May 17 2025
Access to experimental medical treatments is expanding across the US

A couple of weeks ago I was in Washington, DC, for a gathering of scientists, policymakers, and longevity enthusiasts. They had come together to discuss ways to speed along the development of drugs and other treatments that might extend the human lifespan.

One approach that came up was to simply make experimental drugs more easily accessible. Let people try drugs that might help them live longer, the argument went. Some groups have been pushing bills to do just that in Montana, a state whose constitution explicitly values personal liberty.

A couple of years ago, a longevity lobbying group helped develop a bill that expanded on the state’s existing Right to Try law, which allowed seriously ill people to apply for access to experimental drugs (that is, drugs that have not been approved by drug regulators). The expansion, which was passed in 2023, opened access for people who are not seriously ill. 

Over the last few months, the group has been pushing further—for a new bill that sets out exactly how clinics can sell experimental, unproven treatments in the state to anyone who wants them. At the end of the second day of the event, the man next to me looked at his phone. “It just passed,” he told me. (The lobbying group has since announced that the state’s governor Greg Gianforte has signed the bill into law, but when I called his office, Gianforte’s staff said they could not legally tell me whether or not he has.)

The passing of the bill could make Montana something of a US hub for experimental treatments. But it represents a wider trend: the creep of Right to Try across the US. And a potentially dangerous departure from evidence-based medicine.

In the US, drugs must be tested in human volunteers before they can be approved and sold. Early-stage clinical trials are small and check for safety. Later trials test both the safety and efficacy of a new drug.

The system is designed to keep people safe and to prevent manufacturers from selling ineffective or dangerous products. It’s meant to protect us from snake oil.

But people who are seriously ill and who have exhausted all other treatment options are often desperate to try experimental drugs. They might see it as a last hope. Sometimes they can volunteer for clinical trials, but time, distance, and eligibility can rule out that option.

Since the 1980s, seriously or terminally ill people who cannot take part in a trial for some reason can apply for access to experimental treatments through a “compassionate use” program run by the US Food and Drug Administration (FDA). The FDA authorizes almost all of the compassionate use requests it receives (although manufacturers don’t always agree to provide their drug for various reasons).

But that wasn’t enough for the Goldwater Institute, a libertarian organization that in 2014 drafted a model Right to Try law for people who are terminally ill. Versions of this draft have since been passed into law in 41 US states, and the US has had a federal Right to Try law since 2018. These laws generally allow people who are seriously ill to apply for access to drugs that have only been through the very first stages of clinical trials, provided they give informed consent.

Some have argued that these laws have been driven by a dislike of both drug regulation and the FDA. After all, they are designed to achieve the same result as the compassionate use program. The only difference is that they bypass the FDA.

Either way, it’s worth noting just how early-stage these treatments are. A drug that has been through phase I trials might have been tested in just 20 healthy people. Yes, these trials are designed to test the safety of a drug, but they are never conclusive. At that point in a drug’s development, no one can know how a sick person—who is likely to be taking other medicines— will react to it.

Now these Right to Try laws are being expanded even more. The Montana bill, which goes the furthest, will enable people who are not seriously ill to access unproven treatments, and other states have been making moves in the same direction.

Just this week, Georgia’s governor signed into law the Hope for Georgia Patients Act, which allows people with life-threatening illnesses to access personalized treatments, those that are “unique to and produced exclusively for an individual patient based on his or her own genetic profile.” Similar laws, known as “Right to Try 2.0,”  have been passed in other states, too, including Arizona, Mississippi, and North Carolina.

And last year, Utah passed a law that allows health care providers (including chiropractors, podiatrists, midwives, and naturopaths) to deliver unapproved placental stem cell therapies. These treatments involve cells collected from placentas, which are thought to hold promise for tissue regeneration. But they haven’t been through human trials. They can cost tens of thousands of dollars, and their effects are unknown. Utah’s law was described as a “pretty blatant broadbrush challenge to the FDA’s authority” by an attorney who specializes in FDA law. And it’s one that could put patients at risk.

Laws like these spark a lot of very sensitive debates. Some argue that it’s a question of medical autonomy, and that people should have the right to choose what they put in their own bodies.

And many argue there’s a cost-benefit calculation to be made. A seriously ill person potentially has more to gain and less to lose from trying an experimental drug, compared to someone who is in good health.

But everyone needs to be protected from ineffective drugs. Most ethicists think it’s unethical to sell a treatment when you have no idea if it will work, and that argument has been supported by numerous US court decisions over the years. 

There could be a financial incentive for doctors to recommend an experimental drug, especially when they are granted protections by law. (Right to Try laws tend to protect prescribing doctors from disciplinary action and litigation should something go wrong.)

On top of all this, many ethicists are also concerned that the FDA’s drug approval process itself has been on a downward slide over the last decade or so. An increasing number of drug approvals are fast-tracked based on weak evidence, they argue.

Scientists and ethicists on both sides of the debate are now waiting to see what unfolds under the new US administration.  

In the meantime, a quote from Diana Zuckerman, president of the nonprofit National Center for Health Research, comes to mind: “Sometimes hope helps people do better,” she told me a couple of years ago. “But in medicine, isn’t it better to have hope based on evidence rather than hope based on hype?”

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

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May 16 2025
How US research cuts are threatening crucial climate data

Over the last few months, and especially the last few weeks, there’s been an explosion of news about proposed budget cuts to science in the US. One trend I’ve noticed: Researchers and civil servants are sounding the alarm that those cuts mean we might lose key data that helps us understand our world and how climate change is affecting it.

My colleague James Temple has a new story out today about researchers who are attempting to measure the temperature of mountain snowpack across the western US. Snow that melts in the spring is a major water source across the region, and monitoring the temperature far below the top layer of snow could help scientists more accurately predict how fast water will flow down the mountains, allowing farmers, businesses, and residents to plan accordingly.

But long-running government programs that monitor the snowpack across the West are among those being threatened by cuts across the US federal government. Also potentially in trouble: carbon dioxide measurements in Hawaii, hurricane forecasting tools, and a database that tracks the economic impact of natural disasters. It’s all got me thinking: What do we lose when data is in danger?

Take for example the work at Mauna Loa Observatory, which sits on the northern side of the world’s largest active volcano. In this Hawaii facility, researchers have been measuring the concentration of carbon dioxide in the atmosphere since 1958.

The resulting graph, called the Keeling Curve (after Charles David Keeling, the scientist who kicked off the effort) is a pillar of climate research. It shows that carbon dioxide, the main greenhouse gas warming the planet, has increased in the atmosphere from around 313 parts per million in 1958 to over 420 parts per million today.

Proposed cuts to the National Oceanic and Atmospheric Administration (NOAA) jeopardize the Keeling Curve’s future. As Ralph Keeling (current steward of the curve and Keeling’s son) put it in a new piece for Wired, “If successful, this loss will be a nightmare scenario for climate science, not just in the United States, but the world.”

This story has echoes across the climate world right now. A lab at Princeton that produces what some consider the top-of-the-line climate models used to make hurricane forecasts could be in trouble because of NOAA budget cuts. And last week, NOAA announced it would no longer track the economic impact of the biggest natural disasters in the US.

Some of the largest-scale climate efforts will feel the effects of these cuts, and as James’s new story shows, they could also seep into all sorts of specialized fields. Even seemingly niche work can have a huge impact not just on research, but on people.

