phony, crooked" studies that killed people.

In 2025, five of the 11 branches of the CDC's Division of HIV Prevention were abolished and the employees laid off. All the CDC's HIV websites were taken down. After being restored by court order, the web page on treatment now contains the header, "This page does not reflect biological reality and therefore the Administration and this Department rejects it." A similar header appeared on the HIV prevalence page, but some brave CDC soul managed to insert an explanation why the data was frozen in 2023: "the branches that produced HIV incidence estimates... were eliminated." RFK Jr. cancelled $759 million in HIV research grants, and proposed that responsibility for HIV be transferred from the CDC and all other agencies to a new Administration for a Healthy America under his direct control, with a funding reduction of 80%. Pending that reorganization, a half-billion dollars in budget cuts from HIV treatment were put before Congress.

All this came at the moment when the tools to end the HIV epidemic seemed to be in our hands. New cases had been cut by more than 90%, and maternal-to-child transmission had been eliminated completely.

Now, instead of having resources to finish the job, states are implementing or considering a host of expenditure reduction measures: treatment waiting lists, reduced formulary options, work requirements, low income requirements, an end to reimbursement for the lab assays needed to know if the medications were working.

Similar cutbacks are happening globally, as the U.S. withdrew assistance from international HIV prevention. With our domestic defenses being stripped away and an increased threat of foreign exposures, viral spread will obviously accelerate to infect far more than the current 1-in-300 Americans. Those new cases will infect others. Inevitably, HIV will escape from its risk groups to create a generalized pandemic in the U.S.

1983 redux?

Thanks to almost 50 years of hard work by AIDS activists in San Francisco, village health workers in Kenya, laboratorians across the world, along with so many others, the choices now seem clear: With appropriate treatment, we can bring the HIV epidemic to a halt before it becomes a pandemic, allow the infected to live near normal lives, and provide great cost-savings for society. Or, with lack of treatment, we can have uncontrolled transmission, a spreading epidemic that becomes a pandemic, tormented deaths for individuals, and great costs for society.

In this choice, perhaps the term "1983" should take on the same resonance for health that George Orwell once gave the term "1984" for politics. For HIV, do we really want to return to the hopelessness of 1983? Or do we defy inevitability, use strong advocacy backed by strong science to restore our defenses, stop the HIV resurgence before it starts, and put an end to the epidemic before it becomes a pandemic?

Opinion on Live Science gives you insight on the most important issues in science that affect you and the world around you today, written by experts and leading scientists in their field.

Tehran is moving to restrict — or effectively close — the strait of Hormuz to shipping, as part of the latest escalation in the war involving Iran.

Markets have reacted to the global impact of closing this incredibly busy shipping channel, focusing on the risk to oil and gas flows, the prospect of higher crude prices and the inflationary pressures that would follow.

That concern is justified. But it captures only part of the story. A sustained disruption of traffic through Hormuz would not simply constitute an energy crisis. It would also represent a fertilizer shock (where prices go up dramatically and supply goes down) — and, by extension, a direct risk to global food security.

Modern agriculture runs not only on sunlight and soil, but on natural gas. When German chemists Fritz Haber and Carl Bosch developed their nitrogen fixation method in the early 20th century, they did more than just manufacture ammonia at scale.

They launched a global chemical revolution that remains a cornerstone of modern civilization and agriculture. Through this process, methane is transformed into ammonia, and ammonia into nitrogen fertilizers such as urea — the most widely used nitrogen fertilizer. Those fertilizers allow crops to reach the yields on which today's global population depends. Without it, harvests of wheat, maize and rice would fall dramatically.

Around a third of globally traded urea passes through the strait of Hormuz. The Persian Gulf sits at the center of this system for two structural reasons. First, it offers access to some of the world's cheapest natural gas, essential for ammonia production.

Second, over decades, vast capital investments have built ammonia and urea capacity in countries within the region, including Qatar, Saudi Arabia, and the United Arab Emirates. This is aimed at the export market. A significant share of globally traded nitrogen fertilizer — and the liquefied natural gas (LNG) that powers fertilizer plants elsewhere — must therefore travel through the strait of Hormuz. A closure of the strait would threaten not only oil and gas exports but also the physical flow of nitrogen-based fertilizers and what is needed to make them.

