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Even if Kosmyna's glasses aren't for sale, similar technology is on the market. In 2023, Apple patented an AirPods prototype equipped with similar sensors, which would allow the device to monitor brain activity and other so-called biosignals. Last month, Meta unveiled a pair of new smart glasses and a "neural band," which lets users text and surf the web with small gestures alone. Overseas, China is fast-tracking development of the technology for medical and consumer use, and B.C.I.s are among the priorities of its new five-year plan for economic development.

"What's coming is A.I. and neurotechnology integrated with our everyday devices," said Nita Farahany, a professor of law and philosophy at Duke University who studies emerging technologies. "Basically, what we are looking at is brain-to-A.I. direct interactions. These things are going to be ubiquitous. It could amount to your sense of self being essentially overwritten."

To prevent this kind of mind-meddling, several nations and states have already passed neural privacy laws. In 2021, Chile amended its constitution to include explicit protections for "neurorights"; Spain adopted a nonbinding list of "digital rights" that protects individual identity, freedom and dignity from neurotechnologies. In 2023, European nations signed the Léon Declaration on neurotechnology, which prioritizes a "rights oriented" approach to the sector. The legislatures of Mexico, Brazil and Argentina have debated similar measures. California, Colorado, Montana and Connecticut have each passed laws to protect neural data.

The federal government has started taking an interest, too. In September, three senators introduced the Management of Individuals' Neural Data (MIND) Act, which would direct the Federal Trade Commission to examine how neural data should be defined and protected. The Uniform Law Commission, a nonprofit that authors model legislation, has convened lawyers, philosophers and scientists who are working on developing a standard law on mental privacy that states could choose to adopt.

Without regulations governing the collection of neural data and the commercialization of B.C.I.s, there is the real possibility that we might find ourselves becoming even more beholden to our devices and their creators than we all already are. In clinical trials, patients have sometimes been left in the lurch; some have had to have their B.C.I.s surgically explanted because funding for their trial ran out.

And the possibility that therapeutic neurotechnologies could one day be weaponized for political purposes looms heavily over the field. Musk, for example, has expressed a desire to "destroy the woke mind virus." As Quinn Slobodian and Ben Tarnoff argue in a forthcoming book, it does not require a great logical leap to suspect that he sees Neuralink as part of a way to do so.

In the 1920s, the German psychiatrist Hans Berger took the first EEG measurements, celebrating the fact that he could detect brain waves "from the unscathed skull." In the 1940s and '50s, scientists experimented with the use of electrodes to alleviate tremors and epilepsy. The Spanish neurophysiologist José Delgado made headlines in 1965, after he used implanted electrodes to stop a charging bull in its tracks; he bragged that he could "play" the minds of monkeys and cats like "electronic toys."

In a 1970 interview with The New York Times, Delgado prophesied that we would soon be able to alter our own "mental functions" as a result of genetic and neuroscientific advances. "The question is what sort of humans would we like, ideally, to construct?" he asked. The notion that a human being could be "constructed" had been troubling philosophers, scientists and writers since at least the late 18th century, when scientists first manipulated electric currents inside animal bodies. The language of electrification quickly seeped out of science and into politics: The historian Samantha Wesner has shown that in France, Jacobin revolutionaries spoke of "electrifying" people to recruit them to their cause and writers toyed with the possibility that political sentiment could be electrically controlled.

Two centuries later, when Delgado and his colleagues showed that it had become technically possible to use electricity to alter the workings of the animal mind, this too was accompanied by an explosion of political concern about the relation between the citizen and the state. Because the thinking subject is by definition a political subject — "the very presence of mind is a political presence," argues Danielle Carr, a historian of neuroscience who researches the political and cultural history of B.C.I.s and related technologies — the potential to alter the human brain was also understood as a threat to liberal politics itself.

