Arquivo da tag: Tecnologias de controle

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

The inevitable weakness of metrics (MIT Technology Review)

technologyreview.com

Original article

Quantifying our lives is easier than it’s ever been. But a philosopher of games warns that external metrics and data can never capture what’s truly important.

Bryan Gardiner

June 19, 2026


There are plenty of useful things a metric can reveal. There are even more it can obscure or corrupt. It took me well over a decade of tracking my own life in ever greater detail to fully appreciate this duality, which probably reveals something about both me and the nature of measurement.

Like a lot of people bitten by the self-quantifying bug, I initially started gathering personal data to pursue a nebulous collection of goals and desires. As a sedentary technology journalist, I wanted to feel better physically and emotionally, to get outside more, and—where possible—to bring order to some of the messiness and uncertainty of my daily existence. These all seemed to be things that could be improved with the cool clarity of numbers.

Self-quantifiers often get stereotyped as obsessive self-optimizers (and many of them are), but my reasons for producing and collecting personal data were less about life-maxxing and more about life meaning—at least at first. As most people who know me will attest, I do not have now, nor have I ever possessed, a “productivity mindset.” I’m also not all that interested in life hacks, shortcuts, or new ways to compare myself with other people. Instead, what I wanted out of metrics—what I hoped I could divine from a never-ending stream of numbers about my health, work, and social life—was something more elusive: self-knowledge. This was my first mistake. 

The idea that the more we know, the better is so profoundly embedded in our culture that it feels weird to even point it out. Since at least as far back as the Enlightenment, the primary way we’ve all agreed to go about knowing more has been through measurement and quantification. After all, more knowledge—more data—leads to better decisions, which leads to happier, more fulfilled people. Or so we’re told, and with increasing frequency in the era of AI. 

When two Wired magazine editors, Gary Wolf and Kevin Kelly, coined the term “quantified self” in 2007 and helped launch the movement we are all now helplessly a part of, they were essentially selling this very idea. “Unless something can be measured, it cannot be improved,” wrote Kelly in an early blog post, doing his best impression of Lord Kelvin. “So we are on a quest to collect as many personal tools that will assist us in quantifiable measurement of ourselves.” Almost 20 years later, that quest is easier than ever thanks to a flood of devices, apps, and websites all designed to help us build our self-­knowledge through numbers. 

My first tool was a small, plastic clip-on Fitbit I started using in 2011. It did one thing: count the number of steps I took in a day. As a lifelong video game player, I was already well acquainted with the motivational power of simple scoring systems, and I hoped my new gadget would offer the gentle numerical nudge I thought I needed to step away from my Twitter feed and, if not touch grass, at least walk next to some. Walking also seemed to be one of the few times I had what could charitably be called intelligent ideas, which seemed like another promising by-product of doing more of it.

Alas, that was short-lived. I can’t tell you precisely when “getting out into nature more” or “thinking smarter thoughts” stopped mattering to me as goals, but I suspect it took no more than a few weeks. What I can say with certainty is that my initial goal of 6,000 daily steps quickly turned into 10,000, which then jumped to 15,000 and eventually settled at 20,000 for years. Stories about becoming a “steps guy” are clichéd at this point, and they’ve earned that status for a reason.  

It didn’t take long for me to trade in pedometers for heart-rate monitors (I also started running), smartwatches, sleep-tracking rings, and an embarrassing number of macronutrient-­tabulating apps. Outside the health and fitness realm, my early career as a journalist also happened to coincide with the rise of social media and web analytics tools like Chartbeat, which promised to further quantify ­difficult-to-measure aspects of my life, like “job success” and “impact,” by tracking things like page views, followers, retweets, likes, and all sorts of other attentional metrics that now carry great weight.

Metrics inevitably redefine your core sense of what’s important, whether you’re aware of the trap or not.

Ultimately, during the 10-plus years I diligently tracked my heart rate, steps, active calories, sleep, story engagement time, stress levels, and other metrics, I gained virtually nothing in terms of greater self-knowledge. (I suppose I did learn that I liked to make numbers go up and down, but who doesn’t?) The swirl of data that followed me everywhere did not lend additional meaning or insight to the way I relate to myself, my work, or the important people in my life. In fact, the more I used numerical proxies, the worse I felt about pretty much everything. 

