A Pew Research senior data scientist analyzed 500,000 English-language webpages from the past five years with an AI detection tool to estimate how many were likely written or edited by AI: Of all the pages in this sample, 10% show significant signs of AI authorship... If we filter old webpages out of our samples and look at only the pages published after the release of ChatGPT, the trend is even more pronounced. In the July 2026 snapshot, signs of AI authorship can be found in over one-third of pages published after ChatGPT was released. This is in line with other studies that have shown that large shares of recently published pages on the internet were likely written or substantially edited by AI. AI-authored text is not evenly spread across the web. When ChatGPT was first released, the kinds of linguistic patterns that can signal AI authorship appeared at similar rates across the main top-level web domains (.com, .org, .edu and .gov). But in samples from 2026, around one-in-ten pages with a .com domain show signs of AI authorship — about double the share on .org domains (4.6%), and 10 times the rate on .edu or .gov domains (both around 1%). They even identified specific ways online text has changed, "comparing the internet of today to a snapshot from 2023." Em dashes appear twice as often Oxford commas increased 63%. Words used more frequently by AI (like "delve," "interplay" or "testament") have more than doubled in usage. "Negative parallelism" comparisons ("it's not just X, it's Y") have nearly tripled.

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Slashdot reader fjo3 shared this article from Wired: [Flock] has told the public for years that its technology "cannot recognize, identify, or track individuals." It has now built a system that does both, an artificial intelligence tool for police that can identify drivers and track vehicles by their patterns of movement alone, WIRED has learned... Because the system also reaches police case files, 911 dispatch logs, and commercial identity records, those plates can be turned into names, home addresses, and relatives. It can search for people in an area drawn on a map based on nothing more than a physical description... The code describes 45 tools at the AI's disposal, giving it access to plate scans and camera metadata, arrest records, case files, dispatch logs, ballistics results, and commercial databases that contain Social Security numbers, dates of birth, phone numbers, email addresses, relatives and associates. Flock says it is testing the product with a small group of law enforcement partners and describes it as still in development, with capabilities that may not reflect what it eventually sells. It arrives as the company faces bipartisan political pressure, a growing record of officers caught misusing its platform, and a wave of vandalism that has left cameras sawed off and lenses painted over in cities across the country... An officer no longer needs a plate, a name, or a crime to begin: They supply a place, a stretch of time, and a pattern of behavior, and the system is designed to hand back the people who fit... One prompt Flock preloaded into the system reads: "Find me witnesses based on vehicles most seen in [neighborhood] during [last 14 days] during [daily timeframe] *(will not include whitelisted vehicles)." An officer would fill in the blanks and submit it. The output is a list of plates, which other tools in the product then convert into names and home addresses. Another prompt instructs the system to list everyone arrested more than twice in two years for "any offense," exempting only narcotics arrests, and then says to map where those people live, retrieve the calls for service at their homes, and "do a workup on the top three individuals." The prompt begins with everyone in the area who has an arrest record and ends with dossiers on three of them, chosen by the software. A "workup," in Flock's terminology, is a one-command background check. It starts with a name and a date of birth and returns what the department's records and commercial data hold: vehicles, prior listings as a suspect, and, on a second screen, relatives, phone numbers, and online accounts. Wired shares this reaction from a law professor at George Washington University. "It is clear Flock has aspirations far beyond ALPRs to become a digital platform for policing,"

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Long-time Slashdot reader AmiMoJo shared this report from the Guardian: Children's lungs grew bigger and stronger after the most polluting vehicles were restricted from entering London, a study has found. Examinations of London schoolchildren before and after the introduction of the city's ultra-low emission zone found a restoration of lung capacity that had been stunted by exposure to pollution... "Traffic pollution in cities damages children's health and development," said Chris Griffiths, a professor of primary care at the University of Oxford and Queen Mary University of London, and the study's joint senior author. "We provide the strongest evidence yet on how these harms can be prevented. Ambitious clean-air zones should be considered a priority for cities globally with traffic-related air pollution." Air pollution from traffic has stunted the development of children's lungs in London for decades. Previous research found that by the age of eight or nine, children from the most polluted areas had 5-10% less lung capacity than their peers elsewhere. That impairment, which scientists said was the result of exposure to nitrogen dioxide, put them at increased risk as adults of developing respiratory diseases, such as asthma and chronic obstructive pulmonary disease, cardiovascular and metabolic disease, and premature death.