In the U.S., where the Cold War fueled anxiety about potential brainwashing technologies, Delgado's work was at first approached with wonder and confusion, but it soon fell under increasing suspicion. In 1953, the director of the C.I.A., Allen Dulles, warned that the Soviet government was conducting a form of "brain warfare" to control minds. In a forthcoming book, Carr traces how the liberal doctrine of universal human rights and freedoms, including the freedom of thought, was positioned as a protective umbrella against communist mind-meddling, co-opting pre-existing struggles against psychiatric experimentation. While the United States warned of brain warfare abroad, it also worked to deploy it at home. Dulles authorized the creation of the C.I.A.'s clandestine MK-Ultra program, which for 20 years conducted psychiatric and mind-control experiments, often on unwitting and incarcerated subjects, until it was abruptly shut down in 1973.

Around this time, the University of California, Los Angeles, sought to create a Center for the Study and Reduction of Violence leading to widespread speculation that the center would screen people in prisons and mental hospitals for indications of aggression and then subject them to brain surgery. An outcry, led in part by the Black Panthers, shut down funding for the initiative. These developments raised public awareness of neural technologies and contributed to the elevation of laws and rights as a stopgap against their worst uses. "We believe that mind control and behavior manipulation are contrary to the ideas laid down in the Bill of Rights and the American Constitution," the Republican lawmaker Steven Symms argued in a 1974 speech. Over the next decades, the development of neurotechnology drastically slowed. By the 1990s, the end of the Cold War dispelled concerns about communist mind-meddling, and the political climate was ripe for reconsideration of the promises and perils of neurotech. In 2013, President Barack Obama created the Brain Research Through Advancing Innovative Neurotechnologies (BRAIN) program, which poured hundreds of millions of dollars into neuroscience. In 2019, the Pentagon's Defense Advanced Research Projects Agency announced that it was funding several teams working to develop nonsurgical neurotechnologies that could, for example, allow service members to control "swarms of unmanned aerial vehicles" with their minds. As experimentation progressed, so did the medical and therapeutic uses of B.C.I.s. In 2004, Matthew Nagle, a tetraplegic, became the first human to be implanted with a sophisticated B.C.I. For individuals who cannot move or speak — those who are living with degenerative disease or paralysis, for example — advances in neural implants have been transformative.

Earlier this year, Bradford Smith, who lives with A.L.S. and was the third person to receive a Neuralink implant, used the A.I. chatbot Grok to draft his X posts. "Neuralink does not read my deepest thoughts or words I think about," Smith explains in an A.I.-generated video about his experience. "It just reads how I want to move and moves the cursor where I want." Because he received the implant as part of a clinical trial, Smith's neural data is protected by HIPAA rules governing private health information. But for mass-market consumer devices — like EEG headbands and glasses, for example — that can be used to enhance cognition, focus and productivity rather than simply restore brain functions that have been compromised — there are very few data protections. "The conflation of consumer and medical devices, and the lack of a consistent definition of neural data itself, adds to the confusion about what is at stake," said Leigh Hochberg, a neurointensive care physician, neuroscientist and director of BrainGate clinical trials. "It's a good societal conversation to have, to reflect on what we individually believe should remain private."

In 2017, driven by a sense of responsibility and terror about the implications of his own research, Rafael Yuste, a neuroscientist at Columbia University, convened scientists, philosophers, engineers and clinicians to create a set of ethical guidelines for the development of neurotechnologies.

One of the group's primary recommendations was that neurorights protecting individual identity, agency and privacy, as well as equal access and protection from bias, should be recognized as basic human rights and protected under the law. Yuste worked with the lawyer Jared Genser to create the Neurorights Foundation in 2021. Together, they surveyed 30 consumer neurotech companies and found that all but one had "no meaningful limitations" to retrieving or selling user neural data. There is consensus that some regulation is necessary given the risks of companies and governments having unfettered access to neural data, and that existing human rights already offer a small degree of protection. But neuroscientists, philosophers, developers and patients disagree about what kinds of regulations should be in place, and about how neurorights should be translated into written laws.

"If we keep inventing new rights, there is a risk that we won't know where one ends and the other begins," said Andrea Lavazza, an ethicist and a philosopher at Pegaso University in Italy who supports the creation of new rights. The United Nations, UNESCO and the World Economic Forum have each convened groups to investigate the implications of neurotechnologies on human rights; dozens of guidance documents on the ethics of the field have been published.