The frozen reservoir of the Sierra snowpack provides about a third of California’s groundwater, as well as the majority used by towns and cities in northwest Nevada. Researchers there are hoping to help officials better forecast the timing of potential water supplies across the region.

This story brought to mind my visit to El Paso, Texas, a few years ago. I spoke with farmers there who rely on water coming down the Rio Grande, alongside dwindling groundwater, to support their crops. There, water comes down from the mountains in Colorado and New Mexico in the spring and is held in the Elephant Butte Reservoir. One farmer I met showed me pages and pages of notes of reservoir records, which he had meticulously copied by hand. Those crinkled pages were a clear sign: Publicly available data was crucial to his work.

The endeavor of scientific research, particularly when it involves patiently gathering data, isn’t always exciting. Its importance is often overlooked. But as cuts continue, we’re keeping a lookout, because losing data could harm our ability to track, address, and adapt to our changing climate. 

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

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May 16 2025
This baby boy was treated with the first personalized gene-editing drug

Doctors say they constructed a bespoke gene-editing treatment in less than seven months and used it to treat a baby with a deadly metabolic condition.

The rapid-fire attempt to rewrite the child’s DNA marks the first time gene editing has been tailored to treat a single individual, according to a report published in the New England Journal of Medicine.

The baby who was treated, Kyle “KJ” Muldoon Jr., suffers from a rare metabolic condition caused by a particularly unusual gene misspelling.

Researchers say their attempt to correct the error demonstrates the high level of precision new types of gene editors offer. 

“I don’t think I’m exaggerating when I say that this is the future of medicine,” says Kiran Musunuru, an expert in gene editing at the University of Pennsylvania whose team designed the drug. “My hope is that someday no rare disease patients will die prematurely from misspellings in their genes, because we’ll be able to correct them.”

The project also highlights what some experts are calling a growing crisis in gene-editing technology. That’s because even though the technology could cure thousands of genetic conditions, most are so rare that companies could never recoup the costs of developing a treatment for them. 

In KJ’s case, the treatment was programmed to correct a single letter of DNA in his cells.

“In reality, this drug will probably never be used again,” says Rebecca Ahrens-Nicklas, a physician at the Children’s Hospital of Philadelphia who treats metabolic diseases in children and who led the overall effort to treat the child.

That effort involved more than 45 scientists and doctors as well as pro bono assistance from several biotechnology companies. Musunuru says he cannot estimate how much it had cost in time and effort.

Eventually, he says, the cost of custom gene-editing treatments might be similar to that of liver transplants, which is around $800,000, not including lifelong medical care and drugs.

The researchers used a new version of CRISPR technology, called base editing, that can replace a single letter of DNA at a specific location. 

Previous versions of CRISPR have generally been used to delete genes, not rewrite them to restore their function.

The researchers say they were looking for a patient to treat when they learned about KJ. After he was born in August, a doctor noted that the infant was lethargic. Tests found he had a metabolic disorder that leads to the buildup of ammonia, a condition that’s frequently fatal without a liver transplant.

In KJ’s case, gene sequencing showed that the cause was a misspelled letter in the gene CPS1 that stopped it from making a vital enzyme.

The researchers approached KJ’s parents, Nicole and Kyle Muldoon, with the idea of using gene editing to try to correct their baby’s DNA. After they agreed, a race ensued to design the editing drug, test it in animals, and get permission from the US Food and Drug Administration to treat KJ in a one-off experiment.

The team says the boy, who hasn’t turned one yet, received three doses of the gene-editing treatment, of gradually increasing strength. They can’t yet determine exactly how well the gene editor worked because they don’t want to take a liver biopsy, which would be needed to check if KJ’s genes have really been corrected.

But Ahrens-Nicklas says that because the child is “growing and thriving,” she thinks the editing has been at least partly successful and that he may now have “a milder form of this horrific disease.”

“He’s received three doses of the therapy without any complications, and is showing some early signs of benefit,” she says. “It’s really important to say that it’s still very early, so we will need to continue to watch KJ closely to fully understand the full effects of this therapy.”

The case suggests a future in which parents will take sick children to a clinic where their DNA will be sequenced, and then they will rapidly receive individualized treatments. Currently, this would only work for liver diseases, for which it’s easier to deliver gene-editing instructions, but eventually it might also become a possible approach for treating brain diseases and conditions like muscular dystrophy.

The experiment is drawing attention to a gap between what gene editing can do and what treatments are likely to become available to people who need them.

So far, biotechnology companies testing gene editing are working only on fairly common gene conditions, like sickle cell disease, leaving hundreds of ultra-rare conditions aside. One-off treatments, like the one helping KJ, are too expensive to create and get approved without some way to recoup the costs.

The apparent success in treating KJ, however, is making it even more urgent to figure out a way forward. Researchers acknowledge that they don’t yet know how to scale up personalized treatment, although Musunuru says initial steps to standardize the process are underway at his university and in Europe.

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May 15 2025
A US court just put ownership of CRISPR back in play

The CRISPR patents are back in play.

On Monday, the US Court of Appeals for the Federal Circuit said scientists Jennifer Doudna and Emmanuelle Charpentier will get another chance to show they ought to own the key patents on what many consider the defining biotechnology invention of the 21st century.

The pair shared a 2020 Nobel Prize for developing the versatile gene-editing system, which is already being used to treat various genetic disorders, including sickle cell disease. 

But when key US patent rights were granted in 2014 to researcher Feng Zhang of the Broad Institute of MIT and Harvard, the decision set off a bitter dispute in which hundreds of millions of dollars—as well as scientific bragging rights—are at stake.

The new decision is a boost for the Nobelists, who had previously faced a string of demoralizing reversals over the patent rights in both the US and Europe.

“This goes to who was the first to invent, who has priority, and who is entitled to the broadest patents,” says Jacob Sherkow, a law professor at the University of Illinois. 

He says there is now at least a chance that Doudna and Charpentier “could walk away as the clear winner.”

The CRISPR patent battle is among the most byzantine ever, putting the technology alongside the steam engine, the telephone, the lightbulb, and the laser among the most hotly contested inventions in history.

In 2012, Doudna and Charpentier were first to publish a description of a CRISPR gene editor that could be programmed to precisely cut DNA in a test tube. There’s no dispute about that.

However, the patent fight relates to the use of CRISPR to edit inside animal cells—like those of human beings. That’s considered a distinct invention, and one both sides say they were first to come up with that very same year. 

In patent law, this moment is known as conception—the instant a lightbulb appears over an inventor’s head, revealing a definite and workable plan for how an invention is going to function.

In 2022, a specialized body called the Patent Trial and Appeal Board, or PTAB, decided that Doudna and Charpentier hadn’t fully conceived the invention because they initially encountered trouble getting their editor to work in fish and other species. Indeed, they had so much trouble that Zhang scooped them with a 2013 publication demonstrating he could use CRISPR to edit human cells.

The Nobelists appealed the finding, and yesterday the appeals court vacated it, saying the patent board applied the wrong standard and needs to reconsider the case. 

According to the court, Doudna and Charpentier didn’t have to “know their invention would work” to get credit for conceiving it. What could matter more, the court said, is that it actually did work in the end. 

In a statement, the University of California, Berkeley, applauded the call for a do-over.  

“Today’s decision creates an opportunity for the PTAB to reevaluate the evidence under the correct legal standard and confirm what the rest of the world has recognized: that the Doudna and Charpentier team were the first to develop this groundbreaking technology for the world to share,” Jeff Lamken, one of Berkeley’s attorneys, said in the statement.

