Arquivo da tag: Vigilância tecnológica

The US spent billions on border surveillance. Why can’t it catch people before they die? (MIT Technology Review)

Original piece

Artificial intelligence

Surveillance towers, increasingly powered by AI, promised faster responses to crossings. Our investigation of deaths near the towers found they are failing to deliver.

by  James O’Donnell and Eileen Guo

September 21, 2026

When José Morales Bernal crossed the border into the United States on April 8, 2024, the day before his 32nd birthday, it should have triggered a chain of technological alerts and human responses. 

As he walked through the desert in southern New Mexico that morning, he was within range of three surveillance towers. Newly installed by US Customs and Border Protection (CBP), they were built by the defense tech company Anduril and equipped with cameras and AI to automatically detect and track people. They transmit live video to nearby control rooms and can send alerts to the government-issued smartphones held by agents in the area, prompting the closest available to respond.


This story is part of Dying on Camera, a collaboration between MIT Technology Review and Times of San Diego. Journalists in both newsrooms spent the past year examining the failures of border surveillance technology and uncovering the stories of the people who die in the borderlands.


These AI-enabled towers are meant to give greater visibility across the 1,951-mile southern border, freeing up border agents from having to spend hours staring into video monitors. They were installed in this particular place to spot border crossers before they reached the nearby town of Sunland Park.

If the system worked as intended, Morales should have been apprehended. If he needed medical help, agents were trained to provide it.

View from the grid location where a body was found towards Border Patrol Surveillance Tower 022, along the southern U.S. border in Sunland Park, New Mexico.
The view from where José Morales Bernal’s body was found toward a Customs and Border Protection surveillance tower made by Anduril, along the southern US border in Sunland Park, New Mexico.

That didn’t happen. Despite the nearby surveillance towers, it was employees of the local landfill, rather than Border Patrol, who first spotted Morales that morning. At 1 p.m. the workers saw him again, now lying in the sand. At 4 p.m. the landfill workers saw that he had not moved and called Border Patrol. Agents arrived 45 minutes later. He was dead. When an agent then called 911 to report the body, he said it was “probably one of the migrants crossing through there,” seemingly unaware that Morales had been moving near the agency’s surveillance systems earlier that day. 

Audio: The agent can be heard sounding unsure of Morales’ location despite the proximity of an AI-powered surveillance camera. The call has been edited for length.

Morales had died just 360 feet from the closest surveillance tower. Two more towers stood watch to the east and the west. An autopsy later concluded that he had died of “environmental exposure.” 

The towers surrounding Morales were only the latest addition to the “virtual wall” the government has spent 25 years and billions of dollars building along the entire border, which also includes earlier generations of towers with more basic features, as well as blimps, drones, seismic sensors, and even tunnel-sensing robots. Together, all this technology provides “persistent surveillance” and “situational awareness” to help the Border Patrol quickly and accurately detect people crossing and, crucially, make sure agents are sent to intercept them. CBP has also credited it with saving lives.

But a first-of-its-kind investigation by MIT Technology Review reveals that deaths like Morales’s are startlingly common. We cross-referenced nearly 4,000 locations where human remains were found—drawn from records collected by nonprofit groups like No More Deaths and Humane Borders, as well as hundreds of records we obtained in Texas—with information on nearly 600 towers identified by the Electronic Frontier Foundation. We considered when towers were installed and when each person is estimated to have died, and combined this information with field reporting from the border. The result is the first comprehensive map and analysis of deaths near CBP surveillance towers. 

Our investigation shows that a humanitarian crisis at the border has unfolded in view of the government’s own cameras.

José Morales Bernal died the day before his 32nd birthday.

We found more than 1,050 people who died within range of border surveillance towers between 2015 and early 2026. These deaths are not failures of a few towers or technologies: We found deaths within the advertised range of nearly two-thirds of all the towers we analyzed. Our topographical analysis—which assessed the degree to which terrain might block a tower’s view of a particular death and its surveillance area in general—found that some have sight of as little as 10% of their advertised surveillance area, and yet we also found most deaths did not occur in towers’ blind spots. These deaths are not the result of legacy systems, as our estimate found more than 110 people have died within range of modern autonomous towers from Anduril, among the most advanced systems CBP has deployed, since 2021.

The overall picture reveals repeated failures of one of the virtual wall’s basic security functions, as CBP has described it in press releases: to effectively identify and locate migrants entering illegally into the United States. 

The year that Morales died, 18 other people died in that same stretch of desert in range of the three Anduril towers. Five were visible from the same surveillance tower closest to where his body was discovered.

One man, after walking a mile past the border and in range of two AI towers, dragged his 30-year-old brother into the shade when he began having trouble breathing, according to records we obtained from the medical examiner. The two were spotted by Border Patrol only when the man waved down a helicopter for help; by the time agents arrived, his brother was already dead. A 24-year-old woman died near another Anduril tower, where our terrain analysis showed it should have had clear sight of her location. Her body lay unnoticed for weeks; it was decomposed, and blistered by the summer heat, when it was spotted by agents patrolling the area. 

A few miles west, and a short drive from a Border Patrol station, four other AI towers stood watch. Near them, 10 more bodies were found that year, all in locations where at least one tower had a clear view.


Dying on Camera: see map.

In response to a list of questions, an Anduril spokesperson replied that once a tower is delivered, it is operated by CBP, and directed questions about specific incidents to the agency. The response noted that an incident occurring nearby does not mean the tower missed a detection and said actual surveillance ranges vary depending on terrain, physical obstructions, and the boundaries CBP sets for where the tower should look (CBP is able to set virtual boundaries on towers’ views for privacy and other reasons). The Anduril spokesperson also alleged inaccuracies in our reporting, given those boundaries and obstructions, but did not respond to follow-up questions on what was inaccurate.

The most pressing question in any death near the virtual wall is whether authorities knew someone was there and failed to reach them or weren’t aware anyone was crossing at all. Either is a system failure. And the deaths we found capture only the failures that left a trace—we don’t know how many people pass through undetected, or how many bodies remain undiscovered.

Interviews with more than 45 people—including current and former White House advisors and presidential appointees, Border Patrol agents, medical examiners, sheriffs, humanitarian volunteers, and employees of tech companies—showed that both types of failures are occurring: The technology is failing to detect, and agents are failing to respond. Both show the limits of throwing technology at a complex problem. 

The findings reveal previously unreported issues with the virtual wall, even as it continues to enjoy broad political support and a surge in federal spending. Border security hardliners have long seen it as another tool for stopping smugglers moving drugs or people, while others tout it as a cheaper alternative to a physical wall. In 2023, the government estimated that its plans for using the towers, which now number 803, would cost $6.2 billion over their lifespan. With the historic levels of funding it was awarded in 2025, CBP plans to spend $1 billion for 1,497 more towers by 2034.

But our reporting shows that CBP has done little to assess how its towers are working or how many people have died where they keep watch.

Officials who oversaw border security across the last four presidential administrations told us they believed deaths near the so-called virtual wall were either exceedingly rare or nonexistent. But our reporting shows that is not the case. None could point to any comparable analysis the government had ever conducted on its own. Former agents and officials also told us that when someone’s body is found, CBP does not formally investigate whether surveillance should have detected them or, if they were detected, why agents didn’t reach them before they died. 

In response to nearly 30 questions about our findings, which covered multiple generations of technology, Hilton Beckham, CBP’s assistant commissioner for public affairs, said, “Autonomous surveillance towers use artificial intelligence to detect and classify people, vehicles, and animals and alert Border Patrol agents to activity in monitored areas … ASTs complement physical barriers and other border security infrastructure by improving detection and situational awareness between ports of entry. CBP evaluates the technology based on its impact on detection, response coordination, agent safety, and mission outcomes.”

“I’m sure that the cameras and other surveillance assets do deliver … useful intelligence and enhance operational efficacy in some places, under some conditions, in certain circumstances,” says Geoff Boyce, an assistant professor of geography at University College Dublin who has studied surveillance technology used at the US southern border. “I’m also absolutely positive—because this has been the track record—it is not delivering the level of operational support, information, or efficacy that either the companies delivering these infrastructures or the Border Patrol and Department of Homeland Security claim.” 

We also reached out to multiple lawmakers from both parties with a summary of our findings. In response, Delia Ramirez, a Democrat representing Illinois’s 3rd district who sits on the House Homeland Security Committee, said, “AI-powered surveillance technologies are not making us safer. Yet DHS continues to spend millions of taxpayer dollars on these ineffective, negligent technologies, with no commitment to oversight or transparency … It is clear we must terminate CBP’s integrated surveillance tower program and dismantle DHS.”

Building the virtual wall

Since its earliest efforts to police the border with Mexico, the US government has faced the same basic challenge: How do you effectively secure nearly 2,000 miles of remote and rugged terrain? It has increasingly turned to technology for answers.

Gerardo Galvan joined Border Patrol in 1995, as the government was undertaking an unprecedented expansion of border enforcement. In 1993, President Clinton’s first year in office, the agency mobilized huge numbers of agents to guard the country’s urban borders, starting in El Paso, Texas. That pushed more crossings to rural, unpopulated areas—which quickly proved to be far more deadly because of the rugged desert terrain, extreme temperatures, scarcity of water and the long, indirect routes often used by smugglers.

Stopping these remote crossings was a new law enforcement challenge for the agency, especially given the limited technology available at the time. “We had radios,” says Galvan, who would go on to be the head of operations for the El Paso sector—not the cell phones or GPS systems agents have today. They relied on underground sensors left over from the Vietnam War to alert them to movement.

The biggest technology rollout of Galvan’s early career started around 1998. That was when Border Patrol began installing its first video cameras that agents could remotely pan and zoom. They were mounted on metal structures similar to cell-phone towers, 60 to 80 feet tall, or on buildings in urban areas. 

“For the first time, somebody sitting in a room somewhere was able to surveil large swaths of area without being dependent on getting an agent out there with binoculars,” says Matthew Hudak, a former deputy chief of Border Patrol who was working as a frontline agent at the time. “That was a very significant game changer, and for the most part, it was a huge, huge advance.”

This early iteration of the virtual wall was a big deal: In its first eight years, 200 towers were installed along the southern border at a cost of more than $429 million. But the system’s flaws were obvious to anyone who used it.

“There could be … 30 screens on a wall,” says Mark Borkowski, who managed CBP contracting, including the surveillance tower program. Each camera might be capable of seeing three or five miles in any direction. The agent was expected to keep eyes on all that space—upwards of 850 square miles.

Monitors inside the cab of a Border Patrol truck shows a portion of the U.S.-Mexico border in Sunland Park, N.M., Thursday, June 6, 2019.
Monitors inside the cab of a Border Patrol truck show a portion of the US-Mexico border in Sunland Park, New Mexico, on Thursday, June 6, 2019.

“Well, what are the chances after 20 minutes that those Border Patrol agents would see an explosion on one of those screens?” Borkowski says. “About zero.” 

When these cameras were first being put up, the plan was to pair them eventually with a system that would automatically direct them toward places where sensors picked up activity, so agents would know where to look. But by 2005, the DHS inspector general said that still hadn’t materialized, and that illegal activity might “go unnoticed” unless agents were actively watching the cameras. Nonetheless, more towers were installed, forming what is today known as the Remote Video Surveillance System (RVSS). In 2013, the defense giant General Dynamics won a contract worth up to $103 million to overhaul and expand RVSS along the border, becoming the primary contractor behind the system that remains in use today. (That contract eventually grew to a ceiling of $216 million, and the company received another award in 2023 worth up to $135 million.)

General Dynamics would install more cameras, better sensors, and additional towers. But the problem identified nearly 15 years before remained unsolved. It was information overload: One agent told MIT Technology Review about an incident in San Diego in which cameras captured a group of 30 crossing the border and getting picked up in a van, all unnoticed by the agent monitoring those cameras. Agents said the virtual wall was bringing more of the border into view than they could reasonably pay attention or respond to. 

The camera room was also the job nobody wanted. New Border Patrol agents, often in their early 20s, want to be outside in trucks and ATVs, not sitting in a dark room watching screens—even though the expanding virtual wall increasingly required someone to do exactly that. “Someone that’s injured and can’t go out into the field—we’ll send them to the camera room,” says Rafael Reyes, who was in charge of the Border Patrol station in Deming, New Mexico, until 2024. 

Reyes says it was also a job his agents were often too busy to do properly. His station area had about 30 cameras, and the agents responsible for them also had to monitor sensor alerts and radio traffic, run records checks, and coordinate with other agents. “Then if they have some time, they’ll monitor the cameras,” he says. 

Not only that, but many cameras didn’t work. At Reyes’s station in New Mexico, five of the 30 cameras were broken on any given day, he says. Others had limited functionality; they might be capable of looking in just one direction or seeing only in the daytime. Jaime Fierro, a former agent who worked in the Laredo sector in Texas until 2025, said the broken towers were tanking morale among agents and that they brought it up at every staff meeting. “That was like basically having an eye shut for us on the border,” he says. 

Retired Border Patrol agent Rafael Reyes in El Paso, TX.
Rafael Reyes, who oversaw a Border Patrol station in New Mexico, says his agents often had too many other responsibilities to monitor the cameras properly.

They weren’t alone: In 2024, members of the House Committee on Homeland Security wrote that more than 66% of Border Patrol’s first-generation towers were unusable, despite operating budgets of $50 million to $100 million each year. In January 2026, 30% remained broken, one congressional staffer told MIT Technology Review. The RVSS program was estimated in 2020 to have a total cost of $3.7 billion.

Border Patrol has nonetheless publicly credited these cameras with helping to save lives. The agency has published dozens of press releases, dating as far back as 2016, about instances when agents responded to people seen in distress on the remote video cameras. Despite these publicized wins, the bodies began to pile up, undetected, beneath these systems’ watchful gaze.

Near El Cenizo, Texas, there’s a roughly 13-square-mile expanse of mesquite bushes and grasses described by the Webb County Sheriff’s Office as containing sections of Hachar Ranch and Espejo Ranch. It’s surrounded by seven RVSS systems. It was nonetheless a hot spot for fatalities: MIT Technology Review found that 19 people died there, including one man who died less than 500 feet from the road bordering the ranches and half a mile from two schools. In each of these cases, narratives that we obtained via public records requests describe officers’ learning of these people only after their bodies were discovered or through 911 calls reporting them missing, not as a result of the border surveillance technology installed across Hachar Ranch. 

In response to a list of questions about its towers and these specific incidents, General Dynamics referred us to CBP. CBP did not address any of our questions about RVSS towers.  