The immediate effect would be delays to shipments of ammonia, urea and LNG. They could be stopped completely or become prohibitively expensive through higher freight and insurance costs. But the deeper impact would unfold in the months ahead at farms around the world.

In the northern hemisphere, fertilizer purchases accelerate before planting seasons. A delay of weeks can be disruptive; a disruption of months can make a huge difference. If shipments fail to arrive on time, farmers face difficult choices such as how to pay sharply higher prices, reduce application rates, or alter crop mixes. Because of how crops respond, even modest reductions in nitrogen use can produce disproportionately large declines in yield. That could translate into millions of tons of lost crops. The consequences would ripple through global supply chains into feed markets, livestock production, biofuels and ultimately retail food prices.

Do countries not have their own supplies?

Some countries have supplies of fertilizers, but self-sufficiency is rarer than it appears. India, for instance, relies heavily on LNG imports from the Persian Gulf to run its domestic urea plants. Brazil depends substantially on imported nitrogen and phosphate fertilizers to sustain soybean and maize production.

Even the United States, one of the world’s largest fertilizer producers, imports meaningful volumes of ammonia and urea to help meet regional demand and reduce prices. In sub-Saharan Africa, use of fertilizer is already low. A further rise in prices is likely to reduce use even more, cutting yields and increasing food insecurity.

The system's fragility extends beyond nitrogen. Sulphur — as an essential nutrient for plant growth — is largely a byproduct of oil and gas processing. If energy shipments through Hormuz are disrupted, sulphur output falls alongside fuel exports. So, the shock would not only reduce fertilizer shipments but also restrict ways to produce them elsewhere.

Meanwhile, the production of synthetic nitrogen tightly coupled to energy markets because it is manufactured continuously from natural gas. A disruption in gas supply or ammonia trade immediately constrains global nitrogen availability. Estimates suggest that without synthetic nitrogen, the world could feed only a fraction of its current population. The strait of Hormuz therefore sits at the intersection of energy and food security.

Changing where fertilizer is produced cannot happen overnight. Financing and constructing new ammonia plants takes years. A double-digit contraction in exports from a key region cannot be swiftly offset. In the interim, prices would rise, trade flows would re-route and planting decisions would be made under uncertainty. Food price inflation, historically correlated with social unrest, could intensify.

Central banks, focused primarily on fuel-driven inflation, could underestimate the contribution of fertilizer scarcity to prices overall. Crucially, fertilizer shocks do not register with the same immediacy as oil shocks. Petrol prices change overnight. Crop yields reveal themselves months later. Yet the latter may prove more destabilizing.

Controls and closure of this narrow maritime chokepoint would reshape the cost-of-living well beyond the Persian Gulf.

If the 20th century taught policymakers to fear oil embargoes, the 21st should teach them to fear a fertilizer shock. Energy markets can absorb shocks through reserves and substitution. But the global food system has far thinner buffers. A prolonged disruption at Hormuz would not simply reprice crude; it would test the resilience of the industrial nitrogen cycle on which modern civilization depends.

Oil powers cars. Nitrogen powers crops. If the strait of Hormuz closes, the most consequential price may not be Brent crude but the cost of feeding the world.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Long before dinosaurs roamed the land, Earth looked very different from the planet we know today. Around 500 million years ago, most of Earth's surface was bare rock and dry soil. There were no trees, no grass and no flowers. Life existed almost entirely in the oceans.

Then something amazing happened: Plants began to grow on land.

This moment was one of the most important events in Earth's history because it changed the planet forever. As a geoscientist, I am interested in changes in the diversity of flora and fauna — that's plants and animals — over time.

Predecessors of plants lived in water

The story of plants begins in the water. The earliest plantlike organisms were simple, tiny green life-forms such as algae. You can still see algae today as seaweed along beaches or as green slime on rocks in ponds.