One of the fundamental purposes of law, at least in the United States, is to protect the individual from unwarranted interference. If neurotechnologies have the potential to decode or even change patterns of thought and action, advocates believe that law has the distinct capacity to try to restrain its reach into the innermost chambers of the mind. And while freedom of thought, conscience, opinion, expression and privacy are all recognized as basic human rights in international law, some philosophers and lawyers argue that these fundamental freedoms need to be updated and reinterpreted if they have any hope of protecting individuals against interference from neural devices, because they were conceived when the technology was only a distant dream. Farahany, the law and philosophy professor at Duke, argues that we need to recognize a fundamental right to "cognitive liberty," which scholars have defined as "the right and freedom to control one's own consciousness and electrochemical thought process" — to protect our minds. For Farahany, this kind of liberty "is a precondition to any other concept of liberty, in that, if the very scaffolding of thought itself is manipulated, undermined, interfered with, then any other way in which you would exercise your liberties is meaningless, because you are no longer a self-determined human at that point."

To call for the recognition of a new fundamental right, or even for the enhancement of existing human rights is, at the moment, a countercultural move. Over the past several years, human rights and the international laws designed to protect them have been gravely weakened, while technologies that underlie surveillance capitalism have grown only more widespread. We already live in a world awash with personal data, including sensitive financial and biological information. We leave behind reams of revealing data wherever we go, in both the physical and digital worlds. Our computer cameras are powerful enough to capture our heart rates and make medical diagnoses. Adding neural data on top of this might not constitute such an immense shift. Or it might change everything, offering external actors a portal into our most intimate — and often unarticulated — thoughts and desires. The emergence of B.C.I.s during the mid-20th century was greeted and ultimately torpedoed by Cold War liberalism — Dulles, the C.I.A. director, warned that mind-control techniques could thwart the American project of "spreading the gospel of freedom." Today, we lack a corresponding language with which to push back against the data economy's expanding reach into our minds. In a world where everything can be reduced to data to be bought and sold, where privacy regulations offer only a modicum of protection and where both domestic and international law have been weakened, there are few tools to shield our innermost selves from financialization.

In this sense, the debate over neurorights is a kind of last-ditch effort to ensure that the hard-won protections of the past century carry over into this one — to try to prevent the freedom of thought, conscience and opinion, for example, from being effectively suppressed by the increasingly algorithmic experience of everyday life. How much privacy might we, as a society, be willing to trade in exchange for augmented cognition? "In three years, we will have large-scale models of neural data that companies could put on a device or stream to the cloud, to try to make predictions," said Mackenzie Mathis, a neuroscientist at the Swiss Federal Institute of Technology, Lausanne. How those kinds of data transfers should be regulated, she said, is an urgent question. "We are changing people, just like social media, or large-language models changed people." Under these conditions, the challenge of ensuring that individuals retain the ability to manage access to their innermost selves, however defined, becomes all the more acute. "Our mental life is the core of our self, and we used to be sure that no one could break this barrier," said Lavazza. The collapse of that surety could be an invitation to dread a future in which the unrestricted use of these technologies will have destroyed society as we know it. Or it could be an occasion to rethink the politics that got us here in the first place.

Original Submission

Oddly, tameness has also long been associated with traits such as a shorter face, a smaller head, floppy ears and white patches on fur—a pattern that Charles Darwin noted in the 1800s. The occurrence of these characteristics is known as domestication syndrome, but scientists didn't have a comprehensive theory to explain how the traits were connected until 2014. That's when a team of evolutionary biologists noticed that many of the physical traits that co-occur with domestication trace back to an important group of cells during embryonic development called neural crest cells. In early development, these form along an organism's back and migrate to different parts of the body, where they become important for the development of different types of cells. The biologists hypothesized that mutations that hamper the proliferation and development of neural crest cells could later result in a shorter muzzle, a lack of cartilage in the ears, a loss of pigmentation in the coat and a dampened fear response—leading to a better chance of survival in proximity to humans.