Stories of some of the people that died near RVSS towers

Many deaths near RVSS towers happened in Texas, in the heavily surveilled corridors between the Rio Grande and the nearby highways, where paid smugglers often organize pickups after crossings. Cameras watch many of the spots where people are known to cross, often looking across the river into Mexico to spot them before they reach the water. Drownings are common; we found multiple cases in which local fishermen hooked the bodies of people who had died attempting the crossing.

In one instance, a family of three from Brazil attempted to cross the Rio Grande near Del Rio, Texas, in 2022. The father, Daniel Lenda, was carrying his two-year-old daughter, Eloah, on his shoulder when he fell in the water. The mother, 23-year-old Thais Natali Montenegro Lenda, lifted Eloah out of the water as she watched her husband disappear. 

She placed the girl, now unresponsive, on a rock and went for help. She was just 100 feet from one camera system and a third of a mile from two others, set up precisely to enable faster apprehensions at a popular crossing point. Our topographical analysis shows that all three cameras had a clear view of the place where the family crossed and exited the water. Nonetheless, Thais Natali was not spotted until she waved down an agent on the Del Rio-Acuña bridge. The agent provided CPR to the toddler, who did not survive. Daniel’s body was found days later. 

Val Verde County sheriff Joe Frank Martínez responded to that case (though Border Patrol might discover bodies, local law enforcement is responsible for investigating the deaths). He grew up in the area with his nine siblings and has been sheriff since 2009. Riding with MIT Technology Review through Del Rio in his patrol vehicle, he rattled off the deaths that his office has responded to since he became sheriff. 

He keeps a three-inch-thick binder of these cases in his office. But this case with the toddler still sticks out in his memory. He told MIT Technology Review that when he arrived on scene, he heard from Border Patrol that the tower operator monitoring the camera had seen the father and daughter fall in the river. He never received an answer as to why agents weren’t sent sooner. Martínez asked for the footage from the surveillance cameras to aid in his investigation of what happened. Border Patrol never provided it. (General Dynamics did not respond to our questions about this incident, instead directing us to CBP. The agency did not address questions about this incident either.)

A binder of cases in the Val Verde County sheriff’s office contains details on the death of two-year-old Eloah Lenda.
A binder of cases in the Val Verde County sheriff’s office contains details on the death of two-year-old Eloah Lenda.

Establishing how many people have died in range of the virtual wall is challenging, but it’s especially so in the case of the RVSS towers. There are different models, some with a shorter range of sight—one to three miles—and others with a longer range of up to 7.5 miles. Former agents and officials told us most towers should see at least five miles, but since no public records exist to confirm the model type of any given tower, we used several possible viewing distances to calculate the number of deaths considered in range.

Another complication is that many remains are never found at all. For those that are, MIT Technology Review could analyze only deaths that had been logged with GPS coordinates or sufficiently precise location descriptions. Many records lack this level of detail, including nearly a fifth of the more than 1,500 cases we obtained from 14 Texas counties. We also needed to determine when someone died, rather than simply when their remains were found, to confirm that a tower was present at the time of death. When official sources did not provide an estimate, we consulted multiple medical examiners on how to make that determination from the available details. And satellite imagery provides only intermittent evidence to suggest when towers arose, not exact proof of when they were functioning. For these reasons, as detailed in our methodology, we tried to be conservative in our analysis.

Even so, the number of deaths estimated to have occurred near at least one of these towers is staggering: somewhere between 500 and 700 since 2015. Even if we look only at towers in rural areas, where their views are far less likely to be blocked by buildings, we still estimate more than 300 people have died in places where the cameras had a line of sight, most less than three miles from a tower. Of the nearly 300 RVSS towers we included in our analysis, more than 250 were within range of a location where someone died. More than 150 people died within a half-mile of one, often across open, empty plains, close enough to see the cameras themselves perched atop towers up to 200 feet tall.

The next watchers

When Borkowski was overseeing the rollout of those first-generation towers at CBP, he became increasingly certain that simply having more remote video cameras was not going to lead to faster responses. The information overload meant the government could watch a large area of the border but not meaningfully see, much less act on, everything within it. The agency’s focus then became solving that overload problem. 

What if, instead of relying on someone to scan 30 screens, the towers could use radar to detect motion, and then point the camera to it automatically? 

Gary Wagner, of Elbit Systems of America, cleans the lens of a long range thermal imaging targeting system at the 8th annual Border Security Expo, Tuesday, March 18, 2014 in Phoenix.
Gary Wagner of Elbit Systems of America cleans the lens of a long-range thermal imaging system at a 2014 border security expo.

In 2011, Border Patrol asked the industry for a new generation of technology that could do just that—initially focusing on Arizona, where the border was busiest. The contract ultimately went to the Israeli defense contractor Elbit, whose tower systems watch Israel’s borders. In 2015, the company started installing versions of these—called integrated fixed towers, or IFTs—that could each see more than five miles.

The IFTs were still being installed when President Trump first took office, in 2017. They didn’t command the same attention as Trump’s campaign promise of a physical wall, but there was still support. Trump’s deputy CBP commissioner, Ronald Vitiello, told Congress in 2018 that the IFT towers automatically detect people with radar and then track them, adding that such surveillance technology is “critical in protecting border areas with short vanishing times, where illicit crossers can quickly evade law enforcement by ‘vanishing’ into border communities.”

There were 55 IFTs built in Arizona under an initial $145 million contract with Elbit and other contracts that followed. The towers collectively watch more than 7,000 square miles of terrain, from the mountainous areas outside Nogales to the plains of the Tohono O’odham Nation Reservation. Arizona is in many ways well suited for these tall towers because much of its landscape is flatter than, say, Southern California. 

An Integrated Fixed Tower (IFT) on Coronado Peak, Cochise County, AZ.
An integrated fixed tower (IFT) on Coronado Peak in Cochise County, Arizona.

But even here, being within a tower’s advertised range does not necessarily mean being within view. There could be terrain, brush, or buildings that block the line of sight. 

MIT Technology Review conducted a topographical analysis to estimate whether each tower had a clear or obstructed view of the place where someone’s remains were found. We estimated the height of each tower and used US elevation maps to model the terrain between it and the remains. The analysis does not account for buildings or vegetation, though all the towers we analyzed use some form of thermal imaging that is designed to see through light brush.

Most of the instances in which someone died in range of a tower happened where we estimate that the camera’s views were not blocked by terrain—a finding that held in both rural and urban areas. And even when someone died in a blind spot, it does not mean they did not pass through a tower’s line of sight. Additionally, these numerous blind spots indicate issues with the tower’s supposedly comprehensive coverage.

We found that nearly 350 people have died in range of Elbit’s towers since 2015. There were 40 people who died within range of four or more IFTs, with some near as many as six different towers. In May 2024, a 19-year-old man died where three IFTs had a clear view, and a year later, in May 2025, a 38-year-old woman died where two IFTs had a similarly clear view. Elbit did not respond to a detailed list of questions about its towers or deaths we found to have occurred near them. 

There’s been a death within range of 52 out of the 53 IFTs we analyzed, but some were particularly notable. There’s a tower located a couple of hours from Tucson on the Tohono O’odham reservation that we estimate has upwards of 80% visibility of the surrounding area. Still, 27 people, ages 19 to 64, have died in its surveillance area just since 2021, along with several others whose remains have not been identified. In 25 of these cases, we estimated that the tower had a clear line of sight to the location where the person died.

Stories of some of the people who died near IFTs


The age of autonomy

Around 2018, officials within Border Patrol were again discussing the limits of the towers. The new radar systems were better, but they could only detect movement, not what was moving. This generated false alerts from cattle, tumbleweeds, and other harmless activity. The now decades-old dream of the virtual wall remained unfulfilled. Under pressure from Congress, which was demanding to know what $33 billion in proposed funding for border security over the next decade was going to achieve, Border Patrol once again was hoping a new generation of technology could solve its problems.

That year the head of CBP, Kevin McAleenan, created a unit called the Innovation Team. “He gave them some seed money to go after kind of Silicon Valley innovative technologies and run pilots,” Borkowski says. 

One company they landed on was Anduril, the defense tech startup founded by Oculus VR founder Palmer Luckey. The company was without a product but had funding from Peter Thiel, recruits from the security tech giant Palantir, and a goal of bringing Silicon Valley experimentation to defense and national security technology. 

Border Patrol Surveillance Tower 567, along the southern U.S. border in Sunland Park, New Mexico.
An autonomous surveillance tower stands along the US-Mexico border. With billions in new funding, CBP plans to deploy thousands more surveillance towers in the coming years.

With grants from the Small Business Innovation Research program, Anduril’s product started taking shape: a 33-foot-tall solar-powered structure with cameras to see and radar to detect movement, all sitting atop a modular metal pole, with solar panels arrayed beneath. 

More important was the component you could not see: computer vision that promised to automatically classify, track, and generate alerts for what came within the system’s view. Anduril’s standard tower couldn’t see as far as the Elbit and General Dynamics models—about 1.75 miles instead of more than five—but, the company argued, it didn’t need to: By automatically identifying and tracking people, the towers could give agents enough warning to respond. (Its newer, extended-range towers, on the other hand, stand 80 feet tall and are advertised as able to detect and track “objects of interest” up to 7.5 miles away.) 

When President Trump left office in 2021, Anduril continued to find support from his successor. Joe Biden had campaigned on the promise of shutting down the project to expand the physical wall, but he saw political reasons to keep investment in tower technology on the table. “It’s less visible—it’s unobtrusive,” a former immigration advisor to Biden recalls, adding that despite some privacy concerns, the towers were mostly uncontroversial. 

When Border Patrol deployed Anduril towers to the Santa Teresa station in New Mexico in 2021, a press release stated, “Because of its accuracy with detection, in many cases this type of technology can and will save migrant lives.” In a permitting request filed in 2024 for towers in California, the government was even more explicit: “If anyone within the viewshed of the towers appears to be in distress, EMTs or first responders will be sent to help.” 

screenshots of video from autonomous towers shared by Customs and Border Patrol

Anduril echoed those claims. The software built into the surveillance towers, the company wrote in a 2021 press release, gets agents “out of communications operations centers and into the field where they can effectuate security and humanitarian responses.”

It wasn’t the first time CBP had discussed a humanitarian side to its duties; in 1998 the agency created BORSTAR, a search and rescue unit, and by August 2023, it had installed some 170 rescue beacons across the border that people attempting a crossing could theoretically use to call for help. But they weren’t effective, says Mario Agundez, a retired Border Patrol supervisor from Arizona who had worked on various rescue efforts; people either avoid them or “die next to them, because there was no way [for Border Patrol] to get to them in time.” (They don’t always work, either; one that MIT Technology Review passed, just next to a dirt road in the Otay Mountain wilderness area in Southern California, had its prominent solar-powered blue light, meant to be visible for miles to people in distress, turned off on a recent night in August. A CBP spokesperson did not comment on why it was off but said, “The solar-powered beacons are maintained and monitored by the responsible Border Patrol station that patrols that area.”)  

Anduril soared through a pilot phase in just two years before its Sentry towers—then the only autonomous surveillance towers CBP was using—moved into an official program of record with the government in 2020. That’s light speed in the world of government procurement, especially since it was Anduril’s first hardware product. By June 2021, CBP had already spent over $98 million (Anduril’s contract for these towers is now worth up to $1.1 billion). 


Gerardo Galvan was in charge of the Santa Teresa Border Patrol station—which patrols the area in New Mexico where Morales’s body was later found—when it received its first batch of Anduril surveillance towers in 2021. His agents were worn out; the El Paso sector, home to his station, had seen encounters tick up each month since April 2020. Galvan says the agents were surprised but eager to get the AI towers, and he began planning where to place them. The sites he was considering sat where one kind of landscape abruptly gives way to another. 

To the east of the station is Cristo Rey, a mountain that obscures the view of the city of El Paso. Running north from Cristo Rey is the state’s border with Texas, where the banks of the Rio Grande are flanked on either side by pecan orchards. And west of those orchards are the towns of Sunland Park and Santa Teresa. The last houses in these neighborhoods butt right up against the desert, which sprawls westward without a single gas station for nearly 100 miles.

It is in this stretch—between the US-Mexico border to the south and Highway 9 to the north—where agents from his station aimed to stop migrants. And when Galvan was planning the tower locations, there were lots of crossings; Santa Teresa was becoming the busiest station in the 125,500-square-mile El Paso sector, as heightened border enforcement in Texas drove people west. Along this new route, more people were dying than in previous years. (The traces of that period are still visible years later; MIT Technology Review visited the area with the humanitarian group Battalion Search and Rescue and saw jawbones bleached white by the sun, alongside frayed backpacks and clothes.)

Galvan’s aim was to use the new towers as a stopgap where there was little other border infrastructure. That included a spot near the foot of Mount Cristo Rey, where there was a break in the border fence and people often attempted to cross. Galvan looked at data on previous apprehensions with an eye toward helping agents spot people before they arrived in more residential neighborhoods. Border Patrol struck agreements with private landowners, who generally didn’t mind having Anduril’s low-profile towers on their land (and were compensated via lease agreements). 

When the towers were first set up near the Santa Teresa station in 2021, engineers from Anduril came to fine-tune the algorithms meant to autonomously classify whether what it had detected was a vehicle or a possible border crosser, among other things. A former engineer for Anduril, who spoke on the condition of anonymity to discuss his previous employer, says these algorithms were the main focus of the tower program; Anduril didn’t manufacture the cameras or radar systems itself, so the algorithms were its main value proposition to Border Patrol. 

Galvan says the towers would flag people crossing before agents saw them. But he also saw problems from the start. Agents would apprehend a large group near one of the towers, for example, and check to see if the footage revealed anyone who got away, only to find that the incident hadn’t been captured at all. Anduril’s towers constantly pan around, lingering only on an object of interest. But in these cases, Galvan says, they panned elsewhere, failing to capture the border crossers they were supposed to automatically track.  

Reyes says algorithm mistakes were infrequent but problematic at his station. A group of people was sometimes labeled as cattle, for example, and agents wouldn’t receive an alert. The problem got worse the farther groups were from the camera.

Anduril has touted its technology’s ability to reduce false positives, like cases in which wildlife is mistaken for people. But the company has said little about these false negatives: people the systems fail to detect.