Algae have lived in Earth's oceans and lakes for over 1 billion years. They can make their own food, using sunlight, water and carbon dioxide to create sugars. This process is called photosynthesis; it releases oxygen — the gas we need to breathe — as a byproduct.

At first, Earth's atmosphere had very little oxygen. Over millions of years, photosynthesizing organisms like algae and some bacteria slowly released oxygen into the air. This change, sometimes called the Great Oxygenation Event, made it possible for larger and more complex life to evolve. Without oxygen-producing organisms, animals, including humans, could never have existed.

Scientists believe the first true plants evolved from green algae around 470 million years ago. These early plants lived in shallow water near shorelines, where conditions changed often. Sometimes they were underwater, and sometimes they were exposed to air. This habitat helped them slowly adapt to life on land.

Getting a foothold on dry land

Moving onto land was not easy. Water plants are supported by water and can absorb nutrients easily, but land plants faced new challenges. How would they avoid drying out? How could they stand upright without floating? How would they get water and nutrients from dry ground?

To survive, early plants evolved important new features. One key adaptation was a waxy coating, called a cuticle, which helped keep water inside the plant. Plants also developed stronger cell walls that allowed them to stand upright against gravity. Simple rootlike structures, called rhizoids, helped anchor plants to the ground and absorb water and minerals from the soil.

The earliest land plants were very small and simple. They looked similar to modern mosses, liverworts and hornworts, which still grow today in damp places like forest floors and stream edges. These plants did not have true roots or stems, and they stayed close to the ground. Fossils of early land plants, such as Cooksonia, date back to about 430 million years ago and show small branching stems only an inch or two tall.

Even though these plants were tiny, they had a huge impact on Earth. As plants spread across land, their roots helped break down rocks into soil, a process called weathering. This created richer soil that could support more life.

Plants also released more oxygen into the atmosphere, improving air quality and helping animals breathe. Plants created new habitats and food sources, allowing insects and other animals to move from water onto land.

Increasing complexity across millions of years

Once plants became established on land, evolution continued. Around 420 million years ago, plants evolved vascular tissue: tiny tubes that transport water and nutrients throughout the plant. This adaptation allowed plants to grow taller and stronger because water could be moved upward from the roots to the leaves. These vascular plants included early relatives of ferns and club mosses.

With vascular tissue, plant life really started to flourish. By about 360 million years ago, vast forests covered much of Earth. Giant ferns and treelike plants, some over 100 feet (30 meters) tall, dominated the landscape. Over time, dead plant material from these forests was buried and compressed, eventually forming coal, which people still use as an energy source today.

Another major step in plant evolution was the development of seeds, around 380 million years ago, found in seed ferns. Other seed plants, such as early conifers — a group that includes modern pine trees — could reproduce without needing water for fertilization. Seeds protected plant embryos and allowed plants to survive harsh conditions like drought or cold.

The most recent major plant evolution happened around 140 million years ago, when flowering plants, what scientists call angiosperms, appeared. Flowers helped plants attract animals like insects and birds, which spread pollen and seeds. Fruits developed to protect seeds and help them travel. Today, flowering plants make up most of the plants we see, including trees, grasses, fruits and vegetables.

The first plants didn't just survive; they transformed Earth. They changed the atmosphere, built soil, and created ecosystems that allowed animals to thrive on land. Thanks to plant evolution, Earth became a green, living planet full of diverse life.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

Fruits and vegetables quiz: Do you know where pumpkins, blueberries and broccoli come from?

In the three decades between 1993 and 2024, measles in the U.S. was relatively rare — a few hundred cases each year, at most. But suddenly, the disease has become so entrenched in American life that it sometimes fails to make headlines when a new outbreak erupts.

As of March 2026, measles has been continuously circulating around the U.S. for more than a year, starting with an outbreak in Texas that lasted from January to August 2025. Before that outbreak was declared over, an outbreak on the Utah and Arizona border began in August and is ongoing. An outbreak in South Carolina began in September, drastically increased in January 2026, and continues.