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An anonymous reader quotes a report from The Economist: Students and school children are increasingly using artificial intelligence. A survey last year by Chegg, an ed-tech firm, found that 80% of rich-world undergraduates used it in their studies. More recent polls put the figure at 94% in Britain and 93% in Germany. Such widespread adoption has fueled concerns about the impact the technology might be having on learning. Teachers report marking identikit essays that they suspect are churned out by ChatGPT. Yet firm evidence on AI's educational effects has been lacking. David Stromberg of Stockholm University and Victor Lei and Wu Yanhui of the University of Hong Kong set out to fill the gap. They tracked 27,000 pupils aged 12-18 in China, where AI adoption has been fast. Around 80% reported using models such as Doubao and DeepSeek; the other 20% formed the control group. The results are eye-opening. After six months, pupils using AI saw their average homework score rise by 18% across all subjects. The time they took to complete each assignment fell from an average of 64 minutes to 45. But come exam time, the same students scored 20% below their classmates who had not called on AI's help. Homework scores once predicted exam performance; now those who score highest are, perversely, more likely to do worse in exams. The takeaway: "AI can boost learning productivity, but only for those who use the technology intelligently," reports The Economist. "Students must resist the temptation to reach for an AI-generated answer before thinking things through for themselves."

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An anonymous reader quotes a report from RathBiotaClan: Millions of people finish short video after short video every day; a new brain-scan study shows that the very act of finishing a clip they like temporarily quiets the brain regions that normally help them stay focused and weigh longer-term goals. When people watch a short video they enjoy enough to finish, two brain regions involved in cognitive control show significant deactivation. That is the central finding of a new study from Zhejiang University, published in NeuroImagein January 2026. Using functional MRI alongside proton magnetic resonance spectroscopy (H-MRS), the research team examined 56 young adults while they freely watched short video clips inside an MRI scanner. Both the dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (dlPFC) showed reduced activity specifically when participants watched clips they liked enough to view to completion. Cognitive control helps people balance immediate pleasures against longer-term goals, and impairments in this system are linked to conditions such as depression, anxiety, ADHD, and addiction. Short-video platforms present rapid, algorithmically curated streams that are built for continuous, low-effort consumption. Prior behavioral research has tied both internet addiction and smartphone addiction to weaker self-control, and separate neuroimaging work has documented disruptions to reward and cognitive-control circuits in people with behavioral addictions. Despite this, few studies had directly tested whether the act of watching entertaining short videos itself suppresses the brain's cognitive control regions. The Zhejiang University team set out to answer that question, along with a second one: what neurochemical factors might explain why this suppression varies from person to person?

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Elon Musk’s talk about maintaining a million-strong AI data center satellite megaconstellation may not exactly be practical or economical, but it might be unique. It’s about the closest we’ve come to confronting a scheme that would export a considerable amount of valuable materials into space. Humans aren’t doing a great job of material sustainability, but normally we’re talking about stuff escaping a recycling pipeline rather than escaping Earth’s gravitational pull.

The commercial space sector likes talking about the allure of mining asteroids for precious metals to bring back to Earth. Under what circumstances are we going to be willing to do that in reverse? Starlink alone has doubled the mass of objects in low-Earth orbit, and this orbital data center constellation would dwarf that—and dispose of at least some satellites by pushing them away from Earth.