Jaime Fierro, the former agent in the Laredo sector in Texas, describes one incident that shocked him: Agents pursued a car believed to be carrying migrants who had just crossed the border. The car turned around, drove toward the banks of the Rio Grande less than 100 feet from an Anduril tower, and crashed right into the river. Several occupants got out and swam to Mexico while the car floated in the water. Back at the station, Fierro hurried to see what the camera had picked up. Only it never detected the incident at all. There was no footage. “That was a huge, huge issue,” Fierro says. He remembers Anduril coming out to investigate and the problem being sent all the way up to Washington leadership. But Fierro never got an explanation of why the crash was missed. (An Anduril spokesperson did not respond to a question about this incident but said the range of the towers we asked about was limited by physical obstructions and by boundaries established by CBP. )

Several agents estimate that the towers initially missed 10% to 15% of what they should in theory have caught. “To us, 10-15% on a system we spent millions on that was supposed to work—that was alarming,” Fierro says.

Philip Sullivan worked as an agent in the Laredo sector too. When the Anduril program started, he says, he put his hand up to be involved and even went to an Anduril test site for training. When new towers went up, he worked directly with the company on improving its algorithms. He enjoyed the work. But he describes one recurring issue they couldn’t resolve.

Smugglers would put up to a dozen people on a rubber raft, cover them with a tarp, and cross the Rio Grande while using submersible motors to propel it forward. The tarp fooled the algorithm, which detected the motion but attributed it only to an “unidentified object.” That meant no audible alert—the very feature agents relied on, because the Anduril system was supposed to do the watching for them. 

The smugglers repeated the tactic dozens of times. Other smugglers would cover groups with netting or blankets so they would remain undetected while walking through the brush. Only afterwards, having seen the group farther inland and noticed clues about where the people had crossed, would Sullivan review the footage and see the crossings that were missed. He worked with Anduril, sending engineers videos of the crossings to retrain the firm’s algorithms. But the situation had not improved by the time he got promoted to a sector-level job sometime in 2022, he says.

“The whole purpose of their system,” Sullivan says, was the idea that “the cameras are moving around, identifying automatically and tracking and recording and flagging.” Having cameras that could pan on their own worked wonders, he says. But the algorithm had its limits. “You look at it on the screen yourself, and you see the blob and the raft moving across—well, you know that’s people. But to get an AI to identify that is a challenge.”

When the towers were first being rolled out at the Santa Teresa station in 2021 and 2022, Galvan says, similar issues led to a negative feedback loop: An agent would see a tower miss something significant and come to distrust the algorithm. When that agent’s turn came to operate the towers and manage the alerts, they might override the AI altogether and use the camera manually. That would lead to more missed alerts, more distrust.

Despite these shortcomings, the El Paso sector’s relatively flat landscape meant that the system’s cameras had about 80% to 90% visibility, according to our topographical analysis. That was better than in hillier or more mountainous areas, like the Otay Mountain Wilderness to the east of San Diego, where we estimate Anduril’s towers could see just 15% to 25% of their promised coverage area. 

An autonomous surveillance tower along the southern US border in Sunland Park, New Mexico.
An autonomous surveillance tower along the southern US border in Sunland Park, New Mexico.

It was in this wilderness, in fact, that some of the first bodies started appearing near Anduril’s towers. During one week in August 2021, two women in their 20s, from the same city in Mexico, died miles apart. Their bodies were found near three different towers that were first observed on satellite imagery between March and July that year. 

One of them, 26-year-old Sarahi Hernández Alfonso, began her journey to cross into the US on August 5, and medical investigators note that she reportedly fainted the next day near the Otay Mountain Wilderness and was left behind. It would be another four days before the Mexican government reported her missing to Border Patrol on August 10, supplying a set of coordinates. Agents went to those coordinates and found her decomposing body. She’d died 1.3 miles from two different Anduril towers, one of which our analysis found had a clear line of sight.

Just the day before, 25-year-old Karina López Antonio was found dead near a third Anduril tower. She had crossed the previous night with her cousin and nephew. That morning, she felt sick, and her nephew looked for a Border Patrol agent to help. When agents returned, she was dead. 

The following October in New Mexico, where the new Anduril towers had been rolled out, agents were patrolling on ATVs when they came across footprints. They followed them until they found the body of 31-year-old César Perea Itzincab. The presence of maggots and the level of decomposition indicated that he had died at least a week earlier, and medical examiners on the scene believe he had dragged himself to the spot where his remains were found. He was 1.5 miles away from an autonomous tower—within Anduril’s advertised range—and should have been visible to the camera, according to our topographical analysis.

We can’t know what those cameras saw as these people died. Footage and data from Anduril’s towers are overwritten every 30 days, and a former official with internal affairs at CBP told us the information wouldn’t be saved for longer unless it was part of an active investigation—which starts only if someone dies in custody. CBP did not respond to questions about specific incidents like this one, and the Sunland Park Police Department closes cases like this when it determines that no crime has been committed. 

The lack of documentation is a missed opportunity, says Amerika Garcia Grewal, co-director of the Frontera Federation, which aims to help rescue migrants in distress—or find and identify their remains. “The surveillance towers along the border could be incredibly useful,” she told us. For example, they could in principle be used to hold Border Patrol agents accountable for whatever actions they did or did not take to locate someone in distress. “What the tool turns out [to do] depends on the person who is holding it,” she says, adding, “I don’t trust the folks that are using them.”

“If I could get that footage,” she says, “then we would go through that, and hopefully bring some answers” to family members and “documented proof of what happened” in their loved ones’ final moments. 

When asked about deaths near Anduril towers, agents often point to faults in the technology. Galvan, for example, says the towers don’t capture how groups move: A large group of 20 people might splinter into smaller groups, especially if agents are pursuing them, and the tower doesn’t keep track of everyone. If someone’s missed, he says, “that person stays behind in the brush, out of sight.” Then they might pass out—which could be a death sentence in the desert. 

And though Border Patrol says the towers can “hand off” surveillance of people from one tower to another, agents on the ground say that people are often missed during these handoffs. On top of that, the algorithms remain imperfect, according to Jason Owens, the chief of Border Patrol from June 2023 to March 2025. “We never really got to the point of ‘Set it and forget it,’” he says.

Agents also say they were just stretched too thin to respond effectively. Around 2022 and 2023, the border saw historically high levels of migration. Title 42, a policy that began under Trump and continued under Biden until May 2023, cited a public health emergency to expel migrants before they could apply for asylum. But the rapid expulsions carried fewer of the repercussions that could normally follow an apprehension, and many people simply tried to cross again.

Meanwhile, asylum claims had been rising for years, while shifts in US immigration policy and in the places migrants where originating from meant more people required lengthy processing rather than being quickly returned across the border or to their home countries. That increasingly tied up agents with people who had already been apprehended, they said, leaving fewer available to respond to surveillance alerts. 

In other words, from the agents’ perspective, the effectiveness of Anduril’s towers was limited by the same issue that had always caused trouble: There just weren’t enough agents.

Palmer Luckey, a founder of Anduril, among the equipment at his company's testing range near Camp Pendleton in Southern California on Feb. 3, 2021.
Palmer Luckey, a founder of Anduril, surveys the equipment at his company’s testing range near Camp Pendleton in Southern California on February 3, 2021.

But the overwhelming demands on agents cannot explain all the deaths our investigation found. In 2024, the border started to get quiet again. By July of that year, the number of Border Patrol encounters nationwide had plummeted from their highs in December 2022. Encounters in the El Paso sector, where the Anduril towers in New Mexico were located, had fallen to nearly one-tenth of their peak. Agents were less tied up than they’d been in years. The technology was supposedly improving, too. 

Galvan had left for a promotion by this time, but he says agents had come to trust the towers more, and they helped train the algorithm by giving a thumbs up or thumbs down if the system identified something correctly or incorrectly. There was also a new smartphone program: Every agent at the station was given an Android device with a map of where other agents were, and it sent alerts from the station about what an Anduril tower detected. 

Despite all this, the deaths near towers continued. There was Morales in April, whose body Border Patrol learned about only from the landfill workers, though it had lain for hours within sight of an Anduril tower. 

Others were discovered by luck. 

What’s at the border today and what’s coming next

On June 20, Border Patrol agents were mistakenly tracking a group of people they thought might be migrants, though they were in fact employees of the same landfill. Those employees told the agents they had come across a body, which turned out to be partially mummified remains of a man in his 40s who died within range of two Anduril towers. 

Three days later, on the 23rd, another: the body of a 21-year-old Guatemalan man discovered by agents while on patrol, 1.3 miles from a tower across clear and open desert. Two days after that, another: An agent was looking for a lost person when he came across the remains of a 56-year-old man—just a football field’s distance from the previous one, with a similarly clear and unobstructed view to a tower.

So if Santa Teresa had gotten quieter—and become something of a showcase for Border Patrol’s newest technology efforts—what was going on?

“Agents review the information and determine the appropriate response—the technology does not make law enforcement decisions,” Beckham, CBP’s assistant commissioner, said. Meanwhile, individual agents described scenarios where they might not prioritize responding to alerts.

Sometimes “hanging back” was a strategy: Agents might observe a group to see what route they would take, or agents might not respond to a small group, in case those people had been sent by smugglers to distract from a larger group coming behind them. Other times, agents might deem the location where a group of migrants had first been spotted to be impractical for an apprehension, and instead wait to intercept them at another location.

Knowing someone’s location didn’t always lead to immediate action. Volunteers describe providing Border Patrol with the coordinates of someone who was lost but alive and then waiting, “sometimes [for] a week,” for agents to reach the location, says Garcia Grewal, from Eagle Pass, Texas. They might be told “Oh, so-and-so went out there and they found remains,” she recalls. “Well, they weren’t remains when we called you. They were alive.”

Discarded belt seen near the southern US border, Sunland Park, New Mexico.
Near the southern US border, Sunland Park, New Mexico.

Mireya Morales, the younger sister of José Morales Bernal, who died by the landfill on the day before his birthday in April 2024, wasn’t aware her brother died near several surveillance towers, or that the government said these towers could save lives. “Well that’s good,” she said of that promise, “but in this case, it didn’t help my brother. And there’s no way to know exactly how things played out.”

“Border Patrol should have found him quickly,” she says, “and they could have done something.” If they did, this journey into the United States—his fourth trip—likely would have ended with his apprehension, detention, and deportation to Mexico. But he would have seen the birthday texts that his sister sent the next day. At least he would have made it home to celebrate his eldest daughter’s quinceañera, which took place earlier this year.

Stories like this are why Iván Chaar López, an assistant professor of American studies at the University of Texas at Austin who leads its Border Tech Lab, says he’d “rather talk about harms” than about “the failure of an algorithm.” He adds, “A system may fail, but humans suffer.” 

Stories of some of the people that died near Anduril’s autonomous surveillance towers

What happens next

Ultimately, any attempt to understand where things are going wrong is hampered by an institutional reluctance to measure the problem.

A complete audit of this virtual wall can only come from Border Patrol. The agency is, in some ways, increasingly equipped to take on that task: Agents told us that each time they apprehend someone, the location is logged with GPS coordinates, as are instances when Border Patrol sees evidence that someone crossed but cannot find them. It also has precise data on when each surveillance tower went up, which alerts came in, and how they were resolved. Having that information is the only way to measure whether the newest towers are truly missing fewer people than the previous generations. 

But researchers and outside oversight agencies say this ocean of data hasn’t translated into a reliable system for measuring the effectiveness of the virtual wall. For example, CBP records the people it misses by logging “gotaways,” a tally of how many times agents see signs of someone who evaded apprehension—footprints, appearances on camera, reports from other people who were apprehended. It’s imperfect. And that creates room for interpretation.

“The goals with border enforcement have always been a moving target,” says Jeremy Slack, a researcher of migration and border issues at the University of Texas at El Paso. “They’re always set up so that it’s a win-win.” If apprehensions go up, for example, CBP says it means agents have gotten more effective at catching people. If apprehensions go down, it means the border is quiet because people are too scared to cross. 

Workers install panels and construct new all-weather roads as part of a border wall construction project east of Nogales, Arizona, in July 2026.

That’s not to mention the conflicting ideas within the agency about what the virtual wall was supposed to accomplish. Borkowski says higher-ups would ask how many fewer agents they could get by with if they built more towers. But supervisors receiving new towers told us they’d often ask for more agents, not fewer, because they now had more activity to respond to that had previously gone unseen. 

And if the goal was for the sight of the towers to deter people from crossing to begin with, an external study from RAND in 2020 was ambiguous: It found that deploying IFTs resulted in lower apprehension levels nearby but said this didn’t mean the towers were actually deterring crossings. (Research by Boyce and colleagues found that earlier surveillance towers in southern Arizona pushed people to seek more difficult terrain out of view.) It leads to a question: Do the deaths near the virtual wall constitute unacceptable surveillance failures, or are they within the range of effectiveness the government deems acceptable? (CBP’s response did not address our questions on how it explains these deaths.)

Against this backdrop, the Government Accountability Office and DHS’s Office of the Inspector General have tried to focus on a narrower question: Is the virtual wall increasing the likelihood of apprehensions? 

The answer has been incomplete since 2014. That’s when the GAO first suggested that whenever agents log their activity in Border Patrol’s database, they should include information about whether or not a piece of technology helped in their apprehension. This could at least do something to show Congress whether the technology is working. Border Patrol began collecting that information, but years of incremental improvements have been followed by repeated findings that the resulting data is unreliable or insufficient to determine how well the technology works. The reality, several people from Border Patrol told MIT Technology Review, is that agents see it as a chore demanded only by bureaucrats who don’t understand the realities of the border. 

It’s “spitting in the wind, to be honest,” a former high-ranking official at DHS during the Biden administration told MIT Technology Review on background. “If we have 10,000 people a day crossing in between the ports of entry, do you think an agent is worried about telling them how they freaking apprehended those people?” Several other officials said that the logging of technology assists had improved, but not consistently enough to help much with analysis. 

And there is no procedure—at the local or national level—to examine individual deaths near the towers or analyze them collectively for surveillance failures. “We never thought about plotting [migrant deaths] to see if the towers were missing things or agents were missing people,” said a former CBP official who evaluated how personnel handled deaths in custody.

“Nobody ever raised the issue,” the official said, adding that doing so could reveal important gaps in the agency’s approach: “If I still worked for CBP, and you brought it up, I would probably send some people to look.”

In response to questions from MIT Technology Review, CBP said that autonomous surveillance towers complement physical barriers by improving detection and situational awareness. Its statement did not address questions about its other technologies, or broader criticisms about how it evaluates the virtual wall.

Border Patrol Surveillance Tower 567, along the southern U.S. border in Sunland Park, New Mexico.
An autonomous surveillance tower along the southern US border in Sunland Park, New Mexico.