Thirty states have had measles cases this year; 47 have seen cases since the start of 2025. Health officials across the U.S. have confirmed 1,300 infections already this year as of March 6, putting the country on track to surpass 2025’s numbers, which were the highest in 35 years.

We study outbreak preparedness and response at Brown University's Pandemic Center, and we view the return of measles in the U.S. as a grim signal of what's to come.

Low levels of vaccination across the country mean measles outbreaks will continue to occur, needlessly hospitalizing and killing the unvaccinated. But beyond these harms, the disease's resurgence serves as a serious warning about the country's capacity to manage infectious disease threats of all kinds.

An eliminated disease returns

Measles' return is no mystery: At its root is the falling vaccination rate.

Around 90% of the U.S. population has received the MMR vaccine, which protects against measles, mumps and rubella, and in some regions of the country, the rate is below 60%. Since about 2019-2020, that overall number has dropped below the 95% needed for herd immunity. It is necessary to keep that rate nationally, but maintaining herd immunity at the local level is equally important in order to prevent measles from finding pockets of unvaccinated communities.

Countries that remain free of continuous transmission for 12 months are deemed to have eliminated measles — a designation the U.S. achieved in 2000. The Pan American Health Organization was scheduled to decide in April whether the U.S. should lose that designation, but the organization postponed its meeting until November.

Current trends suggest that both the U.S. and Mexico, which has also been battling the disease, may lose this status — as Canada did in November 2025. All three countries have seen their vaccination rates fall below the 95% threshold, and their outbreaks may share epidemiological links.

A serious, long-term threat to US health

By any measure, the ongoing U.S. measles outbreaks signal that the disease has returned in a way that will have serious adverse health consequences. In 2025, three people died from measles in the U.S. That is more than in any year since the disease’s elimination 25 years ago.

Of the country's 2,283 confirmed measles cases in 2025, 11% were sick enough to be hospitalized. In South Carolina, where most measles cases have been reported in 2026, hospitals don't have to report when patients are admitted due to measles complications, so the actual number of hospitalizations due to measles could be much higher.

People who recover from measles can experience complications such as pneumonia, which can lead to death, or encephalitis, which can later lead to deafness or intellectual disabilities from the brain swelling. The virus can also affect the immune system, making people more susceptible to other infections over the long term, even ones they've had before.

In rare instances — though more likely if someone is infected as a child — measles patients can develop a progressive dementia known as subacute sclerosing panencephalitis, or SSPE, anywhere from two to 10 years after their infection. SSPE always leads to death. This past year, a school-age child in Los Angeles died of this condition years after being infected with measles as an infant, before they were old enough to be vaccinated.

Measles is an economic scourge

Recurring outbreaks of measles in the U.S. will mean high economic costs. Countries have pursued measles elimination in part because of the clear economic benefits of stopping domestic transmission of the virus.

Studies have found that the cost of containing measles outbreaks is often as much as tens of thousands of dollars per case. One outbreak in Washington state in 2018-2019, which involved 72 cases — a small outbreak compared with what states are reporting now — cost US$3.2 million for the public health response, medical expenses and productivity losses. The Common Health Coalition found that a sustained 1% drop in MMR coverage would cost the U.S. billions across health care systems and the economy.

An opening for infectious disease

As concerning as recent outbreaks of measles have been, they herald a larger systemic problem.

How a country controls measles can be viewed as a proxy for how well it would control many other diseases. That's because the steps for stopping the spread are the same: deploying vaccines to prevent infections, detecting and isolating cases when they occur, identifying exposed contacts of infected people and making sure they stay home if they're likely to be contagious, and treating sick people safely.

But besides measles, we've already seen infections that were once controlled, like whooping cough, that rose sharply in 2024 and remained high in 2025 compared with before the COVID-19 pandemic.

That's because controlling the spread of many infectious diseases depends on the public's trust in the basic components of public health. Declining MMR vaccine coverage reveals underlying challenges in public support for vaccines. Public confidence in the current Centers for Disease Control and Prevention is also eroding, according to polling from 2023 to early 2026 by the health policy organization KFF. Less than half of the people polled trust the government even "a fair amount" to provide reliable vaccine information.