The Broad Institute posted a statement saying it is “confident” the appeals board “will again confirm Broad’s patents, because the underlying facts have not changed.”

The decision is likely to reopen the investigation into what was written in 13-year-old lab notebooks and whether Zhang based his research, in part, on what he learned from Doudna and Charpentier’s publications. 

The case will now return to the patent board for a further look, although Sherkow says the court finding can also be appealed directly to the US Supreme Court. 

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May 15 2025
Police tech can sidestep facial recognition bans now

Six months ago I attended the largest gathering of chiefs of police in the US to see how they’re using AI. I found some big developments, like officers getting AI to write their police reports. Today, I published a new story that shows just how far AI for police has developed since then. 

It’s about a new method police departments and federal agencies have found to track people: an AI tool that uses attributes like body size, gender, hair color and style, clothing, and accessories instead of faces. It offers a way around laws curbing the use of facial recognition, which are on the rise. 

Advocates from the ACLU, after learning of the tool through MIT Technology Review, said it was the first instance they’d seen of such a tracking system used at scale in the US, and they say it has a high potential for abuse by federal agencies. They say the prospect that AI will enable more powerful surveillance is especially alarming at a time when the Trump administration is pushing for more monitoring of protesters, immigrants, and students. 

I hope you read the full story for the details, and to watch a demo video of how the system works. But first, let’s talk for a moment about what this tells us about the development of police tech and what rules, if any, these departments are subject to in the age of AI.

As I pointed out in my story six months ago, police departments in the US have extraordinary independence. There are more than 18,000 departments in the country, and they generally have lots of discretion over what technology they spend their budgets on. In recent years, that technology has increasingly become AI-centric. 

Companies like Flock and Axon sell suites of sensors—cameras, license plate readers, gunshot detectors, drones—and then offer AI tools to make sense of that ocean of data (at last year’s conference I saw schmoozing between countless AI-for-police startups and the chiefs they sell to on the expo floor). Departments say these technologies save time, ease officer shortages, and help cut down on response times. 

Those sound like fine goals, but this pace of adoption raises an obvious question: Who makes the rules here? When does the use of AI cross over from efficiency into surveillance, and what type of transparency is owed to the public?

In some cases, AI-powered police tech is already driving a wedge between departments and the communities they serve. When the police in Chula Vista, California, were the first in the country to get special waivers from the Federal Aviation Administration to fly their drones farther than normal, they said the drones would be deployed to solve crimes and get people help sooner in emergencies. They’ve had some successes. 

But the department has also been sued by a local media outlet alleging it has reneged on its promise to make drone footage public, and residents have said the drones buzzing overhead feel like an invasion of privacy. An investigation found that these drones were deployed more often in poor neighborhoods, and for minor issues like loud music. 

Jay Stanley, a senior policy analyst at the ACLU, says there’s no overarching federal law that governs how local police departments adopt technologies like the tracking software I wrote about. Departments usually have the leeway to try it first, and see how their communities react after the fact. (Veritone, which makes the tool I wrote about, said they couldn’t name or connect me with departments using it so the details of how it’s being deployed by police are not yet clear). 

Sometimes communities take a firm stand; local laws against police use of facial recognition have been passed around the country. But departments—or the police tech companies they buy from—can find workarounds. Stanley says the new tracking software I wrote about poses lots of the same issues as facial recognition while escaping scrutiny because it doesn’t technically use biometric data.

“The community should be very skeptical of this kind of tech and, at a minimum, ask a lot of questions,” he says. He laid out a road map of what police departments should do before they adopt AI technologies: have hearings with the public, get community permission, and make promises about how the systems will and will not be used. He added that the companies making this tech should also allow it to be tested by independent parties. 

“This is all coming down the pike,” he says—and so quickly that policymakers and the public have little time to keep up. He adds, “Are these powers we want the police—the authorities that serve us—to have, and if so, under what conditions?”

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

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May 15 2025
Why climate researchers are taking the temperature of mountain snow

On a crisp morning in early April, Dan McEvoy and Bjoern Bingham cut clean lines down a wide run at the Heavenly Ski Resort in South Lake Tahoe, then ducked under a rope line cordoning off a patch of untouched snow. 

They side-stepped up a small incline, poled past a row of Jeffrey pines, then dropped their packs. 

The pair of climate researchers from the Desert Research Institute (DRI) in Reno, Nevada, skied down to this research plot in the middle of the resort to test out a new way to take the temperature of the Sierra Nevada snowpack. They were equipped with an experimental infrared device that can take readings as it’s lowered down a hole in the snow to the ground.

The Sierra’s frozen reservoir provides about a third of California’s water and most of what comes out of the faucets, shower heads, and sprinklers in the towns and cities of northwestern Nevada. As it melts through the spring and summer, dam operators, water agencies, and communities have to manage the flow of billions of gallons of runoff, storing up enough to get through the inevitable dry summer months without allowing reservoirs and canals to flood.

The need for better snowpack temperature data has become increasingly critical for predicting when the water will flow down the mountains, as climate change fuels hotter weather, melts snow faster, and drives rapid swings between very wet and very dry periods. 

In the past, it has been arduous work to gather such snowpack observations. Now, a new generation of tools, techniques, and models promises to ease that process, improve water forecasts, and help California and other states safely manage one of their largest sources of water in the face of increasingly severe droughts and flooding.

Observers, however, fear that any such advances could be undercut by the Trump administration’s cutbacks across federal agencies, including the one that oversees federal snowpack monitoring and survey work. That could jeopardize ongoing efforts to produce the water data and forecasts on which Western communities rely.

“If we don’t have those measurements, it’s like driving your car around without a fuel gauge,” says Larry O’Neill, Oregon’s state climatologist. “We won’t know how much water is up in the mountains, and whether there’s enough to last through the summer.”

The birth of snow surveys

The snow survey program in the US was born near Lake Tahoe, the largest alpine lake in North America, around the turn of the 20th century. 

Without any reliable way of knowing how much water would flow down the mountain each spring, lakefront home and business owners, fearing floods, implored dam operators to release water early in the spring. Downstream communities and farmers pushed back, however, demanding that the dam was used to hold onto as much water as possible to avoid shortages later in the year. 

In 1908, James Church, a classics professor at the University of Nevada, Reno, whose passion for hiking around the mountains sparked an interest in the science of snow, invented a device that helped resolve the so-called Lake Tahoe Water Wars: the Mt. Rose snow sampler, named after the peak of a Sierra spur that juts into Nevada.

Professor James E. Church wearing goggles and snowshoes, standing on a snowy hillside
James Church, a professor of classics at the University of Nevada, Reno, became a pioneer in the field of snow surveys.
COURTESY OF UNIVERSITY OF NEVADA, RENO

It’s a simple enough device, with sections of tube that screw together, a sharpened end, and measurement ticks along the side. Snow surveyors measure the depth of the snow by plunging the sampler down to the ground. They then weigh the filled tube on a specialized scale to calculate the water content of the snow. 

Church used the device to take measurements at various points across the range, and calibrated his water forecasts by comparing his readings against the rising and falling levels of Lake Tahoe. 

It worked so well that the US began a federal snow survey program in the mid-1930s, which evolved into the one carried on today by the Department of Agriculture’s Natural Resources Conservation Service (NRCS). Throughout the winter, hundreds of snow surveyors across the American West head up to established locations on snowshoes, backcountry skis, or snowmobiles to deploy their Mt. Rose samplers, which have barely changed over more than a century. 