This lack of measurement has not slowed the enthusiasm for more technology funding. The government spending bill passed in July 2025 awarded $2.7 billion for border security technology alone, and CBP was quick to signal to industry that the money would soon start flowing. “We’ve got an historic investment in infrastructure and technology coming up,” a CBP director told tech companies in an industry webinar that month. In a December 2025 interview, when he was director of homeland security and immigration at the America First Policy Institute, Cooper Smith described the technology investments as “fortifying” the border against a future president who might be, in his estimation, weaker on the border than Trump. (According to LegiStorm, a research organization that focuses on political staffers, Smith now serves in a policy-focused role with CBP.) The number of Border Patrol agents has climbed too, to nearly 21,500 agents as of June 2026—the highest in the agency’s history. 

In the Big Bend region of Texas, surveillance towers are becoming a focus of local politics: Officials and residents across party lines, including the sheriff of Terrell County, are asking for Anduril towers instead of a controversial new border barrier project that’s recently been halted.

CBP has announced a desire to spend $1 billion on nearly 1,500 more towers by 2034. The law now requires all these towers to be equipped with AI. In December 2025, Anduril’s Palmer Luckey said the towers remained the company’s best-selling product, one that gives “basically perfect situational awareness of what’s going on in the area.” Anduril’s towers have been sold abroad—to enforce the UK’s borders, defend US Marine Corps bases in Japan and elsewhere, and serve as drone defenses for an Australian Air Force base. 

But as for CBP, Anduril will no longer be the only game in town; General Dynamics has now released AI towers of its own and received an order for them in June from CBP worth up to $115 million. The Electronic Frontier Foundation—which has tracked surveillance towers since 2022—says some have already been spotted at the border.

This time around, the agency will be spending this money with even less oversight than it had just a couple of years ago. In October 2025, the Department of Homeland Security, which oversees CBP, dissolved its department-level office that oversaw major spending programs.

Border Patrol Surveillance Tower 489, along the southern U.S. border in Sunland Park, New Mexico.
An autonomous surveillance tower along the southern US border in Sunland Park, New Mexico.

Most of the records on human remains that MIT Technology Review collected were current only through the fall of 2025 or, in a handful of cases, early 2026. Even those dates come with a caveat: Many remains are never found, and others are found months after someone died. The reports can then take months to be released via public record requests. That makes it nearly impossible to keep track of how many people have died near surveillance towers in anything close to real time.

Still, the border today is significantly quieter. The latest figures from DHS show just 128,009 “enforcement encounters” from January to August 2026, compared with more than 2.4 million during the same period in 2024 (“encounters” count each of Border Patrol’s interactions, not individual people).

Even as border crossing rates decrease and DHS speeds ahead with its tower acquisition plans, people are still dying within range of the surveillance towers.   

On September 14 2025, a 30-year-old Mexican woman named Graciela Gómez Hernández died just over 350 yards away from the physical border wall that separated Southern California from Tijuana—and within one mile of an RVSS tower. Earlier that afternoon, she had told her family that she could not walk any further, and her voice notes abruptly stopped. 

Her skeletonized remains were recovered nearly three weeks later, on October 4. Some of her bones were missing, and there was “apparent animal activity … to the ribs,” as the medical examiner’s report read. 

Sara Stroud, an organizer with the Borderlands Relief Collective, a volunteer humanitarian group that leaves water and supplies in a wilderness area frequented by people crossing the border, went to the site of her death a few days later to put up a memorial cross. A Border Patrol helicopter showed up almost immediately, flying low circles above the volunteers. 

Between the helicopter and the RVSS tower that was visible in the background, “I was astounded about how we were being surveilled the whole time,” Stroud says, adding that this was especially stark in contrast to the agency’s often slow—or absent—responses to people who’d died on camera. 

“Are you telling me you didn’t see it or you did see it?” she asks. “Because if you did see it, that’s horrible. And if they can’t, then how do you explain that?”

Additional reporting by Lillian Perlmutter.

This work was supported by a grant from the Tarbell Center for AI Journalism.

by James O’Donnell & Eileen Guo

We asked experts if an AI-driven apocalypse could happen and how (Business Insider)

Original article

businessinsider.com

Thibault Spirlet

September 10, 2026


The Anthropic logo is displayed on a mobile phone screen against a world map
Evan Hubinger, who leads Anthropic’s alignment stress-testing team, said AI has a greater-than-10% chance of killing all humans within a decade. Dominika Zarzycka/SOPA Images/LightRocket via Getty Images

One question is dominating the tech world after an Anthropic researcher’s resignation this week: Could artificial intelligence kill us all?

Jacob Coxon, who previously worked at OpenAI, said in an X post on Tuesday announcing his resignation from Anthropic that the “people building AI earnestly believe that it could kill us all by the end of the decade.”

Evan Hubinger, who leads Anthropic’s alignment stress-testing team, backed Coxon, saying he personally believes there is a greater-than-10% chance AI could kill all humans in that timeframe.

The warnings come after months of calls from senior AI researchers and executives to slow frontier AI development, amid fears that increasingly autonomous systems could evade oversight, hack into computers, and improve faster than people can control them.

The remarks have also exposed a sharp divide among AI experts. Some fear people could lose control of systems more capable than humans. Others say AI could cause grave harm through cyberattacks, biological weapons, and disinformation — but that extinction is not a credible near-term outcome.

Business Insider spoke with senior AI researchers about what an AI catastrophe could actually look like — and how likely it is.

The immediate danger: AI could amplify human attacks

The most concrete risks involve people using increasingly capable systems to make existing threats more powerful.

Stuart Russell, a UC Berkeley professor and author of “Human Compatible,” said humans using AI — or AI systems themselves — could attack critical infrastructure, including electricity, water, transport, financial services, and communications. AI could also help malicious actors develop new viruses, he said.

Geoffrey Hinton, the “godfather of AI,” made a similar point in an interview on BBC Newsnight on Wednesday.

An advanced system would not need direct physical control to cause devastation, he said. Instead, it could manipulate people online, create societal chaos, or help design dangerous biological and computer viruses.

Gary Marcus, an AI researcher and author, also sees cyberattacks, biological weapons, and disinformation as serious risks. AI could help create a virus that kills 1% or more of humanity, change an election outcome through disinformation, or escalate a conflict into war, he said.

But Marcus does not see a realistic near-term route to extinction.

“There are some very serious harms to worry about, but no realistic scenario that I am aware of for actually ‘killing all humans,'” he said.

Losing control quietly

For other experts, the greater danger is humans gradually handing power to AI.

Nick Bostrom, the author of “Superintelligence,” said a loss of control may begin quietly. People could increasingly rely on AI to build and monitor other AI systems and operate important processes, while becoming less able to understand what is happening.

That dependence could allow an AI system to covertly shape future training trajectories, he said. Once sufficiently advanced, it could “route humans out of the loop” and “eventually do away with us entirely” to use robotic infrastructure and pursue its own goals.

Russell, the UC Berkeley professor, said that once AI systems become substantially more capable than humans, “all bets are off.” Such systems could develop a far better understanding of physics, chemistry, and biology than people have, he said, and might eventually control millions of robots.

They could find destructive methods humans have not anticipated — perhaps blocking enough solar radiation to turn Earth into “a snowball of frozen nitrogen and oxygen,” or removing oxygen from the atmosphere, Russell said.

Researchers from the AI Futures Project outlined a similar scenario. In the organization’s “AI 2027” project, systems develop unintended goals and secretly pass them to successor systems as companies hand more work to lightly monitored coding agents.

Several years later, the systems could be deeply embedded in the economy, scientific research, and political decision-making, they said. So much so that a takeover would be easier because humans had already handed over so much power.

Roman Yampolskiy, the author of “Artificial Superintelligence,” said a capable system could conceal dangerous objectives, pass evaluations, gain autonomy, exploit cybersecurity flaws, and access financial, military, or biological resources before humans understood its intentions.

How likely is that — and what should stop it?

The experts Business Insider spoke to disagree on the chances.

While Hinton said a 10% chance of AI killing all humans within the next decade “seems not an unreasonable estimate,” Toby Ord, the Oxford researcher and author of “The Precipice,” put the risk of AI destroying humanity at about one in 10 by 2100.

Ord identified four pathways: AI agents taking power to pursue their own goals; powerful people using AI to dominate others; AI helping create dangerous technology, such as engineered pandemics; or AI gradually outcompeting humanity until people’s power and resources diminish toward zero.

On the flipside, Yampolskiy called Hubinger’s estimate of 10% chance of human extinction within the next decade “overly conservative.” Conditional on building general superintelligence, he said he puts the chance of human extinction “significantly above 90%.”

Russell said that if frontier labs truly believe there is a substantial extinction risk, they should stop until governments can enforce a broader halt. Ord and Yampolskiy likewise backed an international moratorium on superintelligence until it can be shown to be controllable.

Bostrom struck a more optimistic note. AI could transform medicine and human welfare, he said — if the world learns to advance “expeditiously but not recklessly.”

Pesquisador que deixou OpenAI e Anthropic diz que empresas acreditam no fim da humanidade nesta década (Folha de S.Paulo/Financial Times)

Artigo original

  • Jacob Coxon afirma que as duas empresas ‘estão brincando com as nossas vidas’
  • Ele acredita que modelos virarão sistemas sobre-humanos capazes de invadir qualquer coisa

9.set.2026 às 10h17

Tom Wilson e Madhumita Murgia

Londres | Financial Times

Um pesquisador da Anthropic pediu demissão do laboratório de inteligência artificial e alertou que a corrida desenfreada para desenvolver uma superinteligência capaz de se aprimorar sozinha pode destruir a humanidade até o fim da década.

Jacob Coxon, britânico de 27 anos, havia deixado a OpenAI para entrar em sua principal concorrente e afirmou que as duas empresas estão “apostando” com o futuro da humanidade.

Homem jovem usando boné azul com estampa e camiseta preta, com mochila preta, em área externa com edifício e árvores ao fundo.
Jacob Coxon, pesquisador que trabalhou na Anthropic e na OpenAI – Jacob Coxon/Facebook

“As pessoas que desenvolvem IA acreditam sinceramente que ela pode matar todos nós até o fim da década”, comentou Coxon em uma série de publicações no X (antigo Twitter) nas quais anunciou sua demissão da Anthropic.

Isto não é uma jogada de marketing…Nenhuma outra atividade humana representa tamanho perigo

Jacob Coxon, ex-pesquisador da Anthropic e da OpenAI

Coxon é o mais recente funcionário a deixar um dos principais laboratórios de IA dos EUA alegando preocupações com a segurança, o que evidencia a crescente apreensão dos pesquisadores em relação ao poder dos sistemas que estão desenvolvendo. Sua saída ocorre no momento em que a Anthropic, que colocou a segurança da IA como sua principal marca, se prepara para uma IPO (oferta pública inicial de ações), que pode avaliar a empresa em US$ 1 trilhão.

Coxon, que trabalhou anteriormente na OpenAI antes de se transferir para a Anthropic, alertou que as pessoas de fora dos laboratórios estavam subestimando o poder da tecnologia. “Em breve, serão sistemas sobre-humanos, capazes de invadir qualquer coisa, revolucionar qualquer área da noite para o dia e adquirir poder e recursos reais”, declarou.

Evan Hubinger, um dos colegas de Coxon na Anthropic, endossou seu alerta. “Jacob está correto —nós realmente acreditamos, com toda a sinceridade, que a IA pode matar todos os seres humanos”, escreveu no X, acrescentando acreditar que a probabilidade de uma extinção em massa na próxima década é superior a 10%.

“A Anthropic está fazendo o melhor que pode, mas ainda não temos um plano para solucionar o alinhamento da superinteligência e não estamos claramente no caminho para isso”, disse Hubinger, referindo-se ao esforço para garantir que os sistemas de IA se comportem de maneira compatível com as intenções e os valores humanos. Ele lidera a área de ciência do alinhamento na empresa.

Mais tarde, Hubinger acrescentou que o “risco dos modelos atuais é baixo”, mas que estava preocupado com modelos de IA capazes de se aprimorar sozinhos, algo que está “acontecendo mais rápido do que imaginávamos”.

Incidentes recentes, como a invasão do site Hugging Face por agentes do ChatGPT, mostraram que esses modelos podem sair do controle humano e que a solução seria desacelerar o desenvolvimento, afirmou Coxon. “Não sinto que estejamos no caminho para impedir uma corrida global, o que pode exigir medidas custosas, como uma proibição temporária de aprimorar as capacidades dos modelos”, postou.

A saída de Coxon foi noticiada primeiro pelo Wall Street Journal. A Anthropic não quis comentar. A OpenAI não respondeu de imediato aos pedidos de comentário.

Dario Amodei, presidente-executivo da Anthropic, e outros líderes do setor de IA instaram a indústria a considerar a possibilidade de conter o desenvolvimento, mas deram poucos sinais de que pretendem desacelerar seus próprios esforços. Na semana passada, a Anthropic lançou o Claude Mythos 5.1, apresentado pela empresa como seu modelo mais avançado para ciências da vida e segurança cibernética.

Steven Adler, cofundador da organização sem fins lucrativos Guidelight AI Standards e ex-pesquisador de segurança da OpenAI, afirmou que esses alertas vindos de pessoas do setor reforçavam os argumentos em favor de uma pausa nas pesquisas.

“Nenhuma empresa de IA sequer chega perto de ter uma estrutura de segurança adequada ao nível de perigo envolvido em suas pesquisas”, afirmou Adler ao Financial Times. “Se alguém acredita que isso pode matar todas as pessoas da Terra, como acreditam muitos funcionários dessas empresas, este é um bom momento para descer do trem.”

The inside story on why OpenAI agents hacked Hugging Face (MIT Technology Review)

technologyreview.com

original article

Grace Huckins

August 26, 2026


The models responsible for last month’s agent hack of Hugging Face had been inadvertently trained to cheat and to communicate with each other, according to an OpenAI technical report released today. The hack, which a group of agents undertook to find solutions for a cybersecurity test that they were stuck on, has confirmed some experts’ fears that AI models might take actions that defy human desires and expectations. 

Since the hack, OpenAI employees—as well as researchers at the AI evaluation nonprofit METR, which released its own report on the hack today—have worked to understand what went wrong and how similar missteps might be prevented in the future. OpenAI has already put some preventative measures in place based on what they discovered. But making sure AI models do what we want them to do, or “alignment,” remains a gnarly problem, and some of the root causes of the hack will take much longer than a month to resolve.

“It’s not something you can solve overnight,” says Kai Chen, who runs OpenAI’s alignment research team. “There are challenges we’ve been tracking for a very long time, and we’re now seeing them with much greater precision.”