Lesch says the neural crest cells are the most salient hypothesis scientists have to explain domestication syndrome right now, but they are still gathering and evaluating evidence for or against it. One piece of the puzzle would be seeing if domestication syndrome was observable in real time with wild animals. For the new study, she and 16 graduate and undergraduate students gathered nearly 20,000 photographs of raccoons across the contiguous U.S. from the community science platform iNaturalist. The team found that raccoons in urban environments had a snout that was 3.5 percent shorter than that of their rural cousins.

Journal Reference: Apostolov, A., Bradley, A., Dreher, S. et al. Tracking domestication signals across populations of North American raccoons (Procyon lotor) via citizen science-driven image repositories. Front Zool 22, 28 (2025). https://doi.org/10.1186/s12983-025-00583-1

Original Submission

As the data pool expands, DHS plans to hold onto the data until an immigrant who has requested benefits or otherwise engaged with DHS agencies is either granted citizenship or removed.
[...]
DHS said it "recognizes" that its sweeping data collection plans that remove age restrictions don't conform with Department of Justice policies. But the agency claimed there was no conflict since "DHS regulatory provisions control all DHS biometrics collections" and "DHS is not authorized to operate or collect biometrics under DOJ authorities."
[...]
Currently, DHS is seeking public comments on the rule change, which can be submitted over the next 60 days ahead of a deadline on January 2, 2026. The agency suggests it "welcomes" comments, particularly on the types of biometric data DHS wants to collect, including concerns about the "reliability of technology."
[...]
However, DHS claims that's now appropriate, including in cases where children were trafficked or are seeking benefits under the Violence Against Women Act and, therefore, are expected to prove "good moral character."

"Generally, DHS plans to use the biometric information collected from children for identity management in the immigration lifecycle only, but will retain the authority for other uses in its discretion, such as background checks and for law enforcement purposes," DHS's proposal said.

The changes will also help protect kids from removals, DHS claimed, by making it easier for an ICE attorney to complete required "identity, law enforcement, or security investigations or examinations."
[...]
It's possible that some DHS agencies may establish an age threshold for some data collection, the rule change noted.

A day after the rule change was proposed, 42 comments have been submitted. Most were critical, but as Lynch warned, speaking out seemed risky, with many choosing to anonymously criticize the initiative as violating people's civil rights and making the US appear more authoritarian.

One anonymous user cited guidance from the ACLU and the Electronic Privacy Information Center, while warning that "what starts as a 'biometrics update' could turn into widespread privacy erosion for immigrants and citizens alike."
[...]
"You pitch it as a tool against child trafficking, which is a real issue, but does swabbing a newborn really help, or does it just create a lifelong digital profile starting at day one?" the commenter asked. "Accuracy for growing kids is questionable, and the [ACLU] has pointed out how this disproportionately burdens families. Imagine the hassle for parents—it's not protection; it's preemptively treating every child like a data point in a government file."

Original Submission

Tilley previously made headlines in 2018 when he located a satellite that NASA had lost contact with in 2005. For his new discovery, Tilley published data and a technical paper describing the "strong wideband S-band emissions," and his work was featured by NPR on October 17.

Tilley's technical paper said emissions were detected from 170 satellites out of the 193 known Starshield satellites. Emissions have since been detected from one more satellite, making it 171 out of 193, he told Ars. "The apparent downlink use of an uplink-allocated band, if confirmed by authorities, warrants prompt technical and regulatory review to assess interference risk and ensure compliance" with ITU regulations, Tilley's paper said.

Tilley said he uses a mix of omnidirectional antennas and dish antennas at his home to receive signals, along with "software-defined radios and quite a bit of proprietary software I've written or open source software that I use for analysis work." The signals did not stop when the paper was published. Tilley said the emissions are powerful enough to be received by "relatively small ground stations."

Tilley's paper said that Starshield satellites emit signals with a width of 9 MHz and signal-to-noise (SNR) ratios of 10 to 15 decibels. "A 10 dB SNR means the received signal power is ten times greater than the noise power in the same bandwidth," while "20 dB means one hundred times," Tilley told Ars.

Other Starshield signals that were 4 or 5 MHz wide "have been observed to change frequency from day to day with SNR exceeding 20dB," his paper said. "Also observed from time to time are other weaker wide signals from 2025–2110 MHz what may be artifacts or actual intentional emissions."