In the 1960s, the US government also began setting up a network of permanent monitoring sites across the mountains, now known as the SNOTEL network. There are more than 900 stations continuously transmitting readings from across Western states and Alaska. They’re equipped with sensors that measure air temperature, snow depth, and soil moisture, and include pressure-sensitive “snow pillows” that weigh the snow to determine the water content. 

The data from the snow surveys and SNOTEL sites all flows into snow depth and snow water content reports that the NRCS publishes, along with forecasts of the amount of water that will fill the streams and reservoirs through the spring and summer.

Taking the temperature

None of these survey and monitoring programs, however, provide the temperature throughout the snowpack. 

The Sierra Nevada snowpack can reach more than 6 meters (20 feet), and the temperature within it may vary widely, especially toward the top. Readings taken at increments throughout can determine what’s known as the cold content, or the amount of energy required to shift the snowpack to a uniform temperature of 32˚F. 

Knowing the cold content of the snowpack helps researchers understand the conditions under which it will begin to rapidly melt, particularly as it warms up in the spring or after rain falls on top of the snow.

If the temperature of the snow, for example, is close to 32ËšF even at several feet deep, a few warm days could easily set it melting. If, on the other hand, the temperature measurements show a colder profile throughout the middle, the snowpack is more stable and will hold up longer as the weather warms.

a person with raising a snow shovel up at head height
Bjoern Bingham, a research scientist at the Desert Research Institute, digs at snowpit at a research plot within the Heavenly Ski Resort, near South Lake Tahoe, California.
JAMES TEMPLE

The problem is that taking the temperature of the entire snowpack has been, until now, tough and time-consuming work. When researchers do it at all, they mainly do so by digging snow pits down to the ground and then taking readings with probe thermometers along an inside wall.

There have been a variety of efforts to take continuous remote readings from sensors attached to fences, wires, or towers, which the snowpack eventually buries. But the movement and weight of the dense shifting snow tends to break the devices or snap the structures they’re assembled upon.

“They rarely last a season,” McAvoy says.

Anne Heggli, a professor of mountain hydrometeorology at DRI, happened upon the idea of using an infrared device to solve this problem during a tour of the institute’s campus in 2019, when she learned that researchers there were using an infrared meat thermometer to take contactless readings of the snow surface.

In 2021, Heggli began collaborating with RPM Systems, a gadget manufacturing company, to design an infrared device optimized for snowpack field conditions. The resulting snow temperature profiler is skinny enough to fit down a hole dug by snow surveyors and dangles on a cord marked off at 10-centimeter (4-inch) increments.

a researcher stands in a snowy trench taking notes, while a second researcher drops a yellow measure down from the surface level
Bingham and Daniel McEvoy, an associate research professor at the Desert Research Institute, work together to take temperature readings from inside the snowpit as well as from within the hole left behind by a snow sampler.
JAMES TEMPLE

At Heavenly on that April morning, Bingham, a staff scientist at DRI, slowly fed the device down a snow sampler hole, calling out temperature readings at each marking. McEvoy scribbled them down on a worksheet fastened to his clipboard as he used a probe thermometer to take readings of his own from within a snow pit the pair had dug down to the ground.

They were comparing the measurements to assess the reliability of the infrared device in the field, but the eventual aim is to eliminate the need to dig snow pits. The hope is that state and federal surveyors could simply carry along a snow temperature profiler and drop it into the snowpack survey holes they’re creating anyway, to gather regular snowpack temperature readings from across the mountains.

In 2023, the US Bureau of Reclamation, the federal agency that operates many of the nation’s dams, funded a three-year research project to explore the use of the infrared gadgets in determining snowpack temperatures. Through it, the DRI research team has now handed devices out to 20 snow survey teams across California, Colorado, Idaho, Montana, Nevada, and Utah to test their use in the field and supplement the snowpack data they’re collecting.

The Snow Lab

The DRI research project is one piece of a wider effort to obtain snowpack temperature data across the mountains of the West.

By early May, the snow depth had dropped from an April peak of 114 inches to 24 inches (2.9 meters to 0.6 meters) at the UC Berkeley Central Sierra Snow Lab, an aging wooden structure perched in the high mountains northwest of Lake Tahoe.

Megan Mason, a research scientist at the lab, used a backcountry ski shovel to dig out a trio of instruments from what was left of the pitted snowpack behind the building. Each one featured different types of temperature sensors, arrayed along a strong polymer beam meant to hold up under the weight and movement of the Sierra snowpack.  

She was pulling up the devices after running the last set of observations for the season, as part of an effort to develop a resilient system that can survive the winter and transmit hourly temperature readings.

The lab is working on the project, dubbed the California Cold Content Initiative, in collaboration with the state’s Department of Water Resources. California is the only western state that opted to maintain its own snow survey program and run its own permanent monitoring stations, all of which are managed by the water department. 

The plan is to determine which instruments held up and functioned best this winter. Then, they can begin testing the most promising approaches at several additional sites next season. Eventually, the goal is to attach the devices at more than 100 of California’s snow monitoring stations, says Andrew Schwartz, the director of the lab.

The NRCS is conducting a similar research effort at select SNOTEL sites equipped with a beaded temperature cable. One such cable is visible at the Heavenly SNOTEL station, next to where McEvoy and Bingham dug their snow pit, strung vertically between an arm extended from the main tower and the snow-covered ground. 

a gloved hand inserts a probe wire into a hole in the snow
DRI’s Bjoern Bingham feeds the snow temperature profiler, an infrared device, down a hole in the Sierra snowpack.
JAMES TEMPLE

Schwartz said that the different research groups are communicating and collaborating openly on the projects, all of which promise to provide complementary information, expanding the database of snowpack temperature readings across the West.

For decades, agencies and researchers generally produced water forecasts using relatively simple regression models that translated the amount of water in the snowpack into the amount of water that will flow down the mountain, based largely on the historic relationships between those variables. 

But these models are becoming less reliable as climate change alters temperatures, snow levels, melt rates, and evaporation, and otherwise drives alpine weather patterns outside of historic patterns.

“As we have years that scatter further and more frequently from the norm, our models aren’t prepared,” Heggli says.

Plugging direct temperature observations into more sophisticated models that have emerged in recent years, Schwartz says, promises to significantly improve the accuracy of water forecasts. That, in turn, should help communities manage through droughts and prevent dams from overtopping even as climate change fuels alternately wetter, drier, warmer, and weirder weather.

About a quarter of the world’s population relies on water stored in mountain snow and glaciers, and climate change is disrupting the hydrological cycles that sustain these natural frozen reservoirs in many parts of the world. So any advances in observations and modeling could deliver broader global benefits.

Ominous weather

There’s an obvious threat to this progress, though.

Even if these projects work as well as hoped, it’s not clear how widely these tools and techniques will be deployed at a time when the White House is gutting staff across federal agencies, terminating thousands of scientific grants, and striving to eliminate tens of billions of dollars in funding at research departments. 

The Trump administration has fired or put on administrative leave nearly 6,000 employees across the USDA, or 6% of the department’s workforce. Those cutbacks have reached regional NRCS offices, according to reporting by local and trade outlets.

That includes more than half of the roles at the Portland office, according to O’Neill, the state climatologist. Those reductions prompted a bipartisan group of legislators to call on the Secretary of Agriculture to restore the positions, warning the losses could impair water data and analyses that are crucial for the state’s “agriculture, wildland fire, hydropower, timber, and tourism sectors,” as the Statesman Journal reported.