What I did learn were two important lessons about what happens when you try to quantify the minutiae of your life. First and foremost, whatever the amount of data you’re currently collecting about yourself, it will never feel sufficient. There’s always a new metric around the corner, a better way for a tracker to remix its readings and more accurately measure what’s “important”: heart rate variability, daily stress, exercise “readiness,” cardiovascular or “fitness” ages. Measurement begets more measurement. You can count on it. 

book cover
The Score: How to Stop Playing Somebody Else’s Game
C. Thi Nguyen

The second lesson was less obvious but no less significant. The more personal or nuanced your goals are when you set off on your self-quantifying journey, the more likely it is you will ultimately replace them with some simplified metric or ranking. Want to become a better journalist? Why not use page views and leaderboards as a proxy for success? Enjoy cooking and want to improve? Foodie metrics dictate that more complicated recipes with longer ingredient lists are the answer. Even when we know that the value of good journalism isn’t reflected in how many people read a given story or that the joys of cooking are as much about improvisation and experimentation as about successfully following some complex recipe, it’s hard to resist the allure of a simple score or stat. Metrics inevitably redefine your core sense of what’s important, whether you’re aware of the trap or not. 

Over the years, people have invented various terms to describe this phenomenon. In his recent book The Score: How to Stop Playing Somebody Else’s Game, the philosopher C. Thi Nguyen calls it “value capture.” Value capture happens, he says, when you adopt external sources of measurement and then let them rule you without adapting them to suit your life. “In value capture, you’re essentially outsourcing your values,” Nguyen writes. “You’re letting an external metric or ranking set what’s important for you.” Crucially, you’re also outsourcing the process of figuring out your own sense of meaning. It’s why my walks quickly shifted from feeling meditative to prioritizing miles. 

Individuals, institutions, and indeed entire societies can fall prey to value capture. In fact, once you start noticing it, you start seeing it everywhere—in journalism, education, and business, but also in our food, our hobbies, and, yes, the way we measure our health and happiness. Here’s how Nguyen puts it:

Value capture happens when a restaurant stops caring about making good food and starts caring about maximizing its Yelp ratings. It happens when students stop caring about education and start caring about their GPA. It happens when scientists stop caring about finding truth and start caring about getting the biggest grants. It even happens in religion. A pastor recently told me that his church had become completely obsessed with baptism rates. The higher-ups had established an internal leaderboard in which the pastors competed on monthly baptism rates, and it was starting to dominate everybody’s attention. He’d found himself caring less about the long-term spiritual development of his flock and focusing more on trying to deliver popular sermons that would up his baptism rates and move him up that leaderboard.

At its core, The Score is trying to untangle a mystery that Nguyen, a specialist in the philosophy of games at the University of Utah, has been thinking about for a long time: Why is it that numbers and scoring systems in games can be the source of so much joy and fluidity and play, but public measures and institutional metrics (i.e., scores that apply to the real world) seem to drain the life out of everything and thrust us all into a bleak mindset of grinding optimization?

To begin to answer this question, he turns to one of the foundational inquiries into the limits of data and quantification, Theodore M. Porter’s 1995 book Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. 

Porter, a historian of science who specializes in the social power of numbers, has spent his career looking at why quantification has become so dominant, not just in political and bureaucratic life but everywhere. One of his key insights about the inherent attractiveness of quantification, which he calls “a technology of distance,” is that it “minimizes the need for intimate knowledge and personal trust.” Put another way, metrics travel extremely well between different contexts and are easy to grasp and aggregate. 

Whether it’s a student’s GPA or a country’s GDP, these measures are understood by pretty much everyone. But that understanding comes at a price, Porter reminds us: To arrive at a clear metric, you inevitably need to simplify what you’re attempting to measure, often jettisoning heaps of nuanced, qualitative, or open-ended information so that others can find the resulting number legible. 

No one (hopefully) believes that a GPA captures in any meaningful way a student’s entire educational experience or aptitude for learning, but we’ve agreed to use it because more qualitative assessments are onerous to wade through and require expertise to decipher and compare. Ditto for the economic metric of GDP, which politicians and societies are now compelled to drive higher and higher because a group of economists once concluded that this figure correlates with general economic well-being.  

This is the essential tension at the heart of all data, argues Nguyen. Any institutional quantification, he says, requires that the evaluation procedure and its product be comprehensible across contexts. That profoundly limits what the metric can actually measure. “In value capture, you’re ultimately taking that decontextualized nugget and internalizing it,” he writes. “You’re guiding your life using an evaluative technology that has been engineered to travel between contexts, by stripping it of nuance.” 