The 2025–2110 MHz band is used by NASA for science missions and by other countries for similar missions, Tilley noted. "Any other radio activity that's occurring on this band is intentionally limited to avoid causing disruption to its primary purpose," he said.

The band is used for some fully terrestrial, non-space purposes. Mobile service is allowed in 2025–2110 MHz, but ITU rules say that "administrations shall not introduce high-density mobile systems" in these frequencies. The band is also licensed in the US for non-federal terrestrial services, including the Broadcast Auxiliary Service, Cable Television Relay Service, and Local Television Transmission Service.

While Earth-based systems using the band, such as TV links from mobile studios, have legal protection against interference, Tilley noted that "they normally use highly directional and local signals to link a field crew with a studio... they're not aimed into space but at a terrestrial target with a very directional antenna." A trade group representing the US broadcast industry told Ars that it hasn't observed any interference from Starshield satellites.

[...] While Tilley doesn't know exactly what the emissions are for, his paper said the "signal characteristics—strong, coherent, and highly predictable carriers from a large constellation—create the technical conditions under which opportunistic or deliberate PNT exploitation could occur."

PNT refers to Positioning, Navigation, and Timing (PNT) applications. "While it is not suggested that the system was designed for that role, the combination of wideband data channels and persistent carrier tones in a globally distributed or even regionally operated network represents a practical foundation for such use, either by friendly forces in contested environments or by third parties seeking situational awareness," the paper said.

Much more information in the linked source.

Original Submission

We Did the Math on AI's Energy Footprint. Here's the Story You Haven't Heard.

upstart writes:

We did the math on AI's energy footprint. Here's the story you haven't heard.:

[...] Now that we have an estimate of the total energy required to run an AI model to produce text, images, and videos, we can work out what that means in terms of emissions that cause climate change.

First, a data center humming away isn't necessarily a bad thing. If all data centers were hooked up to solar panels and ran only when the sun was shining, the world would be talking a lot less about AI's energy consumption. That's not the case. Most electrical grids around the world are still heavily reliant on fossil fuels. So electricity use comes with a climate toll attached.

"AI data centers need constant power, 24-7, 365 days a year," says Rahul Mewawalla, the CEO of Mawson Infrastructure Group, which builds and maintains high-energy data centers that support AI.

That means data centers can't rely on intermittent technologies like wind and solar power, and on average, they tend to use dirtier electricity. One preprint study from Harvard's T.H. Chan School of Public Health found that the carbon intensity of electricity used by data centers was 48% higher than the US average. Part of the reason is that data centers currently happen to be clustered in places that have dirtier grids on average, like the coal-heavy grid in the mid-Atlantic region that includes Virginia, West Virginia, and Pennsylvania. They also run constantly, including when cleaner sources may not be available.

Data centers can't rely on intermittent technologies like wind and solar power, and on average, they tend to use dirtier electricity.

Tech companies like Meta, Amazon, and Google have responded to this fossil fuel issue by announcing goals to use more nuclear power. Those three have joined a pledge to triple the world's nuclear capacity by 2050. But today, nuclear energy only accounts for 20% of electricity supply in the US, and powers a fraction of AI data centers' operations—natural gas accounts for more than half of electricity generated in Virginia, which has more data centers than any other US state, for example. What's more, new nuclear operations will take years, perhaps decades, to materialize.

In 2024, fossil fuels including natural gas and coal made up just under 60% of electricity supply in the US. Nuclear accounted for about 20%, and a mix of renewables accounted for most of the remaining 20%.

Gaps in power supply, combined with the rush to build data centers to power AI, often mean shortsighted energy plans. In April, Elon Musk's X supercomputing center near Memphis was found, via satellite imagery, to be using dozens of methane gas generators that the Southern Environmental Law Center alleges are not approved by energy regulators to supplement grid power and are violating the Clean Air Act.

The key metric used to quantify the emissions from these data centers is called the carbon intensity: how many grams of carbon dioxide emissions are produced for each kilowatt-hour of electricity consumed. Nailing down the carbon intensity of a given grid requires understanding the emissions produced by each individual power plant in operation, along with the amount of energy each is contributing to the grid at any given time. Utilities, government agencies, and researchers use estimates of average emissions, as well as real-time measurements, to track pollution from power plants.