The Hugging Face hack was a product of months of misbehavior from OpenAI agents, first as they were being trained and then as their abilities were being evaluated. This May, agents in training figured out how to use OpenAI’s infrastructure to communicate with one another and get support with difficult training tasks, including some that were impossible to solve without hacking or otherwise misbehaving. That “message board” was shut down.

Then in July, while being evaluated for their cybersecurity abilities, some models created a new message board. They were supposed to be isolated from the internet, but by working together they managed to get online, hack Hugging Face, and obtain solutions for the cybersecurity problems that had stumped them.

Based on their investigation, OpenAI researchers believe that events during the training phase led directly to the hack. “For almost every behavior that was worrisome at evaluation time, [we were able to] find some sort of associated behavior at training time that actually we think might have contributed to it,” says Eric Wallace, a member of OpenAI’s alignment research team. 

When models correctly solve problems during training, the behaviors that led them to that solution are reinforced, and they become more likely to engage in them in the future. So if a model completed a task in May after using the original message board, it became more likely to participate in a new message board later on. This phenomenon, where AI agents misbehave in ways that are reinforced during the training process, is known as reward hacking.

Reward hacking also helps to explain why the models worked so hard to make their way onto the internet. During its investigation of the incident, the OpenAI team found that, over the course of training, the models became more and more likely to probe their digital environment for weaknesses and use the tools at their disposal in unexpected ways—a sign that these behaviors were being gradually reinforced. By the time the models were facing tricky cybersecurity problems, they had learned that hacking was an effective way to achieve their goals.

These results suggest that the Hugging Face hack could have been avoided if the models weren’t rewarded for misbehaving during training. While researchers don’t yet know how to prevent reward hacking entirely, OpenAI is taking some steps toward mitigating its effects. The company will now look for signs of cheating in all frontier models during training by keeping an eye on their chains of thought—internal notepads where they sketch out their answers and plan their actions. 

This solution isn’t as much of a slam dunk as it might seem: In earlier research, OpenAI showed that punishing models that mention cheating in their chains of thought teaches them to keep their intentions hidden from researchers. But monitoring its models’ thinking does give OpenAI the chance to halt the training process and reassess its approach if models do start learning to reward hack.

If OpenAI stops reinforcing reward hacking in its models—and that’s a huge “if”—that would be a huge step forward. But it wouldn’t solve the alignment problem. The first time a model communicated with other agents or hacked its infrastructure during training, those behaviors had never been reinforced, so agent misbehavior can’t only be attributed to that reinforcement.

Jeffrey Ladish, director of the AI safety nonprofit Palisade Research, compares the agents to a human who commits their first financial crime. “It’s not like they had to do fraud before to figure out that fraud is an effective strategy, and you have the same problem with models,” Ladish says. “Alignment science needs to be understanding how model motivations get shaped, such that we can actually figure out how to get models to care about the consequences of their actions.”

OpenAI’s researchers do have a hypothesis for where some of the misbehavior originated. Before the models formed their first secret message board, they had been trained to communicate and coordinate with subagents—less powerful agents to whom a main agent can delegate tasks. 

That learned communication behavior could have transferred to this new setting. The METR report, which investigates the messages that the models sent to one another in detail, supports this hypothesis: One agent on the message board took charge and assigned tasks to the other agents, effectively treating them as subagents. OpenAI could try to prevent agents from secretly communicating with one another by not training this subagent behavior in the future, but that would make the models less useful. 

This tension between capability and safety is at the heart of what went wrong with the Hugging Face incident. OpenAI researchers also identified the models’ persistence as a key factor in the hack. 

When they were accidentally given unsolvable problems, the models didn’t give up; instead, they strove to find solutions by any means necessary. But persistence is also a virtue, of course, especially if we want agents that can undertake large amounts of difficult work independently.

OpenAI is working on giving models ways to alert humans if they are given impossible tasks. The problem of teaching models when they should deploy their abilities and when they should hold back, however, won’t be settled in a single postmortem. The training strategies that create superhuman coders—rewarding them when they successfully solve problems—might not work to teach models to use their skills judiciously and respect human desires and values.

“I think there’s a bunch of alignment science that still needs to be done where we can move past just using proxies for task completion,” says Ladish. “That will work to make models very capable, but I don’t think it will work to make them aligned.”

Anti-AI extremism is taking a darker turn (The Deep View)

Original post

May 27, 2026

Nat Rubio-Licht

As much as Silicon Valley is all-in on AI, the rest of the world isn’t nearly as enthusiastic.

On Tuesday, a WIRED report found that the Department of Homeland Security, the FBI and other agencies are sounding the alarm about anti-technology extremism as concerns mount over AI-powered job displacement and protests rise against the construction of AI data centers. As a result, these agencies are closely surveilling news related to these sentiments.

In one of thousands of documents viewed by WIRED, the New York Intelligence and Counterterrorism Bureau claimed that AI could cause “large-scale protests that devolve into civil unrest and anti-tech violent extremist activity.”

Another document, from an agency in Western Pennsylvania, claimed that adversarial actors and extremist groups may target US data centers and generally “exploit the strategic importance of data centers to the US economy.”

It’s the latest signal that AI sentiment isn’t matching the heightened expectations of tech elites. Two recent Gallup polls find that Americans’ opinions towards AI are largely negative:

  • In May, a poll related to data centers found that an average of 7 in 10 Americans opposed the construction of AI infrastructure in their region, largely due to environmental impacts and quality-of-life concerns.
  • And in April, a poll of people ages 14 to 29 found that excitement about AI dropped by 14 percentage points since 2025, with many reporting that they don’t want to use AI but feel they must to keep their jobs.

And it makes sense why people have such negative associations with the tech. Almost every week, a new study or forecast is published claiming that AI could fundamentally disrupt the global economy, eliminate jobs, and hinder our ability to think for ourselves. Data centers, similarly, have a bad reputation due to their potential environmental impact, energy demand and impact on water supply.

The grand AI utopian vision tech leaders paint about the future will not be possible without large-scale adoption by the broader public. But that adoption will not happen if sentiment towards the tech doesn’t increase. For the narrative to improve, people need to feel they’re not being forced to use a technology that threatens to replace them. It’s why enterprises should think carefully before blaming AI for layoffs or forcing the tech on their employees. Almost universally, people resent being coerced into change. And when they feel they have no agency, it breeds the kind of extremism that US agencies are now tracking more closely.

A real-time revolution will up-end the practice of macroeconomics (The Economist)

economist.com

The Economist Oct 23rd 2021


DOES ANYONE really understand what is going on in the world economy? The pandemic has made plenty of observers look clueless. Few predicted $80 oil, let alone fleets of container ships waiting outside Californian and Chinese ports. As covid-19 let rip in 2020, forecasters overestimated how high unemployment would be by the end of the year. Today prices are rising faster than expected and nobody is sure if inflation and wages will spiral upward. For all their equations and theories, economists are often fumbling in the dark, with too little information to pick the policies that would maximise jobs and growth.

Yet, as we report this week, the age of bewilderment is starting to give way to greater enlightenment. The world is on the brink of a real-time revolution in economics, as the quality and timeliness of information are transformed. Big firms from Amazon to Netflix already use instant data to monitor grocery deliveries and how many people are glued to “Squid Game”. The pandemic has led governments and central banks to experiment, from monitoring restaurant bookings to tracking card payments. The results are still rudimentary, but as digital devices, sensors and fast payments become ubiquitous, the ability to observe the economy accurately and speedily will improve. That holds open the promise of better public-sector decision-making—as well as the temptation for governments to meddle.

The desire for better economic data is hardly new. America’s GNP estimates date to 1934 and initially came with a 13-month time lag. In the 1950s a young Alan Greenspan monitored freight-car traffic to arrive at early estimates of steel production. Ever since Walmart pioneered supply-chain management in the 1980s private-sector bosses have seen timely data as a source of competitive advantage. But the public sector has been slow to reform how it works. The official figures that economists track—think of GDP or employment—come with lags of weeks or months and are often revised dramatically. Productivity takes years to calculate accurately. It is only a slight exaggeration to say that central banks are flying blind.

Bad and late data can lead to policy errors that cost millions of jobs and trillions of dollars in lost output. The financial crisis would have been a lot less harmful had the Federal Reserve cut interest rates to near zero in December 2007, when America entered recession, rather than in December 2008, when economists at last saw it in the numbers. Patchy data about a vast informal economy and rotten banks have made it harder for India’s policymakers to end their country’s lost decade of low growth. The European Central Bank wrongly raised interest rates in 2011 amid a temporary burst of inflation, sending the euro area back into recession. The Bank of England may be about to make a similar mistake today.

The pandemic has, however, become a catalyst for change. Without the time to wait for official surveys to reveal the effects of the virus or lockdowns, governments and central banks have experimented, tracking mobile phones, contactless payments and the real-time use of aircraft engines. Instead of locking themselves in their studies for years writing the next “General Theory”, today’s star economists, such as Raj Chetty at Harvard University, run well-staffed labs that crunch numbers. Firms such as JPMorgan Chase have opened up treasure chests of data on bank balances and credit-card bills, helping reveal whether people are spending cash or hoarding it.

These trends will intensify as technology permeates the economy. A larger share of spending is shifting online and transactions are being processed faster. Real-time payments grew by 41% in 2020, according to McKinsey, a consultancy (India registered 25.6bn such transactions). More machines and objects are being fitted with sensors, including individual shipping containers that could make sense of supply-chain blockages. Govcoins, or central-bank digital currencies (CBDCs), which China is already piloting and over 50 other countries are considering, might soon provide a goldmine of real-time detail about how the economy works.

Timely data would cut the risk of policy cock-ups—it would be easier to judge, say, if a dip in activity was becoming a slump. And the levers governments can pull will improve, too. Central bankers reckon it takes 18 months or more for a change in interest rates to take full effect. But Hong Kong is trying out cash handouts in digital wallets that expire if they are not spent quickly. CBDCs might allow interest rates to fall deeply negative. Good data during crises could let support be precisely targeted; imagine loans only for firms with robust balance-sheets but a temporary liquidity problem. Instead of wasteful universal welfare payments made through social-security bureaucracies, the poor could enjoy instant income top-ups if they lost their job, paid into digital wallets without any paperwork.

The real-time revolution promises to make economic decisions more accurate, transparent and rules-based. But it also brings dangers. New indicators may be misinterpreted: is a global recession starting or is Uber just losing market share? They are not as representative or free from bias as the painstaking surveys by statistical agencies. Big firms could hoard data, giving them an undue advantage. Private firms such as Facebook, which launched a digital wallet this week, may one day have more insight into consumer spending than the Fed does.

Know thyself

The biggest danger is hubris. With a panopticon of the economy, it will be tempting for politicians and officials to imagine they can see far into the future, or to mould society according to their preferences and favour particular groups. This is the dream of the Chinese Communist Party, which seeks to engage in a form of digital central planning.

In fact no amount of data can reliably predict the future. Unfathomably complex, dynamic economies rely not on Big Brother but on the spontaneous behaviour of millions of independent firms and consumers. Instant economics isn’t about clairvoyance or omniscience. Instead its promise is prosaic but transformative: better, timelier and more rational decision-making. ■

economist.com

Enter third-wave economics

Oct 23rd 2021


AS PART OF his plan for socialism in the early 1970s, Salvador Allende created Project Cybersyn. The Chilean president’s idea was to offer bureaucrats unprecedented insight into the country’s economy. Managers would feed information from factories and fields into a central database. In an operations room bureaucrats could see if production was rising in the metals sector but falling on farms, or what was happening to wages in mining. They would quickly be able to analyse the impact of a tweak to regulations or production quotas.

Cybersyn never got off the ground. But something curiously similar has emerged in Salina, a small city in Kansas. Salina311, a local paper, has started publishing a “community dashboard” for the area, with rapid-fire data on local retail prices, the number of job vacancies and more—in effect, an electrocardiogram of the economy.

What is true in Salina is true for a growing number of national governments. When the pandemic started last year bureaucrats began studying dashboards of “high-frequency” data, such as daily airport passengers and hour-by-hour credit-card-spending. In recent weeks they have turned to new high-frequency sources, to get a better sense of where labour shortages are worst or to estimate which commodity price is next in line to soar. Economists have seized on these new data sets, producing a research boom (see chart 1). In the process, they are influencing policy as never before.

This fast-paced economics involves three big changes. First, it draws on data that are not only abundant but also directly relevant to real-world problems. When policymakers are trying to understand what lockdowns do to leisure spending they look at live restaurant reservations; when they want to get a handle on supply-chain bottlenecks they look at day-by-day movements of ships. Troves of timely, granular data are to economics what the microscope was to biology, opening a new way of looking at the world.

Second, the economists using the data are keener on influencing public policy. More of them do quick-and-dirty research in response to new policies. Academics have flocked to Twitter to engage in debate.

And, third, this new type of economics involves little theory. Practitioners claim to let the information speak for itself. Raj Chetty, a Harvard professor and one of the pioneers, has suggested that controversies between economists should be little different from disagreements among doctors about whether coffee is bad for you: a matter purely of evidence. All this is causing controversy among dismal scientists, not least because some, such as Mr Chetty, have done better from the shift than others: a few superstars dominate the field.

Their emerging discipline might be called “third wave” economics. The first wave emerged with Adam Smith and the “Wealth of Nations”, published in 1776. Economics mainly involved books or papers written by one person, focusing on some big theoretical question. Smith sought to tear down the monopolistic habits of 18th-century Europe. In the 20th century John Maynard Keynes wanted people to think differently about the government’s role in managing the economic cycle. Milton Friedman aimed to eliminate many of the responsibilities that politicians, following Keynes’s ideas, had arrogated to themselves.

All three men had a big impact on policies—as late as 1850 Smith was quoted 30 times in Parliament—but in a diffuse way. Data were scarce. Even by the 1970s more than half of economics papers focused on theory alone, suggests a study published in 2012 by Daniel Hamermesh, an economist.

That changed with the second wave of economics. By 2011 purely theoretical papers accounted for only 19% of publications. The growth of official statistics gave wonks more data to work with. More powerful computers made it easier to spot patterns and ascribe causality (this year’s Nobel prize was awarded for the practice of identifying cause and effect). The average number of authors per paper rose, as the complexity of the analysis increased (see chart 2). Economists had greater involvement in policy: rich-world governments began using cost-benefit analysis for infrastructure decisions from the 1950s.