These growing cracks in the country's public health armor will complicate efforts to protect Americans from future disease threats — whether an outbreak, a pandemic or a biological attack.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

President Donald Trump directed the Pentagon and other federal agencies to begin releasing government files related to UFOs and unidentified anomalous phenomena — called UAP — in February 2026, following years of pressure from Congress, military whistleblowers and the public.

Congress formally mandated UAP investigations through the National Defense Authorization Act in December 2022. The Pentagon's official UAP investigative body, the All-domain Anomaly Resolution Office, AARO, now carries a caseload exceeding 2,000 reports dating back to 1945. Defense Secretary Pete Hegseth confirmed this figure earlier this year.

The cases were submitted by military personnel, pilots and government employees describing aerial objects that could not be explained as known aircraft, drones or weather phenomena. Governments in Japan, France, Brazil and Canada also have their own formal UAP investigation programs.

Yet modern research universities remain almost entirely absent from this conversation. No major university has established a dedicated UAP research center. No federal science agency offers competitive grants for UAP inquiry. No doctoral programs train researchers in UAP methodology. The gap between what governments openly acknowledge and what universities are willing to study is, at this point, difficult to explain on purely intellectual grounds.

I have navigated this gap while conducting my own UAP research. My work developing the temporal aerospace correlation tool, a standardized framework for correlating civilian UAP sighting reports with documented rocket launch activity from Cape Canaveral, is currently under peer review at Limina: The Journal of UAP Studies.

Designing that framework meant making methodological decisions without community standards, without institutional funding and without the professional infrastructure many researchers in established fields take for granted. What is missing is not interest or data — it is the shared scaffolding that turns isolated curiosity into cumulative science.

Stigma is measurable

The most rigorous evidence for the gap between faculty interest in UAP and faculty willingness to study it comes from peer-reviewed studies by Marissa Yingling, Charlton Yingling and Bethany Bell, published in the scholarly journal Humanities and Social Sciences Communications.

Across 14 disciplines at 144 major U.S. research universities, 1,460 faculty responded to their 2023 national survey. Most surveyed believed UAP research was important. Curiosity outweighed skepticism in every discipline that was part of the study. Nearly one-fifth had personally observed something aerial they could not identify. Yet fewer than 1% had ever conducted UAP-related research.

The gap was not explained by intellectual dismissal, but it was in part explained by fear. Researchers were not primarily deterred by intellectual skepticism because they doubted the topic's merits. Instead, they feared they might lose funding, face ridicule from colleagues or find their careers quietly derailed. Faculty reported being told to "be careful."

A 2024 follow-up study found that roughly 28% said they might vote against a colleague's tenure case for conducting UAP research, even when they personally believed the topic warranted study.

Historian and philosopher of science Thomas Kuhn argued that scientific communities suppress anomalous questions not because those questions are unanswerable, but because they fall outside the boundaries the community has collectively decided are worth investigating.

Sociologist Thomas Gieryn called this suppression "boundary work," referring to the active process by which scientists police what counts as legitimate science.

For UAP researchers, the data and tools to study the phenomenon exist. What may not exist is social permission to use them without professional consequence.

Creating an academic discipline

Academic disciplines do not emerge spontaneously. They require dedicated journals, agreed-upon methods, graduate programs and professional societies.

The history of cognitive neuroscience demonstrates how disciplines emerge. Before the 1980s, researchers at the intersection of neuroscience and cognitive psychology faced resistance from both parent disciplines.

These fields achieved mainstream acceptance only after targeted funding from the Alfred P. Sloan Foundation, new brain-imaging tools and the gradual formation of academic programs that created career pathways for researchers. Researchers at the nexus of these fields did not wait for central questions to be resolved. They built infrastructure, and the infrastructure made progress possible.

UAP studies as a discipline is developing some of these elements, but largely outside universities. The Society for UAP Studies, a nonprofit of scholars and researchers, operates Limina as a double-blind, peer-reviewed journal and has convened international symposia drawing researchers from physics, philosophy of science and the social sciences. But a nonprofit scholarly society without tenured faculty does not constitute a discipline.