Given the roughly five-year expected lifetime for data center GPUs, about 200,000 of the 1 million proposed SpaceX AI1 satellites would be decommissioned each year. Based on their May 29 FCC filing, about 40,000 would definitely deorbit and burn up in the atmosphere. (Those materials would largely be dispersed throughout the atmosphere, turning a resource into a diffuse contaminant that slowly settles over the globe. One related issue: the aluminum would cause an unknown amount of ozone depletion over a period of decades.) Some or all of the remaining 160,000 satellites would be moved outward into a distant “disposal” orbit, instead. Either way, they're lost from a "material life cycle" point of view.

Without full, detailed specifications for these satellites, there’s no way to properly tally the amount of material we’re talking about. Focusing on just the GPUs themselves—ignoring solar panels, cooling systems, and the rest of the server and networking devices—can at least provide a starting point.

Musk has described these satellites as using a modified Nvidia Vera Rubin NVL72 rack, which contains 72 GPUs. Though it references a slightly older card, a May study on the material footprint of LLMs provided a full chemical analysis of an A100, covering 32 elements. The massive air-cooled heatsink on that card accounted for 88 percent of its mass, which we’ll simply have to exclude, since the satellite will obviously require another type of cooling that has not been defined.

But using the extremely conservative assumption that each AI1 satellite was simply composed of 72 naked A100 GPUs taped together, we can estimate the material exported to space (or vaporized so thoroughly that it might as well have been) each year.

That includes 1,000 tons of copper, 170 kilograms of gold, almost 2 tons of silver, over 20 tons each of bismuth and titanium, over 2 tons of palladium, and 76 kilograms of thallium.

Some of these elements are, unsurprisingly, rounding errors compared to the amount we mine each year. But that’s around 1 percent of global annual palladium and thallium—a remarkable amount to eject into space.

Earth’s neighborhood inconvenience store

Another way to think about this is to calculate the size of asteroid you would have to mine to recover the amounts of these elements being lost. As a 2023 study notes, there are only a few elements that can be found at a higher concentration in asteroids compared to ores on Earth, like the platinum group metals.

Using average chemistry and densities for a couple different types of asteroids—common CM-group carbonaceous chondrites and rarer iron-rich M-type asteroids—some of the elements lost could be found in modestly sized bodies. The platinum, for example, equates to the contents of an asteroid 16 to 43 meters in diameter. The 180 kilograms of cobalt could be recovered from an asteroid about 3 to 6 meters across.

But it would take a 140–190-meter asteroid to collect that much copper, something in the 225–300-meter range for an equivalent amount of silver and barium, and something like a 530-meter asteroid for an equivalent amount of tin.

Again, this would have to be repeated annually to balance the losses from the satellite constellation.

Most of these elements are too low in value to be proposed targets for asteroid mining, but it has been suggested that spacecraft materials like aluminum and titanium might someday be mined in space for use in space. SpaceX suggested a variant of this in an SEC filing: “We intend to establish lunar‑based manufacturing capabilities, including factories to produce large‑scale AI compute satellites[…] We expect to use raw materials from the Moon to construct most of the mass of the satellites and ship chips and other lower mass elements from Earth.”

It’s technically possible to mine aluminum and titanium on the Moon. It doesn’t necessarily follow that it’s cheaper to manufacture satellites on the Moon just because it would reduce the weight launched from Earth’s surface. (Of course, you’d first have to launch an entire moonbase and mining operation and satellite factory up there…)

There are a number of questions about all this that one would not have to answer if one were building servers on Earth, deploying them in data centers inside humble buildings, and responsibly processing e-waste for recycling in a few years when they die of email-summary-related causes. (Or even better, pushing some equipment to the secondary market if it has useful life left.) In addition to the cost of putting something in orbit, there is a cost to not getting it back.

Will there someday be an environmental review for space projects that includes an evaluation of the mass of materials it proposes to remove from the Earth system? The legal framework for extracting minerals from space has been much discussed—but congested orbits full of junk (or junk reentering the atmosphere) may not be the only space disposal concern on the horizon if projects of this size are ever seriously pursued.

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