There are more than 80 active SNOTEL stations in Oregon.

The fear is there won’t be enough people left to reach all the sites this summer to replace batteries, solar panels, and drifting or broken sensors, which could quickly undermine the reliability of the data or cut off the flow of information. 

“Staff and budget reductions at NRCS will make it impossible to maintain SNOTEL instruments and conduct routine manual observations, leading to inoperability of the network within a year,” the lawmakers warned.

The USDA and NRCS didn’t respond to inquiries from MIT Technology Review. 

looking down at a researcher standing in a snowy trench with a clipboard of notes
DRI’s Daniel McEvoy scribbles down temperature readings at the Heavenly site.
JAMES TEMPLE

If the federal cutbacks deplete the data coming back from SNOTEL stations or federal snow survey work, the DRI infrared method could at least “still offer a simplistic way of measuring the snowpack temperatures” in places where state and regional agencies continue to carry out surveys, McEvoy says.

But most researchers stress the field needs more surveys, stations, sensors, and readings to understand how the climate and water cycles are changing from month to month and season to season. Heggli stresses that there should be broad bipartisan support for programs that collect snowpack data and provide the water forecasts that farmers and communities rely on. 

“This is how we account for one of, if not the, most valuable resource we have,” she says. “In the West, we go into a seasonal drought every summer; our snowpack is what trickles down and gets us through that drought. We need to know how much we have.”

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May 15 2025
The first US hub for experimental medical treatments is coming

A bill that allows medical clinics to sell unproven treatments has been passed in Montana. 

Under the legislation, doctors can apply for a license to open an experimental treatment clinic and recommend and sell therapies not approved by the Food and Drug Administration (FDA) to their patients. Once it’s signed by the governor, the law will be the most expansive in the country in allowing access to drugs that have not been fully tested. 

The bill allows for any drug produced in the state to be sold in it, providing it has been through phase I clinical trials—the initial, generally small, first-in-human studies that are designed to check that a new treatment is not harmful. These trials do not determine if the drug is effective.

The bill, which was passed by the state legislature on April 29 and is expected to be signed by Governor Greg Gianforte, essentially expands on existing Right to Try legislation in the state. But while that law was originally designed to allow terminally ill people to access experimental drugs, the new bill was drafted and lobbied for by people interested in extending human lifespans—a group of longevity enthusiasts that includes scientists, libertarians, and influencers.  

These longevity enthusiasts are hoping Montana will serve as a test bed for opening up access to experimental drugs. “I see no reason why it couldn’t be adopted by most of the other states,” said Todd White, speaking to an audience of policymakers and others interested in longevity at an event late last month in Washington, DC. White, who helped develop the bill and directs a research organization focused on aging, added that “there are some things that can be done at the federal level to allow Right to Try laws to proliferate more readily.” 

Supporters of the bill say it gives individuals the freedom to make choices about their own bodies. At the same event, bioethicist Jessica Flanigan of the University of Richmond said she was “optimistic” about the measure, because “it’s great any time anybody is trying to give people back their medical autonomy.” 

Ultimately, they hope that the new law will enable people to try unproven drugs that might help them live longer, make it easier for Americans to try experimental treatments without having to travel abroad, and potentially turn Montana into a medical tourism hub.

But ethicists and legal scholars aren’t as optimistic. “I hate it,” bioethicist Alison Bateman-House of New York University says of the bill. She and others are worried about the ethics of promoting and selling unproven treatments—and the risks of harm should something go wrong.

Easy access?

No drugs have been approved to treat human aging. Some in the longevity field believe that regulation has held back the development of such drugs. In the US, federal law requires that drugs be shown to be both safe and effective before they can be sold. That requirement was made law in the 1960s following the thalidomide tragedy, in which women who took the drug for morning sickness had babies with sometimes severe disabilities. Since then, the FDA has been responsible for the approval of new drugs.  

Typically, new drugs are put through a series of human trials. Phase I trials generally involve between 20 and 100 volunteers and are designed to check that the drug is safe for humans. If it is, the drug is then tested in larger groups of hundreds, and then thousands, of volunteers to assess the dose and whether it actually works. Once a drug is approved, people who are prescribed it are monitored for side effects. The entire process is slow, and it can last more than a decade—a particular pain point for people who are acutely aware of their own aging. 

But some exceptions have been made for people who are terminally ill under Right to Try laws. Those laws allow certain individuals to apply for access to experimental treatments that have been through phase I clinical trials but have not received FDA approval.

Montana first passed a Right to Try law in 2015 (a federal law was passed around three years later). Then in 2023, the state expanded the law to include all patients there, not just those with terminal illnesses—meaning that any person in Montana could, in theory, take a drug that had been through only a phase I trial.

At the time, this was cheered by many longevity enthusiasts—some of whom had helped craft the expanded measure.

But practically, the change hasn’t worked out as they envisioned. “There was no licensing, no processing, no registration” for clinics that might want to offer those drugs, says White. “There needed to be another bill that provided regulatory clarity for service providers.” 

So the new legislation addresses “how clinics can set up shop in Montana,” says Dylan Livingston, founder and CEO of the Alliance for Longevity Initiatives, which hosted the DC event. Livingston built A4LI, as it’s known, a few years ago, as a lobbying group for the science of human aging and longevity.

Livingston, who is exploring multiple approaches to improve both funding for scientific research and to change drug regulation, helped develop and push the 2023 bill in Montana with the support of State Senator Kenneth Bogner, he says. “I gave [Bogner] a menu of things that could be done at the state level … and he loved the idea” of turning Montana into a medical tourism hub, he says. 

After all, as things stand, plenty of Americans travel abroad to receive experimental treatments that cannot legally be sold in the US, including expensive, unproven stem cell and gene therapies, says Livingston. 

“If you’re going to go and get an experimental gene therapy, you might as well keep it in the country,” he says. Livingston has suggested that others might be interested in trying a novel drug designed to clear aged “senescent” cells from the body, which is currently entering phase II trials for an eye condition caused by diabetes. “One: let’s keep the money in the country, and two: if I was a millionaire getting an experimental gene therapy, I’d rather be in Montana than Honduras.”

“Los Alamos for longevity”

Honduras, in particular, has become something of a home base for longevity experiments. The island of Roatán is home to the Global Alliance for Regenerative Medicine clinic, which, along with various stem cell products, sells a controversial unproven “anti-aging” gene therapy for around $20,000 to customers including wealthy longevity influencer Bryan Johnson. 

Tech entrepreneur and longevity enthusiast Niklas Anzinger has also founded the city of Infinita in the region’s special economic zone of Próspera, a private city where residents are able to make their own suggestions for medical regulations. It’s the second time he’s built a community there as part of his effort to build a “Los Alamos for longevity” on the island, a place where biotech companies can develop therapies that slow or reverse human aging “at warp speed,” and where individuals are free to take those experimental treatments. (The first community, Vitalia, featured a biohacking lab, but came to an end following a disagreement between the two founders.) 

Anzinger collaborated with White, the longevity enthusiast who spoke at the A4LI event (and is an advisor to Infinita VC, Anzinger’s investment company), to help put together the new Montana bill. “He asked if I would help him try to advance the new bill, so that’s what we did for the last few months,” says White, who trained as an electrical engineer but left his career in telecommunications to work with an organization that uses blockchain to fund research into extending human lifespans. 