To turn UAP studies into a recognized academic field would require three things.

First, funding. The Yingling studies found that competitive research grants would do more to unlock faculty participation than any other single factor. Without grants, researchers cannot hire students to assist them, maintain instruments or sustain the multiyear projects that produce meaningful results.

Second, shared methodological standards — these would entail agreed-upon procedures for collecting, recording and evaluating UAP reports — would mean findings from one research group can be compared and built upon by others.

Third, institutions could publicly affirm that they will evaluate appropriately rigorous UAP scholarship on its scientific merits during tenure reviews. Several universities have already done this for gun violence research and psychedelic-assisted therapy studies.

These are not isolated examples. Research into near-death experiences and adverse childhood experiences followed similar trajectories, moving from being a professional liability to mainstream legitimacy after the removal of institutional barriers.

The international comparison

This gap in UAP scholarship is unique to the United States. France's GEIPAN, a dedicated investigation unit within its national space agency, has operated since 1977. It has publicly archived approximately 5,300 French UAP cases, of which about 2% to 3% remain unexplained after rigorous analysis.

In 2020, Japan formalized UAP reporting protocols for its Self-Defense Forces, the branch of the Japanese military responsible for national defense. By June 2024, more than 80 lawmakers had formed a parliamentary UAP investigation group that by May 2025 had formally proposed a dedicated UAP research office to the defense minister. Canada launched its own multiagency UAP investigation survey in 2023.

None of these actions has produced a corresponding response from American research universities. Universities provide independent, peer-reviewed analyses that government programs structurally cannot.

The University of Würzburg in Germany became the first Western university to officially recognize UAP as a legitimate object of academic research in 2022, when it formally added UAP investigation to its research canon. Researchers at Stockholm University and the Nordic Institute for Theoretical Physics in Sweden have been actively publishing peer-reviewed UAP research since 2017, most recently in Scientific Reports in October 2025.

Congress has passed legislation, the Pentagon is reporting on its investigations, and the president has directed federal agencies to begin releasing records. So the question no longer is whether governments take UAP seriously — it is whether universities will follow, and which ones will get there first.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.

The war in Iran has dominated headlines with reports of airstrikes and escalating military activity. But beyond the immediate devastation, the conflict has also illuminated a quieter and rapidly growing danger: the vulnerability of ships, and the people who operate them, to disruption of their navigation systems.

Modern shipping depends heavily on GPS satellite navigation. When those signals are disrupted or manipulated, ships can suddenly appear to their navigators and to other ships to be somewhere they are not. In some cases, vessels have been shown jumping across maps, drifting miles inland or appearing to circle in impossible patterns. The risk is even higher in war zones, where ships could be misdirected into harm's way.

As a cybersecurity researcher studying critical infrastructure and maritime systems, I investigate how digital threats affect ships and the people who operate them.

To understand the threat from GPS disruptions, it helps to first understand how GPS works. GPS systems determine location using signals from satellites orbiting Earth. A receiver calculates its position by measuring how long those signals take to arrive. Because those signals are extremely weak by the time they reach Earth, they are relatively easy to disrupt.

GPS jamming and spoofing

In GPS jamming, an attacker blocks the real satellite signals by overwhelming them with electromagnetic noise so receivers cannot detect them. When this happens, navigation systems lose their position. On a phone, it might look like the map freezing or jumping erratically.

GPS spoofing is more sophisticated. Instead of blocking signals, an attacker transmits fake satellite signals designed to mimic the real ones. The receiver accepts these signals and gives a false location. Imagine driving north while your navigation system suddenly insists you are traveling south. The receiver is not malfunctioning; it has simply been tricked.

For mariners at sea, spoofing can have serious consequences. In the open ocean, there are few landmarks to verify a ship’s position if GPS behaves strangely. Nearshore, the margin for error disappears: Water depths change quickly and hazards are everywhere, especially in narrow routes like the Strait of Hormuz near Iran, where reports indicate that GPS spoofing has been happening since the outbreak of the war. Because ships are large and slow to maneuver, even small navigation errors can lead to groundings or collisions.