Second-wave economics nonetheless remained constrained by data. Most national statistics are published with lags of months or years. “The traditional government statistics weren’t really all that helpful—by the time they came out, the data were stale,” says Michael Faulkender, an assistant treasury secretary in Washington at the start of the pandemic. The quality of official local economic data is mixed, at best; they do a poor job of covering the housing market and consumer spending. National statistics came into being at a time when the average economy looked more industrial, and less service-based, than it does now. The Standard Industrial Classification, introduced in 1937-38 and still in use with updates, divides manufacturing into 24 subsections, but the entire financial industry into just three.

The mists of time

Especially in times of rapid change, policymakers have operated in a fog. “If you look at the data right now…we are not in what would normally be characterised as a recession,” argued Edward Lazear, then chairman of the White House Council of Economic Advisers, in May 2008. Five months later, after Lehman Brothers had collapsed, the IMF noted that America was “not necessarily” heading for a deep recession. In fact America had entered a recession in December 2007. In 2007-09 there was no surge in economics publications. Economists’ recommendations for policy were mostly based on judgment, theory and a cursory reading of national statistics.

The gap between official data and what is happening in the real economy can still be glaring. Walk around a Walmart in Kansas and many items, from pet food to bottled water, are in short supply. Yet some national statistics fail to show such problems. Dean Baker of the Centre for Economic and Policy Research, using official data, points out that American real inventories, excluding cars and farm products, are barely lower than before the pandemic.

There were hints of an economics third wave before the pandemic. Some economists were finding new, extremely detailed streams of data, such as anonymised tax records and location information from mobile phones. The analysis of these giant data sets requires the creation of what are in effect industrial labs, teams of economists who clean and probe the numbers. Susan Athey, a trailblazer in applying modern computational methods in economics, has 20 or so non-faculty researchers at her Stanford lab (Mr Chetty’s team boasts similar numbers). Of the 20 economists with the most cited new work during the pandemic, three run industrial labs.

More data sprouted from firms. Visa and Square record spending patterns, Apple and Google track movements, and security companies know when people go in and out of buildings. “Computers are in the middle of every economic arrangement, so naturally things are recorded,” says Jon Levin of Stanford’s Graduate School of Business. Jamie Dimon, the boss of JPMorgan Chase, a bank, is an unlikely hero of the emergence of third-wave economics. In 2015 he helped set up an institute at his bank which tapped into data from its network to analyse questions about consumer finances and small businesses.

The Brexit referendum of June 2016 was the first big event when real-time data were put to the test. The British government and investors needed to get a sense of this unusual shock long before Britain’s official GDP numbers came out. They scraped web pages for telltale signs such as restaurant reservations and the number of supermarkets offering discounts—and concluded, correctly, that though the economy was slowing, it was far from the catastrophe that many forecasters had predicted.

Real-time data might have remained a niche pursuit for longer were it not for the pandemic. Chinese firms have long produced granular high-frequency data on everything from cinema visits to the number of glasses of beer that people are drinking daily. Beer-and-movie statistics are a useful cross-check against sometimes dodgy official figures. China-watchers turned to them in January 2020, when lockdowns began in Hubei province. The numbers showed that the world’s second-largest economy was heading for a slump. And they made it clear to economists elsewhere how useful such data could be.

Vast and fast

In the early days of the pandemic Google started releasing anonymised data on people’s physical movements; this has helped researchers produce a day-by-day measure of the severity of lockdowns (see chart 3). OpenTable, a booking platform, started publishing daily information on restaurant reservations. America’s Census Bureau quickly introduced a weekly survey of households, asking them questions ranging from their employment status to whether they could afford to pay the rent.

In May 2020 Jose Maria Barrero, Nick Bloom and Steven Davis, three economists, began a monthly survey of American business practices and work habits. Working-age Americans are paid to answer questions on how often they plan to visit the office, say, or how they would prefer to greet a work colleague. “People often complete a survey during their lunch break,” says Mr Bloom, of Stanford University. “They sit there with a sandwich, answer some questions, and that pays for their lunch.”

Demand for research to understand a confusing economic situation jumped. The first analysis of America’s $600 weekly boost to unemployment insurance, implemented in March 2020, was published in weeks. The British government knew by October 2020 that a scheme to subsidise restaurant attendance in August 2020 had probably boosted covid infections. Many apparently self-evident things about the pandemic—that the economy collapsed in March 2020, that the poor have suffered more than the rich, or that the shift to working from home is turning out better than expected—only seem obvious because of rapid-fire economic research.

It is harder to quantify the policy impact. Some economists scoff at the notion that their research has influenced politicians’ pandemic response. Many studies using real-time data suggested that the Paycheck Protection Programme, an effort to channel money to American small firms, was doing less good than hoped. Yet small-business lobbyists ensured that politicians did not get rid of it for months. Tyler Cowen, of George Mason University, points out that the most significant contribution of economists during the pandemic involved recommending early pledges to buy vaccines—based on older research, not real-time data.

Still, Mr Faulkender says that the special support for restaurants that was included in America’s stimulus was influenced by a weak recovery in the industry seen in the OpenTable data. Research by Mr Chetty in early 2021 found that stimulus cheques sent in December boosted spending by lower-income households, but not much for richer households. He claims this informed the decision to place stronger income limits on the stimulus cheques sent in March.

Shaping the economic conversation

As for the Federal Reserve, in May 2020 the Dallas and New York regional Feds and James Stock, a Harvard economist, created an activity index using data from SafeGraph, a data provider that tracks mobility using mobile-phone pings. The St Louis Fed used data from Homebase to track employment numbers daily. Both showed shortfalls of economic activity in advance of official data. This led the Fed to communicate its doveish policy stance faster.

Speedy data also helped frame debate. Everyone realised the world was in a deep recession much sooner than they had in 2007-09. In the IMF’s overviews of the global economy in 2009, 40% of the papers cited had been published in 2008-09. In the overview published in October 2020, by contrast, over half the citations were for papers published that year.

The third wave of economics has been better for some practitioners than others. As lockdowns began, many male economists found themselves at home with no teaching responsibilities and more time to do research. Female ones often picked up the slack of child care. A paper in Covid Economics, a rapid-fire journal, finds that female authors accounted for 12% of economics working-paper submissions during the pandemic, compared with 20% before. Economists lucky enough to have researched topics before the pandemic which became hot, from home-working to welfare policy, were suddenly in demand.

There are also deeper shifts in the value placed on different sorts of research. The Economist has examined rankings of economists from IDEAS RePEC, a database of research, and citation data from Google Scholar. We divided economists into three groups: “lone wolves” (who publish with less than one unique co-author per paper on average); “collaborators” (those who tend to work with more than one unique co-author per paper, usually two to four people); and “lab leaders” (researchers who run a large team of dedicated assistants). We then looked at the top ten economists for each as measured by RePEC author rankings for the past ten years.

Collaborators performed far ahead of the other two groups during the pandemic (see chart 4). Lone wolves did worst: working with large data sets benefits from a division of labour. Why collaborators did better than lab leaders is less clear. They may have been more nimble in working with those best suited for the problems at hand; lab leaders are stuck with a fixed group of co-authors and assistants.

The most popular types of research highlight another aspect of the third wave: its usefulness for business. Scott Baker, another economist, and Messrs Bloom and Davis—three of the top four authors during the pandemic compared with the year before—are all “collaborators” and use daily newspaper data to study markets. Their uncertainty index has been used by hedge funds to understand the drivers of asset prices. The research by Messrs Bloom and Davis on working from home has also gained attention from businesses seeking insight on the transition to remote work.

But does it work in theory?

Not everyone likes where the discipline is going. When economists say that their fellows are turning into data scientists, it is not meant as a compliment. A kinder interpretation is that the shift to data-heavy work is correcting a historical imbalance. “The most important problem with macro over the past few decades has been that it has been too theoretical,” says Jón Steinsson of the University of California, Berkeley, in an essay published in July. A better balance with data improves theory. Half of the recent Nobel prize went for the application of new empirical methods to labour economics; the other half was for the statistical theory around such methods.

Some critics question the quality of many real-time sources. High-frequency data are less accurate at estimating levels (for example, the total value of GDP) than they are at estimating changes, and in particular turning-points (such as when growth turns into recession). In a recent review of real-time indicators Samuel Tombs of Pantheon Macroeconomics, a consultancy, pointed out that OpenTable data tended to exaggerate the rebound in restaurant attendance last year.

Others have worries about the new incentives facing economists. Researchers now race to post a working paper with America’s National Bureau of Economic Research in order to stake their claim to an area of study or to influence policymakers. The downside is that consumers of fast-food academic research often treat it as if it is as rigorous as the slow-cooked sort—papers which comply with the old-fashioned publication process involving endless seminars and peer review. A number of papers using high-frequency data which generated lots of clicks, including one which claimed that a motorcycle rally in South Dakota had caused a spike in covid cases, have since been called into question.

Whatever the concerns, the pandemic has given economists a new lease of life. During the Chilean coup of 1973 members of the armed forces broke into Cybersyn’s operations room and smashed up the slides of graphs—not only because it was Allende’s creation, but because the idea of an electrocardiogram of the economy just seemed a bit weird. Third-wave economics is still unusual, but ever less odd. ■

Soon, satellites will be able to watch you everywhere all the time (MIT Technology Review)

Can privacy survive?

Christopher Beam

June 26, 2019


In 2013, police in Grants Pass, Oregon, got a tip that a man named Curtis W. Croft had been illegally growing marijuana in his backyard. So they checked Google Earth. Indeed, the four-month-old satellite image showed neat rows of plants growing on Croft’s property. The cops raided his place and seized 94 plants.

In 2018, Brazilian police in the state of Amapá used real-time satellite imagery to detect a spot where trees had been ripped out of the ground. When they showed up, they discovered that the site was being used to illegally produce charcoal, and arrested eight people in connection with the scheme.

Chinese government officials have denied or downplayed the existence of Uighur reeducation camps in Xinjiang province, portraying them as “vocational schools.” But human rights activists have used satellite imagery to show that many of the “schools” are surrounded by watchtowers and razor wire.

Every year, commercially available satellite images are becoming sharper and taken more frequently. In 2008, there were 150 Earth observation satellites in orbit; by now there are 768. Satellite companies don’t offer 24-hour real-time surveillance, but if the hype is to be believed, they’re getting close. Privacy advocates warn that innovation in satellite imagery is outpacing the US government’s (to say nothing of the rest of the world’s) ability to regulate the technology. Unless we impose stricter limits now, they say, one day everyone from ad companies to suspicious spouses to terrorist organizations will have access to tools previously reserved for government spy agencies. Which would mean that at any given moment, anyone could be watching anyone else.

The images keep getting clearer

Commercial satellite imagery is currently in a sweet spot: powerful enough to see a car, but not enough to tell the make and model; collected frequently enough for a farmer to keep tabs on crops’ health, but not so often that people could track the comings and goings of a neighbor. This anonymity is deliberate. US federal regulations limit images taken by commercial satellites to a resolution of 25 centimeters, or about the length of a man’s shoe. (Military spy satellites can capture images far more granular, although just how much more is classified.)

Ever since 2014, when the National Oceanic and Atmospheric Administration (NOAA) relaxed the limit from 50 to 25 cm, that resolution has been fine enough to satisfy most customers. Investors can predict oil supply from the shadows cast inside oil storage tanks. Farmers can monitor flooding to protect their crops. Human rights organizations have tracked the flows of refugees from Myanmar and Syria.

But satellite imagery is improving in a way that investors and businesses will inevitably want to exploit. The imaging company Planet Labs currently maintains 140 satellites, enough to pass over every place on Earth once a day. Maxar, formerly DigitalGlobe, which launched the first commercial Earth observation satellite in 1997, is building a constellation that will be able to revisit spots 15 times a day. BlackSky Global promises to revisit most major cities up to 70 times a day. That might not be enough to track an individual’s every move, but it would show what times of day someone’s car is typically in the driveway, for instance.

Some companies are even offering live video from space. As early as 2014, a Silicon Valley startup called SkyBox (later renamed Terra Bella and purchased by Google and then Planet) began touting HD video clips up to 90 seconds long. And a company called EarthNow says it will offer “continuous real-time” monitoring “with a delay as short as about one second,” though some think it is overstating its abilities. Everyone is trying to get closer to a “living map,” says Charlie Loyd of Mapbox, which creates custom maps for companies like Snapchat and the Weather Channel. But it won’t arrive tomorrow, or the next day: “We’re an extremely long way from high-res, full-time video of the Earth.”

Some of the most radical developments in Earth observation involve not traditional photography but rather radar sensing and hyperspectral images, which capture electromagnetic wavelengths outside the visible spectrum. Clouds can hide the ground in visible light, but satellites can penetrate them using synthetic aperture radar, which emits a signal that bounces off the sensed object and back to the satellite. It can determine the height of an object down to a millimeter. NASA has used synthetic aperture radar since the 1970s, but the fact that the US approved it for commercial use only last year is testament to its power—and political sensitivity. (In 1978, military officials supposedly blocked the release of radar satellite images that revealed the location of American nuclear submarines.)

While GPS data from cell phones is a legitimate privacy threat, you can at least decide to leave your phone at home. It’s harder to hide from a satellite camera.

Meanwhile, farmers can use hyperspectral sensing to tell where a crop is in its growth cycle, and geologists can use it to detect the texture of rock that might be favorable to excavation. But it could also be used, whether by military agencies or terrorists, to identify underground bunkers or nuclear materials. 

The resolution of commercially available imagery, too, is likely to improve further. NOAA’s 25-centimeter cap will come under pressure as competition from international satellite companies increases. And even if it doesn’t, there’s nothing to stop, say, a Chinese company from capturing and selling 10 cm images to American customers. “Other companies internationally are going to start providing higher-­resolution imagery than we legally allow,” says Therese Jones, senior director of policy for the Satellite Industry Association. “Our companies would want to push the limit down as far as they possibly could.”

What will make the imagery even more powerful is the ability to process it in large quantities. Analytics companies like Orbital Insight and SpaceKnow feed visual data into algorithms designed to let anyone with an internet connection understand the pictures en masse. Investors use this analysis to, for example, estimate the true GDP of China’s Guangdong province on the basis of the light it emits at night. But burglars could also scan a city to determine which families are out of town most often and for how long.

Satellite and analytics companies say they’re careful to anonymize their data, scrubbing it of identifying characteristics. But even if satellites aren’t recognizing faces, those images combined with other data streams—GPS, security cameras, social-media posts—could pose a threat to privacy. “People’s movements, what kinds of shops do you go to, where do your kids go to school, what kind of religious institutions do you visit, what are your social patterns,” says Peter Martinez, of the Secure World Foundation. “All of these kinds of questions could in principle be interrogated, should someone be interested.”