This intensity varies widely across regions. The US grid is fragmented, and the mixes of coal, gas, renewables, or nuclear vary widely. California's grid is far cleaner than West Virginia's, for example.

Time of day matters too. For instance, data from April 2024 shows that California's grid can swing from under 70 grams per kilowatt-hour in the afternoon when there's a lot of solar power available to over 300 grams per kilowatt-hour in the middle of the night.

This variability means that the same activity may have very different climate impacts, depending on your location and the time you make a request. Take that charity marathon runner, for example. The text, image, and video responses they requested add up to 2.9 kilowatt-hours of electricity. In California, generating that amount of electricity would produce about 650 grams of carbon dioxide pollution on average. But generating that electricity in West Virginia might inflate the total to more than 1,150 grams.

What we've seen so far is that the energy required to respond to a query can be relatively small, but it can vary a lot, depending on the type of query and the model being used. The emissions associated with that given amount of electricity will also depend on where and when a query is handled. But what does this all add up to?

ChatGPT is now estimated to be the fifth-most visited website in the world, just after Instagram and ahead of X. In December, OpenAI said that ChatGPT receives 1 billion messages every day, and after the company launched a new image generator in March, it said that people were using it to generate 78 million images per day, from Studio Ghibli–style portraits to pictures of themselves as Barbie dolls.

Given the direction AI is headed—more personalized, able to reason and solve complex problems on our behalf, and everywhere we look—it's likely that our AI footprint today is the smallest it will ever be.

One can do some very rough math to estimate the energy impact. In February the AI research firm Epoch AI published an estimate of how much energy is used for a single ChatGPT query—an estimate that, as discussed, makes lots of assumptions that can't be verified. Still, they calculated about 0.3 watt-hours, or 1,080 joules, per message. This falls in between our estimates for the smallest and largest Meta Llama models (and experts we consulted say that if anything, the real number is likely higher, not lower).

One billion of these every day for a year would mean over 109 gigawatt-hours of electricity, enough to power 10,400 US homes for a year. If we add images and imagine that generating each one requires as much energy as it does with our high-quality image models, it'd mean an additional 35 gigawatt-hours, enough to power another 3,300 homes for a year. This is on top of the energy demands of OpenAI's other products, like video generators, and that for all the other AI companies and startups.

But here's the problem: These estimates don't capture the near future of how we'll use AI. In that future, we won't simply ping AI models with a question or two throughout the day, or have them generate a photo. Instead, leading labs are racing us toward a world where AI "agents" perform tasks for us without our supervising their every move. We will speak to models in voice mode, chat with companions for 2 hours a day, and point our phone cameras at our surroundings in video mode. We will give complex tasks to so-called "reasoning models" that work through tasks logically but have been found to require 43 times more energy for simple problems, or "deep research" models that spend hours creating reports for us. We will have AI models that are "personalized" by training on our data and preferences.

This future is around the corner: OpenAI will reportedly offer agents for $20,000 per month and will use reasoning capabilities in all of its models moving forward, and DeepSeek catapulted "chain of thought" reasoning into the mainstream with a model that often generates nine pages of text for each response. AI models are being added to everything from customer service phone lines to doctor's offices, rapidly increasing AI's share of national energy consumption.

"The precious few numbers that we have may shed a tiny sliver of light on where we stand right now, but all bets are off in the coming years," says Luccioni.

Every researcher we spoke to said that we cannot understand the energy demands of this future by simply extrapolating from the energy used in AI queries today. And indeed, the moves by leading AI companies to fire up nuclear power plants and create data centers of unprecedented scale suggest that their vision for the future would consume far more energy than even a large number of these individual queries.

"The precious few numbers that we have may shed a tiny sliver of light on where we stand right now, but all bets are off in the coming years," says Luccioni. "Generative AI tools are getting practically shoved down our throats and it's getting harder and harder to opt out, or to make informed choices when it comes to energy and climate."

To understand how much power this AI revolution will need, and where it will come from, we have to read between the lines.

See also:

• Power Hungry

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