“Right to Try has always been this thing [for people] who are terminal[ly ill] and trying a Hail Mary approach to solving these things; now Right to Try laws are being used to allow you to access treatments earlier,” White told the audience at the A4LI event. “Making it so that people can use longevity medicines earlier is, I think, a very important thing.”

The new bill largely sets out the “infrastructure” for clinics that want to sell experimental treatments, says White. It states that clinics will need to have a license, for example, and that this must be renewed on an annual basis. 

“Now somebody who actually wants to deliver drugs under the Right to Try law will be able to do so,” he says. The new legislation also protects prescribing doctors from disciplinary action.

And it sets out requirements for informed consent that go further than those of existing Right to Try laws. Before a person takes an experimental drug under the new law, they will be required to provide a written consent that includes a list of approved alternative drugs and a description of the worst potential outcome.

On the safe side

“In the Montana law, we explicitly enhanced the requirements for informed consent,” Anzinger told an audience at the same A4LI event. This, along with the fact that the treatments will have been through phase I clinical trials, will help to keep people safe, he argued. “We have to treat this with a very large degree of responsibility,” he added.

“We obviously don’t want to be killing people,” says Livingston. 

But he also adds that he, personally, won’t be signing up for any experimental treatments. “I want to be the 10 millionth, or even the 50 millionth, person to get the gene therapy,” he says. “I’m not that adventurous … I’ll let other people go first.”

Others are indeed concerned that, for the “adventurous” people, these experimental treatments won’t necessarily be safe. Phase I trials are typically tiny, and they often involve less than 50 people, all of whom are typically in good health. A trial like that won’t tell you much about side effects that only show up in 5% of people, for example, or about interactions the drug might have with other medicines.

Around 90% of drug candidates in clinical trials fail. And around 17% of drugs fail late-stage clinical trials because of safety concerns. Even those that make it all the way through clinical trials and get approved by the FDA can still end up being withdrawn from the market when rare but serious side effects show up. Between 1992 and 2023, 23 drugs that were given accelerated approval for cancer indications were later withdrawn from the market. And between 1950 and 2013, the reason for the withdrawal of 95 drugs was “death.”

“It’s disturbing that they want to make drugs available after phase I testing,” says Sharona Hoffman, professor of law and bioethics at Case Western Reserve University in Cleveland, Ohio. “This could endanger patients.”

“Famously, the doctor’s first obligation is to first do no harm,” says Bateman-House. “If [a drug] has not been through clinical trials, how do you have any standing on which to think it isn’t going to do any harm?”

But supporters of the bill argue that individuals can make their own decisions about risk. When speaking at the A4LI event, Flanigan introduced herself as a bioethicist before adding “but don’t hold it against me; we’re not all so bad.” She argued that current drug regulations impose a “massive amount of restrictions on your bodily rights and your medical freedom.” Why should public officials be the ones making decisions about what’s safe for people? Individuals, she argued, should be empowered to make those judgments themselves.

Other ethicists counter that this isn’t an issue of people’s rights. There are lots of generally accepted laws about when we can access drugs, says Hoffman; people aren’t allowed to drink and drive because they might kill someone. “So, no, you don’t have a right to ingest everything you want if there are risks associated with it.”

The idea that individuals have a right to access experimental treatments has in fact failed in US courts in the past, says Carl Coleman, a bioethicist and legal scholar at Seton Hall in New Jersey. 

He points to a case from 20 years ago: In the early 2000s, Frank Burroughs founded the Abigail Alliance for Better Access to Developmental Drugs. His daughter, Abigail Burroughs, had head and neck cancer, and she had tried and failed to access experimental drugs. In 2003, about two years after Abigail’s death, the group sued the FDA, arguing that people with terminal cancer have a constitutionally protected right to access experimental, unapproved treatments, once those treatments have been through phase I trials. In 2007, however, a court rejected that argument, determining  that terminally ill individuals do not have a constitutional right to experimental drugs.

Bateman-House also questions a provision in the Montana bill that claims to make treatments more equitable. It states that “experimental treatment centers” should allocate 2% of their net annual profits “to support access to experimental treatments and healthcare for qualifying Montana residents.” Bateman-House says she’s never seen that kind of language in a bill before. It may sound positive, but it could in practice introduce even more risk to the local community. “On the one hand, I like equity,” she says. “On the other hand, I don’t like equity to snake oil.”

After all, the doctors prescribing these drugs won’t know if they will work. It is never ethical to make somebody pay for a treatment when you don’t have any idea whether it will work, Bateman-House adds. “That’s how the US system has been structured: There’s no profit without evidence of safety and efficacy.”

The clinics are coming

Any clinics that offer experimental treatments in Montana will only be allowed to sell drugs that have been made within the state, says Coleman. “Federal law requires any drug that is going to be distributed in interstate commerce to have FDA approval,” he says.

White isn’t too worried about that. Montana already has manufacturing facilities for biotech and pharmaceutical companies, including Pfizer. “That was one of the specific advantages [of focusing] on Montana, because everything can be done in state,” he says. He also believes that the current administration is “predisposed” to change federal laws around interstate drug manufacturing. (FDA commissioner Marty Makary has been a vocal critic of the agency and the pace at which it approves new drugs.)

At any rate, the clinics are coming to Montana, says Livingston. “We have half a dozen that are interested, and maybe two or three that are definitively going to set up shop out there.” He won’t name names, but he says some of the interested clinicians already have clinics in the US, while others are abroad. 

Mac Davis—founder and CEO of Minicircle, the company that developed the controversial “anti-aging” gene therapy—told MIT Technology Review he was “looking into it.”

“I think this can be an opportunity for America and Montana to really kind of corner the market when it comes to medical tourism,” says Livingston. “There is no other place in the world with this sort of regulatory environment.”

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May 15 2025
Google DeepMind’s new AI agent uses large language models to crack real-world problems

Google DeepMind has once again used large language models to discover new solutions to long-standing problems in math and computer science. This time the firm has shown that its approach can not only tackle unsolved theoretical puzzles, but improve a range of important real-world processes as well.

Google DeepMind’s new tool, called AlphaEvolve, uses the Gemini 2.0 family of large language models (LLMs) to produce code for a wide range of different tasks. LLMs are known to be hit and miss at coding. The twist here is that AlphaEvolve scores each of Gemini’s suggestions, throwing out the bad and tweaking the good, in an iterative process, until it has produced the best algorithm it can. In many cases, the results are more efficient or more accurate than the best existing (human-written) solutions.

“You can see it as a sort of super coding agent,” says Pushmeet Kohli, a vice president at Google DeepMind who leads its AI for Science teams. “It doesn’t just propose a piece of code or an edit, it actually produces a result that maybe nobody was aware of.”

In particular, AlphaEvolve came up with a way to improve the software Google uses to allocate jobs to its many millions of servers around the world. Google DeepMind claims the company has been using this new software across all of its data centers for more than a year, freeing up 0.7% of Google’s total computing resources. That might not sound like much, but at Google’s scale it’s huge.

Jakob Moosbauer, a mathematician at the University of Warwick in the UK, is impressed. He says the way AlphaEvolve searches for algorithms that produce specific solutions—rather than searching for the solutions themselves—makes it especially powerful. “It makes the approach applicable to such a wide range of problems,” he says. “AI is becoming a tool that will be essential in mathematics and computer science.”