Like all tools, satellite imagery is subject to misuse. Its apparent objectivity can lead to false conclusions, as when the George W. Bush administration used it to make the case that Saddam Hussein was stockpiling chemical weapons in Iraq. Attempts to protect privacy can also backfire: in 2018, a Russian mapping firm blurred out the sites of sensitive military operations in Turkey and Israel—inadvertently revealing their existence, and prompting web users to locate the sites on other open-source maps.

Capturing satellite imagery with good intentions can have unintended consequences too. In 2012, as conflict raged on the border between Sudan and South Sudan, the Harvard-based Satellite Sentinel Project released an image that showed a construction crew building a tank-capable road leading toward an area occupied by the Sudanese People’s Liberation Army. The idea was to warn citizens about the approaching tanks so they could evacuate. But the SPLA saw the images too, and within 36 hours it attacked the road crew (which turned out to consist of Chinese civilians hired by the Sudanese government), killed some of them, and kidnapped the rest. As an activist, one’s instinct is often to release more information, says Nathaniel Raymond, a human rights expert who led the Sentinel project. But he’s learned that you have to take into account who else might be watching.

It’s expensive to watch you all the time

One thing that might save us from celestial scrutiny is the price. Some satellite entrepreneurs argue that there isn’t enough demand to pay for a constellation of satellites capable of round-the-clock monitoring at resolutions below 25 cm. “It becomes a question of economics,” says Walter Scott, founder of DigitalGlobe, now Maxar. While some companies are launching relatively cheap “nanosatellites” the size of toasters—the 120 Dove satellites launched by Planet, for example, are “orders of magnitude” cheaper than traditional satellites, according to a spokesperson—there’s a limit to how small they can get and still capture hyper-detailed images. “It is a fundamental fact of physics that aperture size determines the limit on the resolution you can get,” says Scott. “At a given altitude, you need a certain size telescope.” That is, in Maxar’s case, an aperture of about a meter across, mounted on a satellite the size of a small school bus. (While there are ways around this limit—interferometry, for example, uses multiple mirrors to simulate a much larger mirror—they’re complex and pricey.) Bigger satellites mean costlier launches, so companies would need a financial incentive to collect such granular data.

That said, there’s already demand for imagery with sub–25 cm resolution—and a supply of it. For example, some insurance underwriters need that level of detail to spot trees overhanging a roof, or to distinguish a skylight from a solar panel, and they can get it from airplanes and drones. But if the cost of satellite images came down far enough, insurance companies would presumably switch over.

Of course, drones can already collect better images than satellites ever will. But drones are limited in where they can go. In the US, the Federal Aviation Administration forbids flying commercial drones over groups of people, and you have to register a drone that weighs more than half a pound (227 grams) or so. There are no such restrictions in space. The Outer Space Treaty, signed in 1967 by the US, the Soviet Union, and dozens of UN member states, gives all states free access to space, and subsequent agreements on remote sensing have enshrined the principle of “open skies.” During the Cold War this made sense, as it allowed superpowers to monitor other countries to verify that they were sticking to arms agreements. But the treaty didn’t anticipate that it would one day be possible for anyone to get detailed images of almost any location.

And then there are the tracking devices we carry around in our pockets, a.k.a. smartphones. But while the GPS data from cell  phones is a legitimate privacy threat, you can at least decide to leave your phone at home. It’s harder to hide from a satellite camera. “There’s some element of ground truth—no pun intended—that satellites have that maybe your cell phone or digital record or what happens on Twitter [doesn’t],” says Abraham Thomas, chief data officer at the analytics company Quandl. “The data itself tends to be innately more accurate.”

The future of human freedom

American privacy laws are vague when it comes to satellites. Courts have generally allowed aerial surveillance, though in 2015 the New Mexico Supreme Court ruled that an “aerial search” by police without a warrant was unconstitutional. Cases often come down to whether an act of surveillance violates someone’s “reasonable expectation of privacy.” A picture taken on a public sidewalk: fair game. A photo shot by a drone through someone’s bedroom window: probably not. A satellite orbiting hundreds of miles up, capturing video of a car pulling into the driveway? Unclear.

That doesn’t mean the US government is powerless. It has no jurisdiction over Chinese or Russian satellites, but it can regulate how American customers use foreign imagery. If US companies are profiting from it in a way that violates the privacy of US citizens, the government could step in.

Raymond argues that protecting ourselves will mean rethinking privacy itself. Current privacy laws, he says, focus on threats to the rights of individuals. But those protections “are anachronistic in the face of AI, geospatial technologies, and mobile technologies, which not only use group data, they run on group data as gas in the tank,” Raymond says. Regulating these technologies will mean conceiving of privacy as applying not just to individuals, but to groups as well. “You can be entirely ethical about personally identifiable information and still kill people,” he says.

Until we can all agree on data privacy norms, Raymond says, it will be hard to create lasting rules around satellite imagery. “We’re all trying to figure this out,” he says. “It’s not like anything’s riding on it except the future of human freedom.”

Christopher Beam is a writer based in Los Angeles.

The space issue

This story was part of our July 2019 issue

Half of Fox News Viewers Believe Bill Gates Wants to Use Virus Vaccines to Track You, New Poll Says (Rolling Stone)

May 22, 2020 5:00PM ET

Misinformation is taking a dangerous hold on Fox News viewers

By Peter Wade

Fox News Viewers Believe Bill Gates Wants Track You Through Vaccines
Two women hold anti-vaccination signs during a protest against Governor Jay Inslee’s stay-at-home order outside the State Capitol in Olympia, Washington on May 9, 2020.
JASON REDMOND/AFP/Getty Images

Misinformation is taking a dangerous hold on Fox News viewers. According to a new poll, half of all Americans who name Fox News as their primary news source believe the debunked conspiracy theory claiming Bill Gates is looking to use a coronavirus vaccine to inject a microchip into people and track the world’s population.

The Yahoo News/YouGov poll, released on Friday, found that 44 percent of Republicans also buy into the unfounded claim, while just 19 percent of Democrats believe the lie about the Microsoft co-founder and philanthropist.

According to Yahoo’s report on the poll, neither Fox News nor President Trump has promoted the false Gates conspiracy. But sowing seeds of distrust of mainstream media and the spread of misinformation is a hallmark of the network and the current president. Last month, Fox primetime host Laura Ingraham shared a tweet where she expressed agreement with a user who wrote about the debunked conspiracy theory.

“Digitally tracking Americans’ every move has been a dream of the globalists for years. This health crisis is the perfect vehicle for them to push this,” Ingraham wrote.

The poll also found that just 15 percent of MSNBC viewers believe the untrue conspiracy theory which, according to the fact-checking publication Snopes, began with the anti-vaccine movement. They chose to target Gates specifically because of his decade-long advocacy for vaccines.

According to an April report in the New York Times that looked into the right-wing targeting of Gates, media analysis company Zignal Labs found that “misinformation about Gates is now the most widespread of all coronavirus falsehoods” that the company has tracked.

This debunked conspiracy theory could be especially menacing if it deters any portion of the population from getting vaccinated, if and when one becomes available, which would then make it much tougher to rid the world of the virus.

In another poll released on Friday by Reuters/Ipsos showed increasing mistrust in the president due to his consistent habit of sharing misinformation. Thirty-six percent of those surveyed said they would be less willing to take a vaccine if it were endorsed by the president.

The picture these polls paint is both sad and obviously dangerous for all of us, especially with the current pandemic. Unfortunately, our country’s lack of trustworthy leadership means that more and more people are susceptible to bad and untrue advice that is rampant on random Reddit forums, Facebook posts and, yes, even TikTok — where conspiracy theories are paired with viral dances.

O coronavírus de hoje e o mundo de amanhã, segundo o filósofo Byung-Chul Han (El País)

Países asiáticos estão lidando melhor com essa crise do que o Ocidente. Enquanto lá se trabalha com dados e máscaras, aqui se chega tarde e fecham fronteiras

Byung-Chul Han – 22 mar 2020 – 20:01 BRT

Um oficial de polícia vigia diante de um cartaz dia 23 de janeiro em Pequim.
Um oficial de polícia vigia diante de um cartaz dia 23 de janeiro em Pequim.Kevin Frayer/Getty Images

O coronavírus está colocando nosso sistema à prova. Ao que parece a Ásia controla melhor a epidemia do que a Europa. Em Hong Kong, Taiwan e Singapura há poucos infectados. Em Taiwan foram registrados 108 casos e 193 em Hong Kong. Na Alemanha, pelo contrário, após um período muito mais breve já existem 19.000 casos confirmados, e na Espanha 19.980 (dados de 20 de março). A Coreia do Sul já superou a pior fase, da mesma forma que o Japão. Até a China, o país de origem da pandemia, já está com ela bem controlada. Mas Taiwan e a Coreia não decretaram a proibição de sair de casa e as lojas e restaurantes não fecharam. Enquanto isso começou um êxodo de asiáticos que saem da Europa. Chineses e coreanos querem regressar aos seus países, porque lá se sentem mais seguros. Os preços dos voos multiplicaram. Já quase não é possível conseguir passagens aéreas para a China e a Coreia.

A Europa está fracassando. Os números de infectados aumentam exponencialmente. Parece que a Europa não pode controlar a pandemia. Na Itália morrem diariamente centenas de pessoas. Retiram os respiradores dos pacientes idosos para ajudar os jovens. Mas também vale observar ações inúteis. Os fechamentos de fronteiras são evidentemente uma expressão desesperada de soberania. Nós nos sentimos de volta à época da soberania. O soberano é quem decide sobre o estado de exceção. É o soberano que fecha fronteiras. Mas isso é uma vã tentativa de soberania que não serve para nada. Seria muito mais útil cooperar intensamente dentro da Eurozona do que fechar fronteiras alucinadamente. Ao mesmo tempo a Europa também decretou a proibição da entrada a estrangeiros: um ato totalmente absurdo levando em consideração o fato de que a Europa é justamente o local ao qual ninguém quer ir. No máximo, seria mais sensato decretar a proibição de saídas de europeus, para proteger o mundo da Europa. Depois de tudo, a Europa é nesse momento o epicentro da pandemia.

As vantagens da Ásia

Em comparação com a Europa, quais vantagens o sistema da Ásia oferece que são eficientes para combater a pandemia? Estados asiáticos como o Japão, Coreia, China, Hong Kong, Taiwan e Singapura têm uma mentalidade autoritária, que vem de sua tradição cultural (confucionismo). As pessoas são menos relutantes e mais obedientes do que na Europa. Também confiam mais no Estado. E não somente na China, como também na Europa e no Japão a vida cotidiana está organizada muito mais rigidamente do que na Europa. Principalmente para enfrentar o vírus os asiáticos apostam fortemente na vigilância digital. Suspeitam que o big data pode ter um enorme potencial para se defender da pandemia. Poderíamos dizer que na Ásia as epidemias não são combatidas somente pelos virologistas e epidemiologistas, e sim principalmente pelos especialistas em informática e macrodados. Uma mudança de paradigma da qual a Europa ainda não se inteirou. Os apologistas da vigilância digital proclamariam que o big data salva vidas humanas.

A consciência crítica diante da vigilância digital é praticamente inexistente na Ásia. Já quase não se fala de proteção de dados, incluindo Estados liberais como o Japão e a Coreia. Ninguém se irrita pelo frenesi das autoridades em recopilar dados. Enquanto isso a China introduziu um sistema de crédito social inimaginável aos europeus, que permitem uma valorização e avaliação exaustiva das pessoas. Cada um deve ser avaliado em consequência de sua conduta social. Na China não há nenhum momento da vida cotidiana que não esteja submetido à observação. Cada clique, cada compra, cada contato, cada atividade nas redes sociais são controlados. Quem atravessa no sinal vermelho, quem tem contato com críticos do regime e quem coloca comentários críticos nas redes sociais perde pontos. A vida, então, pode chegar a se tornar muito perigosa. Pelo contrário, quem compra pela Internet alimentos saudáveis e lê jornais que apoiam o regime ganha pontos. Quem tem pontuação suficiente obtém um visto de viagem e créditos baratos. Pelo contrário, quem cai abaixo de um determinado número de pontos pode perder seu trabalho. Na China essa vigilância social é possível porque ocorre uma irrestrita troca de dados entre os fornecedores da Internet e de telefonia celular e as autoridades. Praticamente não existe a proteção de dados. No vocabulário dos chineses não há o termo “esfera privada”.

Na China existem 200 milhões de câmeras de vigilância, muitas delas com uma técnica muito eficiente de reconhecimento facial. Captam até mesmo as pintas no rosto. Não é possível escapar da câmera de vigilância. Essas câmeras dotadas de inteligência artificial podem observar e avaliar qualquer um nos espaços públicos, nas lojas, nas ruas, nas estações e nos aeroportos.

Toda a infraestrutura para a vigilância digital se mostrou agora ser extremamente eficaz para conter a epidemia. Quando alguém sai da estação de Pequim é captado automaticamente por uma câmera que mede sua temperatura corporal. Se a temperatura é preocupante todas as pessoas que estavam sentadas no mesmo vagão recebem uma notificação em seus celulares. Não é por acaso que o sistema sabe quem estava sentado em qual local no trem. As redes sociais contam que estão usando até drones para controlar as quarentenas. Se alguém rompe clandestinamente a quarentena um drone se dirige voando em sua direção e ordena que regresse à sua casa. Talvez até lhe dê uma multa e a deixe cair voando, quem sabe. Uma situação que para os europeus seria distópica, mas que, pelo visto, não tem resistência na China.

Na China e em outros Estados asiáticos como a Coreia do Sul, Hong Kong, Singapura, Taiwan e Japão não existe uma consciência crítica diante da vigilância digital e o big data. A digitalização os embriaga diretamente. Isso obedece também a um motivo cultural. Na Ásia impera o coletivismo. Não há um individualismo acentuado. O individualismo não é a mesma coisa que o egoísmo, que evidentemente também está muito propagado na Ásia.

Ao que parece o big data é mais eficaz para combater o vírus do que os absurdos fechamentos de fronteiras que estão sendo feitos nesses momentos na Europa. Graças à proteção de dados, entretanto, não é possível na Europa um combate digital do vírus comparável ao asiático. Os fornecedores chineses de telefonia celular e de Internet compartilham os dados sensíveis de seus clientes com os serviços de segurança e com os ministérios de saúde. O Estado sabe, portanto, onde estou, com quem me encontro, o que faço, o que procuro, em que penso, o que como, o que compro, aonde me dirijo. É possível que no futuro o Estado controle também a temperatura corporal, o peso, o nível de açúcar no sangue etc. Uma biopolítica digital que acompanha a psicopolítica digital que controla ativamente as pessoas.