Red Sea grounding

One example came in May 2025. While transiting the Red Sea, the container ship MSC Antonia began showing positions far from its true location. To navigators onboard, this looked like they had jumped hundreds of miles south on the map and started moving in a new direction. This caused the crew to become disoriented, and the ship eventually ran aground. The grounding caused millions of dollars in damage and required a salvage operation that lasted over five weeks.

Incidents like the MSC Antonia are not isolated. Vessel-tracking data has revealed clusters of ships suddenly appearing in impossible locations, sometimes far inland or moving in perfect circles. These anomalies are increasingly linked to GPS spoofing in regions experiencing geopolitical conflict.

But GPS interference is only one type of cyber threat facing ships. Industry reports have documented ransomware attacks on shipping companies, supply chain compromises and increasing concern about the security of onboard control systems, including engines, propulsion and navigation equipment. As ships become more connected through satellite internet systems and remote monitoring tools, the number of potential entry points for cyberattacks is growing.

Military vessels often address these risks through stricter network segregation and regular training exercises such as "mission control" drills, which simulate operating with compromised communications or navigation systems. Some cybersecurity experts argue that similar practices could help commercial shipping improve its resilience, although smaller crews and limited resources make adopting military-style procedures more difficult.

Mariners' experiences

Much of the public discussion around maritime cybersecurity focuses on technical vulnerabilities in ship systems. But an equally important piece of the puzzle is the people who must interpret and respond to these technologies when something goes wrong.

In recent research, my colleagues and I interviewed professional mariners about their experiences with cyber incidents and their preparedness to respond to them. The interviews included navigation officers, engineers and other crew members responsible for ship systems. What emerged was a consistent picture: Cyber threats are increasingly occurring at sea, but crews are not well prepared to deal with them.

Many mariners told us that their cybersecurity training focused almost entirely on email phishing and USB drives. That kind of training may make sense in an office, but it does little to prepare crews for cyber incidents on a ship, where navigation and control systems can be the primary targets. As a result, many mariners lack clear guidance on how cyberattacks might affect the equipment they rely on every day.

This becomes a problem when ship systems begin behaving strangely. Mariners described GPS showing incorrect positions or temporarily losing signal. It can be difficult to tell whether these incidents are equipment failures or signs of cyber interference.

Even when mariners suspect something may be wrong, many ships lack clear procedures for responding to cyber incidents. Participants frequently described situations where they would have to improvise if navigation or other digital systems behaved unexpectedly. Unlike equipment failures, which have established checklists and procedures, cyber incidents often fall into a gray area where responsibility and response plans are unclear.

Another challenge is the gradual disappearance of traditional navigation practices. For centuries, mariners relied on paper charts and celestial navigation to determine their position. Today, most commercial vessels rely almost entirely on electronic systems.

Many mariners noted that paper charts are not available onboard, and celestial navigation is rarely practiced. If GPS or electronic navigation systems fail, crews have limited ways to independently verify their position. One mariner bluntly described the risk to us: "If you don't have charts and you're being spoofed, you're a little screwed."

Increasing connectivity, increasing risk

At the same time, ships are becoming more connected. Modern vessels increasingly rely on satellite internet systems like Starlink and remote monitoring tools to manage operations and communicate with shore.

While these technologies improve efficiency, they also expand the vulnerability of ship systems. Connectivity that allows crews to send emails or access the internet can also provide pathways for cyber threats to reach onboard systems.

As GPS spoofing becomes more common in regions experiencing geopolitical conflict, the challenges mariners described in our research are becoming harder to ignore. The oceans may seem vast and empty, but the digital signals that guide modern ships travel through crowded and contested space.

When those signals are manipulated, the consequences do not stay confined to military systems. They reach the commercial vessels that carry most of the world’s goods and the crews responsible for navigating them safely.

This edited article is republished from The Conversation under a Creative Commons license. Read the original article.