AlphaEvolve continues a line of work that Google DeepMind has been pursuing for years. Its vision is that AI can help to advance human knowledge across math and science. In 2022, it developed AlphaTensor, a model that found a faster way to solve matrix multiplications—a fundamental problem in computer science—beating a record that had stood for more than 50 years. In 2023, it revealed AlphaDev, which discovered faster ways to perform a number of basic calculations performed by computers trillions of times a day. AlphaTensor and AlphaDev both turn math problems into a kind of game, then search for a winning series of moves.

FunSearch, which arrived in late 2023, swapped out game-playing AI and replaced it with LLMs that can generate code. Because LLMs can carry out a range of tasks, FunSearch can take on a wider variety of problems than its predecessors, which were trained to play just one type of game. The tool was used to crack a famous unsolved problem in pure mathematics.

AlphaEvolve is the next generation of FunSearch. Instead of coming up with short snippets of code to solve a specific problem, as FunSearch did, it can produce programs that are hundreds of lines long. This makes it applicable to a much wider variety of problems.    

In theory, AlphaEvolve could be applied to any problem that can be described in code and that has solutions that can be evaluated by a computer. “Algorithms run the world around us, so the impact of that is huge,” says Matej Balog, a researcher at Google DeepMind who leads the algorithm discovery team.

Survival of the fittest

Here’s how it works: AlphaEvolve can be prompted like any LLM. Give it a description of the problem and any extra hints you want, such as previous solutions, and AlphaEvolve will get Gemini 2.0 Flash (the smallest, fastest version of Google DeepMind’s flagship LLM) to generate multiple blocks of code to solve the problem.

It then takes these candidate solutions, runs them to see how accurate or efficient they are, and scores them according to a range of relevant metrics. Does this code produce the correct result? Does it run faster than previous solutions? And so on.

AlphaEvolve then takes the best of the current batch of solutions and asks Gemini to improve them. Sometimes AlphaEvolve will throw a previous solution back into the mix to prevent Gemini from hitting a dead end.

When it gets stuck, AlphaEvolve can also call on Gemini 2.0 Pro, the most powerful of Google DeepMind’s LLMs. The idea is to generate many solutions with the faster Flash but add solutions from the slower Pro when needed.

These rounds of generation, scoring, and regeneration continue until Gemini fails to come up with anything better than what it already has.

Number games

The team tested AlphaEvolve on a range of different problems. For example, they looked at matrix multiplication again to see how a general-purpose tool like AlphaEvolve compared to the specialized AlphaTensor. Matrices are grids of numbers. Matrix multiplication is a basic computation that underpins many applications, from AI to computer graphics, yet nobody knows the fastest way to do it. “It’s kind of unbelievable that it’s still an open question,” says Balog.

The team gave AlphaEvolve a description of the problem and an example of a standard algorithm for solving it. The tool not only produced new algorithms that could calculate 14 different sizes of matrix faster than any existing approach, it also improved on AlphaTensor’s record-beating result for multipying two four-by-four matrices.

AlphaEvolve scored 16,000 candidates suggested by Gemini to find the winning solution, but that’s still more efficient than AlphaTensor, says Balog. AlphaTensor’s solution also only worked when a matrix was filled with 0s and 1s. AlphaEvolve solves the problem with other numbers too.

“The result on matrix multiplication is very impressive,” says Moosbauer. “This new algorithm has the potential to speed up computations in practice.”

Manuel Kauers, a mathematician at Johannes Kepler University in Linz, Austria, agrees: “The improvement for matrices is likely to have practical relevance.”

By coincidence, Kauers and a colleague have just used a different computational technique to find some of the speedups AlphaEvolve came up with. The pair posted a paper online reporting their results last week.

“It is great to see that we are moving forward with the understanding of matrix multiplication,” says Kauers. “Every technique that helps is a welcome contribution to this effort.”

Real-world problems

Matrix multiplication was just one breakthrough. In total, Google DeepMind tested AlphaEvolve on more than 50 different types of well-known math puzzles, including problems in Fourier analysis (the math behind data compression, essential to applications such as video streaming), the minimum overlap problem (an open problem in number theory proposed by mathematician Paul Erdős in 1955), and kissing numbers (a problem introduced by Isaac Newton that has applications in materials science, chemistry, and cryptography). AlphaEvolve matched the best existing solutions in 75% of cases and found better solutions in 20% of cases.  

Google DeepMind then applied AlphaEvolve to a handful of real-world problems. As well as coming up with a more efficient algorithm for managing computational resources across data centers, the tool found a way to reduce the power consumption of Google’s specialized tensor processing unit chips.

AlphaEvolve even found a way to speed up the training of Gemini itself, by producing a more efficient algorithm for managing a certain type of computation used in the training process.

Google DeepMind plans to continue exploring potential applications of its tool. One limitation is that AlphaEvolve can’t be used for problems with solutions that need to be scored by a person, such as lab experiments that are subject to interpretation.   

Moosbauer also points out that while AlphaEvolve may produce impressive new results across a wide range of problems, it gives little theoretical insight into how it arrived at those solutions. That’s a drawback when it comes to advancing human understanding.  

Even so, tools like AlphaEvolve are set to change the way researchers work. “I don’t think we are finished,” says Kohli. “There is much further that we can go in terms of how powerful this type of approach is.”

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May 13 2025
How a new type of AI is helping police skirt facial recognition bans

Police and federal agencies have found a controversial new way to skirt the growing patchwork of laws that curb how they use facial recognition: an AI model that can track people using attributes like body size, gender, hair color and style, clothing, and accessories. 

The tool, called Track and built by the video analytics company Veritone, is used by 400 customers, including state and local police departments and universities all over the US. It is also expanding federally: US attorneys at the Department of Justice began using Track for criminal investigations last August. Veritone’s broader suite of AI tools, which includes bona fide facial recognition, is also used by the Department of Homeland Security—which houses immigration agencies—and the Department of Defense, according to the company. 

“The whole vision behind Track in the first place,” says Veritone CEO Ryan Steelberg, was “if we’re not allowed to track people’s faces, how do we assist in trying to potentially identify criminals or malicious behavior or activity?” In addition to tracking individuals where facial recognition isn’t legally allowed, Steelberg says, it allows for tracking when faces are obscured or not visible. 

The product has drawn criticism from the American Civil Liberties Union, which—after learning of the tool through MIT Technology Review—said it was the first instance they’d seen of a nonbiometric tracking system used at scale in the US. They warned that it raises many of the same privacy concerns as facial recognition but also introduces new ones at a time when the Trump administration is pushing federal agencies to ramp up monitoring of protesters, immigrants, and students.

Veritone gave us a demonstration of Track in which it analyzed people in footage from different environments, ranging from the January 6 riots to subway stations. You can use it to find people by specifying body size, gender, hair color and style, shoes, clothing, and various accessories. The tool can then assemble timelines, tracking a person across different locations and video feeds. It can be accessed through Amazon and Microsoft cloud platforms.

VERITONE; MIT TECHNOLOGY REVIEW (CAPTIONS)

In an interview, Steelberg said that the number of attributes Track uses to identify people will continue to grow. When asked if Track differentiates on the basis of skin tone, a company spokesperson said it’s one of the attributes the algorithm uses to tell people apart but that the software does not currently allow users to search for people by skin color. Track currently operates only on recorded video, but Steelberg claims the company is less than a year from being able to run it on live video feeds.