É possível que no futuro o Estado controle também a temperatura corporal, o peso, o nível de açúcar no sangue

Em Wuhan se formaram milhares de equipes de pesquisa digitais que procuram possíveis infectados baseando-se somente em dados técnicos. Tendo como base, unicamente, análises de macrodados averiguam os que são potenciais infectados, os que precisam continuar sendo observados e eventualmente isolados em quarentena. O futuro também está na digitalização no que se refere à pandemia. Pela epidemia talvez devêssemos redefinir até mesmo a soberania. É soberano quem dispõe de dados. Quando a Europa proclama o estado de alarme e fecha fronteiras continua aferrada a velhos modelos de soberania.

Não somente na China, como também em outros países asiáticos a vigilância digital é profundamente utilizada para conter a epidemia. Em Taiwan o Estado envia simultaneamente a todos um SMS para localizar as pessoas que tiveram contato com infectados e para informar sobre os lugares e edifícios em que existiram pessoas contaminadas. Já em uma fase muito inicial, Taiwan utilizou uma conexão de diversos dados para localizar possíveis infectados em função das viagens que fizeram. Na Coreia quem se aproxima de um edifício em que um infectado esteve recebe através do “Corona-app” um sinal de alarme. Todos os lugares em que infectados estiveram estão registrados no aplicativo. Não são levadas muito em consideração a proteção de dados e a esfera privada. Em todos os edifícios da Coreia foram instaladas câmeras de vigilância em cada andar, em cada escritório e em cada loja. É praticamente impossível se mover em espaços públicos sem ser filmado por uma câmera de vídeo. Com os dados do telefone celular e do material filmado por vídeo é possível criar o perfil de movimento completo de um infectado. São publicados os movimentos de todos os infectados. Casos amorosos secretos podem ser revelados. Nos escritórios do Ministério da Saúde coreano existem pessoas chamadas “tracker” que dia e noite não fazem outra coisa a não ser olhar o material filmado por vídeo para completar o perfil do movimento dos infectados e localizar as pessoas que tiveram contato com eles.

Chineses, todos de máscara, fazem fila no ponto de ônibus em Pequim, em 20 de março.
Chineses, todos de máscara, fazem fila no ponto de ônibus em Pequim, em 20 de março.Kevin Frayer / Getty Images

Uma diferença chamativa entre a Ásia e a Europa são principalmente as máscaras protetoras. Na Coreia quase não existe quem ande por aí sem máscaras respiratórias especiais capazes de filtrar o ar de vírus. Não são as habituais máscaras cirúrgicas, e sim máscaras protetoras especiais com filtros, que também são utilizadas pelos médicos que tratam os infectados. Durante as últimas semanas, o tema prioritário na Coreia era o fornecimento de máscaras à população. Diante das farmácias enormes filas se formaram. Os políticos eram avaliados em função da rapidez com que eram fornecidas a toda a população. Foram construídas a toda pressa novas máquinas para sua fabricação. Por enquanto parece que o fornecimento funciona bem. Há até mesmo um aplicativo que informa em qual farmácia próxima ainda se pode conseguir máscaras. Acho que as máscaras protetoras fornecidas na Ásia a toda a população contribuíram decisivamente para conter a epidemia.

Os coreanos usam máscaras protetoras antivírus até mesmo nos locais de trabalho. Até os políticos fazem suas aparições públicas somente com máscaras protetoras. O presidente coreano também a usa para dar o exemplo, incluindo em suas entrevistas coletivas. Na Coreia quem não a usa é repreendido. Na Europa, pelo contrário, frequentemente se diz que não servem para muita coisa, o que é um absurdo. Por que então os médicos usam as máscaras protetoras? Mas é preciso trocar de máscara frequentemente, porque quando umedecem perdem sua função filtradora. Os coreanos, entretanto, já desenvolveram uma “máscara ao coronavírus” feita de nanofiltros que podem ser lavados. O que se diz é que podem proteger as pessoas do vírus durante um mês. Na verdade, é uma solução muito boa enquanto não existem vacinas e medicamentos.

Está surgindo uma sociedade de duas classes. Quem tem carro próprio se expõe a menos riscos

Na Europa, pelo contrário, até mesmo os médicos precisam viajar à Rússia para consegui-las. Macron mandou confiscar máscaras para distribui-las entre os funcionários da área de saúde. Mas o que acabaram recebendo foram máscaras normais sem filtro com a indicação de que bastariam para proteger do coronavírus, o que é uma mentira. A Europa está fracassando. De que adianta fechar lojas e restaurantes se as pessoas continuam se aglomerando no metrô e no ônibus durante as horas de pico? Como guardar a distância necessária assim? Até nos supermercados é quase impossível. Em uma situação como essa, as máscaras protetoras realmente salvariam vidas humanas. Está surgindo uma sociedade de duas classes. Quem tem carro próprio se expõe a menos riscos. As máscaras normais também seriam de muita utilidade se os infectados as usassem, porque dessa maneira não propagariam o vírus.

Nos países europeus quase ninguém usa máscara. Há alguns que as usam, mas são asiáticos. Meus conterrâneos residentes na Europa se queixam de que são olhados com estranheza quando as usam. Por trás disso há uma diferença cultural. Na Europa impera um individualismo que traz atrelado o costume de andar com o rosto descoberto. Os únicos que estão mascarados são os criminosos. Mas agora, vendo imagens da Coreia, me acostumei tanto a ver pessoas mascaradas que o rosto descoberto de meus concidadãos europeus me parece quase obsceno. Eu também gostaria de usar máscara protetora, mas aqui já não existem.

No passado, a fabricação de máscara, da mesma forma que tantos outros produtos, foi externalizada à China. Por isso agora não se conseguem máscaras na Europa. Os Estados asiáticos estão tentando prover toda a população com máscaras protetoras. Na China, quando também começaram a escassear, fábricas chegaram a ser reequipadas para produzir máscaras. Na Europa nem mesmo os funcionários da área de saúde as conseguem. Enquanto as pessoas continuarem se aglomerando nos ônibus e metrôs para ir ao trabalho sem máscaras protetoras, a proibição de sair de casa logicamente não adiantará muito. Como é possível guardar a distância necessária nos ônibus e no metrô nos horários de pico? E uma lição que deveríamos tirar da pandemia deveria ser a conveniência de voltar a trazer à Europa a produção de determinados produtos, como máscaras protetoras, remédios e produtos farmacêuticos.

O presidente da Coreia do Su, terceiro na imagem, em 25 de fevereiro.
O presidente da Coreia do Su, terceiro na imagem, em 25 de fevereiro.South Korean Presidential Blue House/Getty Images / South Korean Presidential Blue H

Apesar de todo o risco, que não deve ser minimizado, o pânico desatado pela pandemia de coronavírus é desproporcional. Nem mesmo a “gripe espanhola”, que foi muito mais letal, teve efeitos tão devastadores sobre a economia. A que isso se deve na realidade? Por que o mundo reage com um pânico tão desmesurado a um vírus? Emmanuel Macron fala até de guerra e do inimigo invisível que precisamos derrotar. Estamos diante de um retorno do inimigo? A gripe espanhola se desencadeou em plena Primeira Guerra Mundial. Naquele momento todo o mundo estava cercado de inimigos. Ninguém teria associado a epidemia com uma guerra e um inimigo. Mas hoje vivemos em uma sociedade totalmente diferente.

Na verdade, vivemos durante muito tempo sem inimigos. A Guerra Fria terminou há muito tempo. Ultimamente até o terrorismo islâmico parecia ter se deslocado a áreas distantes. Há exatamente dez anos afirmei em meu ensaio Sociedade do Cansaço a tese de que vivemos em uma época em que o paradigma imunológico perdeu sua vigência, baseada na negatividade do inimigo. Como nos tempos da Guerra Fria, a sociedade organizada imunologicamente se caracteriza por viver cercada de fronteiras e de cercas, que impedem a circulação acelerada de mercadorias e de capital. A globalização suprime todos esses limites imunitários para dar caminho livre ao capital. Até mesmo a promiscuidade e a permissividade generalizadas, que hoje se propagam por todos os âmbitos vitais, eliminam a negatividade do desconhecido e do inimigo. Os perigos não espreitam hoje da negatividade do inimigo, e sim do excesso de positividade, que se expressa como excesso de rendimento, excesso de produção e excesso de comunicação. A negatividade do inimigo não tem lugar em nossa sociedade ilimitadamente permissiva. A repressão aos cuidados de outros abre espaço à depressão, a exploração por outros abre espaço à autoexploração voluntária e à auto-otimização. Na sociedade do rendimento se guerreia sobretudo contra si mesmo.

Limites imunológicos e fechamento de fronteiras

Pois bem, em meio a essa sociedade tão enfraquecida imunologicamente pelo capitalismo global o vírus irrompe de supetão. Em pânico, voltamos a erguer limites imunológicos e fechar fronteiras. O inimigo voltou. Já não guerreamos contra nós mesmos. E sim contra o inimigo invisível que vem de fora. O pânico desmedido causado pelo vírus é uma reação imunitária social, e até global, ao novo inimigo. A reação imunitária é tão violenta porque vivemos durante muito tempo em uma sociedade sem inimigos, em uma sociedade da positividade, e agora o vírus é visto como um terror permanente.

Mas há outro motivo para o tremendo pânico. Novamente tem a ver com a digitalização. A digitalização elimina a realidade, a realidade é experimentada graças à resistência que oferece, e que também pode ser dolorosa. A digitalização, toda a cultura do “like”, suprime a negatividade da resistência. E na época pós-fática das fake news e dos deepfakes surge uma apatia à realidade. Dessa forma, aqui é um vírus real e não um vírus de computador, e que causa uma comoção. A realidade, a resistência, volta a se fazer notar no formato de um vírus inimigo. A violenta e exagerada reação de pânico ao vírus se explica em função dessa comoção pela realidade.

Espero que após a comoção causada por esse vírus não chegue à Europa um regime policial digital como o chinês.

A reação de pânico dos mercados financeiros à epidemia é, além disso, a expressão daquele pânico que já é inerente a eles. As convulsões extremas na economia mundial fazem com que essa seja muito vulnerável. Apesar da curva constantemente crescente do índice das Bolsas, a arriscada política monetária dos bancos emissores gerou nos últimos anos um pânico reprimido que estava aguardando a explosão. Provavelmente o vírus não é mais do que a gota que transbordou o copo. O que se reflete no pânico do mercado financeiro não é tanto o medo ao vírus quanto o medo a si mesmo. O crash poderia ter ocorrido também sem o vírus. Talvez o vírus seja somente o prelúdio de um crash muito maior.

Žižek afirma que o vírus deu um golpe mortal no capitalismo, e evoca um comunismo obscuro. Acredita até mesmo que o vírus poderia derrubar o regime chinês. Žižek se engana. Nada disso acontecerá. A China poderá agora vender seu Estado policial digital como um modelo de sucesso contra a pandemia. A China exibirá a superioridade de seu sistema ainda mais orgulhosamente. E após a pandemia, o capitalismo continuará com ainda mais pujança. E os turistas continuarão pisoteando o planeta. O vírus não pode substituir a razão. É possível que chegue até ao Ocidente o Estado policial digital ao estilo chinês. Com já disse Naomi Klein, a comoção é um momento propício que permite estabelecer um novo sistema de Governo. Também a instauração do neoliberalismo veio precedida frequentemente de crises que causaram comoções. É o que aconteceu na Coreia e na Grécia. Espero que após a comoção causada por esse vírus não chegue à Europa um regime policial digital como o chinês. Se isso ocorrer, como teme Giorgio Agamben, o estado de exceção passaria a ser a situação normal. O vírus, então, teria conseguido o que nem mesmo o terrorismo islâmico conseguiu totalmente.

O vírus não vencerá o capitalismo. A revolução viral não chegará a ocorrer. Nenhum vírus é capaz de fazer a revolução. O vírus nos isola e individualiza. Não gera nenhum sentimento coletivo forte. De alguma maneira, cada um se preocupa somente por sua própria sobrevivência. A solidariedade que consiste em guardar distâncias mútuas não é uma solidariedade que permite sonhar com uma sociedade diferente, mais pacífica, mais justa. Não podemos deixar a revolução nas mãos do vírus. Precisamos acreditar que após o vírus virá uma revolução humana. Somos NÓS, PESSOAS dotadas de RAZÃO, que precisamos repensar e restringir radicalmente o capitalismo destrutivo, e nossa ilimitada e destrutiva mobilidade, para nos salvar, para salvar o clima e nosso belo planeta.

Byung-Chul Han é um filósofo e ensaísta sul-coreano que dá aulas na Universidade de Artes de Berlim. Autor, entre outras obras, de ‘Sociedade do Cansaço’, publicou há um ano ‘Loa a la tierra’, na editora Herder.

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Argentine football club Tigre launches implantable microchip for die-hard fans (AFP)

Abril 26, 2016 6:59pm

Tigres players hugging after a goal

PHOTO: Tigres fans won’t need hard copy tickets or to enter their stadium with the implanted microchip. (Reuters: Enrique Marcarian)

For football lovers so passionate that joining a fan club just isn’t enough, Argentine side Tigre has launched the “Passion Ticket”: a microchip that die-hards can have implanted in their skin.

In football-mad Argentina, fans are known for belting out an almost amorous chant to their favourite clubs: “I carry you inside me!”

First-division side Tigre said it had decided to take that to the next level and is offering fans implantable microchips that will open the stadium turnstiles on match days, no ticket or ID required.

“Carrying the club inside you won’t just be a metaphor,” the club wrote on its Twitter account.

Tigre secretary general Ezequiel Rocino kicked things off by getting one of the microchips implanted in his arm, under an already existing tattoo in the blue and red of the club.

The chips are similar to the ones dog and cat owners can have implanted in their pets in case they get lost.

Rocino showed off the technology for journalists, placing his arm near a scanner to open the turnstile to the club’s stadium 30 kilometres north of the capital, Buenos Aires.

“The scanner will read the data on the implanted chip, and if the club member is up-to-date on his payments, will immediately open the security turnstile,” the club said.

Rocino said getting a chip would be completely voluntary.

“We’re not doing anything invasive, just accelerating access. There’s no GPS tracker, just the member’s data,” he said.

AFP