Agencies using Track can add footage from police body cameras, drones, public videos on YouTube, or so-called citizen upload footage (from Ring cameras or cell phones, for example) in response to police requests.

“We like to call this our Jason Bourne app,” Steelberg says. He expects the technology to come under scrutiny in court cases but says, “I hope we’re exonerating people as much as we’re helping police find the bad guys.” The public sector currently accounts for only 6% of Veritone’s business (most of its clients are media and entertainment companies), but the company says that’s its fastest-growing market, with clients in places including California, Washington, Colorado, New Jersey, and Illinois. 

That rapid expansion has started to cause alarm in certain quarters. Jay Stanley, a senior policy analyst at the ACLU, wrote in 2019 that artificial intelligence would someday expedite the tedious task of combing through surveillance footage, enabling automated analysis regardless of whether a crime has occurred. Since then, lots of police-tech companies have been building video analytics systems that can, for example, detect when a person enters a certain area. However, Stanley says, Track is the first product he’s seen make broad tracking of particular people technologically feasible at scale.

“This is a potentially authoritarian technology,” he says. “One that gives great powers to the police and the government that will make it easier for them, no doubt, to solve certain crimes, but will also make it easier for them to overuse this technology, and to potentially abuse it.”

Chances of such abusive surveillance, Stanley says, are particularly high right now in the federal agencies where Veritone has customers. The Department of Homeland Security said last month that it will monitor the social media activities of immigrants and use evidence it finds there to deny visas and green cards, and Immigrations and Customs Enforcement has detained activists following pro-Palestinian statements or appearances at protests. 

In an interview, Jon Gacek, general manager of Veritone’s public-sector business, said that Track is a “culling tool” meant to speed up the task of identifying important parts of videos, not a general surveillance tool. Veritone did not specify which groups within the Department of Homeland Security or other federal agencies use Track. The Departments of Defense, Justice, and Homeland Security did not respond to requests for comment.

For police departments, the tool dramatically expands the amount of video that can be used in investigations. Whereas facial recognition requires footage in which faces are clearly visible, Track doesn’t have that limitation. Nathan Wessler, an attorney for the ACLU, says this means police might comb through videos they had no interest in before. 

“It creates a categorically new scale and nature of privacy invasion and potential for abuse that was literally not possible any time before in human history,” Wessler says. “You’re now talking about not speeding up what a cop could do, but creating a capability that no cop ever had before.”

Track’s expansion comes as laws limiting the use of facial recognition have spread, sparked by wrongful arrests in which officers have been overly confident in the judgments of algorithms.  Numerous studies have shown that such algorithms are less accurate with nonwhite faces. Laws in Montana and Maine sharply limit when police can use it—it’s not allowed in real time with live video—while San Francisco and Oakland, California have near-complete bans on facial recognition. Track provides an alternative. 

Though such laws often reference “biometric data,” Wessler says this phrase is far from clearly defined. It generally refers to immutable characteristics like faces, gait and fingerprints rather than things that change, like clothing. But certain attributes, such as body size, blur this distinction. 

Consider also, Wessler says, someone in winter who frequently wears the same boots, coat, and backpack. “Their profile is going to be the same day after day,” Wessler says. “The potential to track somebody over time based on how they’re moving across a whole bunch of different saved video feeds is pretty equivalent to face recognition.”

In other words, Track might provide a way of following someone that raises many of the same concerns as facial recognition, but isn’t subject to laws restricting use of facial recognition because it does not technically involve biometric data. Steelberg said there are several ongoing cases that include video evidence from Track, but that he couldn’t name the cases or comment further. So for now, it’s unclear whether it’s being adopted in jurisdictions where facial recognition is banned. 

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May 10 2025
Did solar power cause Spain’s blackout?

At roughly midday on Monday, April 28, the lights went out in Spain. The grid blackout, which extended into parts of Portugal and France, affected tens of millions of people—flights were grounded, cell networks went down, and businesses closed for the day.

Over a week later, officials still aren’t entirely sure what happened, but some (including the US energy secretary, Chris Wright) have suggested that renewables may have played a role, because just before the outage happened, wind and solar accounted for about 70% of electricity generation. Others, including Spanish government officials, insisted that it’s too early to assign blame.

It’ll take weeks to get the full report, but we do know a few things about what happened. And even as we wait for the bigger picture, there are a few takeaways that could help our future grid.

Let’s start with what we know so far about what happened, according to the Spanish grid operator Red Eléctrica:

  • A disruption in electricity generation took place a little after 12:30 p.m. This may have been a power plant flipping off or some transmission equipment going down.
  • A little over a second later, the grid lost another bit of generation.
  • A few seconds after that, the main interconnector between Spain and southwestern France got disconnected as a result of grid instability.
  • Immediately after, virtually all of Spain’s electricity generation tripped offline.

One of the theories floating around is that things went wrong because the grid diverged from its normal frequency. (All power grids have a set frequency: In Europe the standard is 50 hertz, which means the current switches directions 50 times per second.) The frequency needs to be constant across the grid to keep things running smoothly.

There are signs that the outage could be frequency-related. Some experts pointed out that strange oscillations in the grid frequency occurred shortly before the blackout.

Normally, our grid can handle small problems like an oscillation in frequency or a drop that comes from a power plant going offline. But some of the grid’s ability to stabilize itself is tied up in old ways of generating electricity.

Power plants like those that run on coal and natural gas have massive rotating generators. If there are brief issues on the grid that upset the balance, those physical bits of equipment have inertia: They’ll keep moving at least for a few seconds, providing some time for other power sources to respond and pick up the slack. (I’m simplifying here—for more details I’d highly recommend this report from the National Renewable Energy Laboratory.)

Solar panels don’t have inertia—they rely on inverters to change electricity into a form that’s compatible with the grid and matches its frequency. Generally, these inverters are “grid-following,” meaning if frequency is dropping, they follow that drop.

In the case of the blackout in Spain, it’s possible that having a lot of power on the grid coming from sources without inertia made it more possible for a small problem to become a much bigger one.

Some key questions here are still unanswered. The order matters, for example. During that drop in generation, did wind and solar plants go offline first? Or did everything go down together?

Whether or not solar and wind contributed to the blackout as a root cause, we do know that wind and solar don’t contribute to grid stability in the same way that some other power sources do, says Seaver Wang, climate lead of the Breakthrough Institute, an environmental research organization. Regardless of whether renewables are to blame, more capability to stabilize the grid would only help, he adds.

It’s not that a renewable-heavy grid is doomed to fail. As Wang put it in an analysis he wrote last week: “This blackout is not the inevitable outcome of running an electricity system with substantial amounts of wind and solar power.”

One solution: We can make sure the grid includes enough equipment that does provide inertia, like nuclear power and hydropower. Reversing a plan to shut down Spain’s nuclear reactors beginning in 2027 would be helpful, Wang says. Other options include building massive machines that lend physical inertia and using inverters that are “grid-forming,” meaning they can actively help regulate frequency and provide a sort of synthetic inertia.

Inertia isn’t everything, though. Grid operators can also rely on installing a lot of batteries that can respond quickly when problems arise. (Spain has much less grid storage than other places with a high level of renewable penetration, like Texas and California.)

Ultimately, if there’s one takeaway here, it’s that as the grid evolves, our methods to keep it reliable and stable will need to evolve too.

If you’re curious to hear more on this story, I’d recommend this Q&A from Carbon Brief about the event and its aftermath and this piece from Heatmap about inertia, renewables, and the blackout.

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