Every so often I’ll find myself in friendly debate with a “numbers person”—a statistician, an economist, or a friend who’s still a committed self-quantifier. After patiently listening to my measurement-gone-awry examples—the disastrous attempt to quantify pain as “the fifth vital sign” in the mid-1990s (which exacerbated the opioid epidemic), or any of the countless examples of the McNamara fallacy, where decisions in academia, medicine, and politics are based solely on what’s easily measured—many will insist that I’m misunderstanding or misinterpreting the whole point of measuring. Metrics, they’ll say, are simply a means, and the important questions concern the ends for which they are used. In other words, these unfortunate outcomes amount to user error, not something inherently dangerous or misleading about the nature of measurement. 

At some point during these conversations, Goodhart’s Law will invariably come up, usually as an explanation the metrics-minded deploy for why the ends get all mucked up. The principle, which is attributed to the British economist Charles Goodhart, is often expressed as the following: “When a measure becomes a target, it ceases to be a good measure.” I have a profound dislike for Goodhart’s Law, not because I think it’s untrue, but rather for the way it gets interpreted.

As Nguyen notes, Goodhart’s Law says very little about why metrics fail to capture what’s important—or what to do about it. Find better measures, some will conclude. Don’t let metrics become targets, others will insist. These are not helpful takeaways. All measurements, I would argue, are in fact targets, whether you intend them to be or not. Metrics inevitably present one direction or option as better, Nguyen writes in The Score—“longer lifespans, faster student graduation rates, more page views, higher customer satisfaction scores.” What people are talking about when they bring up Goodhart’s Law isn’t human error; it’s actually a fundamental problem with measurement itself. 

I want to be clear here: Measurement can and does serve a number of vital functions. It has in a very literal sense made the modern world possible, with all its life­-saving, suffering-reducing, and awe-inspiring scientific breakthroughs. When used with care and diligence, metrics can make our progress (or lack of it) clearer and more transparent. Are we decreasing carbon dioxide emissions or not? They can also introduce accountability into formerly opaque systems, such as by measuring whether a company is complying with state and federal regulations. They can even make us more objective, reduce biases, and galvanize us to act. 

But as Nguyen points out throughout The Score, the fundamental weakness of metrics comes when we use them to pursue subtler, more personal goals. What I think many of us miss—what I know I certainly missed—is that there are always trade-offs when you try to distill something important down to a data point. When we turn to metrics to understand ourselves, our social world, and culture as a whole, they will never come close to capturing what matters. Even worse, they’ll often actively obscure it. 


Today, I find that numbers have very little to offer when it comes to my daily work, my physical or mental fitness, my relationships, or any other part of my life I consider important. Granted, I’m lucky enough to be in relatively good health at the moment. I don’t have to track my glucose levels or monitor my blood pressure. As a freelance writer, I also have the luxury of not having numbers foisted on me in the form of key performance indicators (KPIs), objectives and key results (OKRs), or any of the endless quantitative evaluations that come baked into pretty much every corporate and gig economy job. 

Still, in a very real sense, there is no escaping metrics or, especially, the logic that accompanies them. Knowing has become numeric, and we all live in a world that increasingly sees us as a collection of numbers—as “data subjects.” The first and most urgent challenge, I’d suggest, is finding a way to keep us from seeing ourselves and each other that way. 

This won’t be easy. As Porter, Nguyen, and countless other philosophers, anthropologists, and historians have already observed, the language of numbers is largely how we ascribe value today—as well as how we digest and metabolize our relationships to ourselves, to others, and to the world around us. Indeed, many of us have accepted not only that metrics have a natural existence in human affairs but that there are in fact no aspects of human life that cannot be somehow translated into data.

Knowing has become numeric, and we all live in a world that increasingly sees us as a collection of numbers— as “data subjects.”

So how do we push back? Nguyen’s book offers a useful first step. As he notes again and again in The Score, believing that numbers say something real or useful about human needs and desires gives them power. We can, at the very least, start to seriously question that belief, to ask what meaning and pleasure we might be giving up in pursuit of a metric.

Doing so will hopefully lead to another realization: that playing the numbers game is ultimately a losing proposition for humans. If we insist on expressing our worth through attentional metrics and productivity scores, if we continue to turn intelligence and creativity into a series of benchmarks for AI to surpass, we’ve already lost. Of course machines will surpass us in a world built around metrics. That is literally what we create them to do. The answer is not to turn ourselves into machines too. 

If there’s one thing that keeps me up at night, it is that we’ve become so accustomed to seeing and understanding the larger world and ourselves through numbers that it has deprived us of the language to express what’s fundamental and valuable about our own humanity. We need this ability now more than ever, especially if we’re going to adequately answer two of the most important questions of our era: What are humans for? And what is AI for?

As part of my own attempts to disentangle myself from a life of numbers—efforts that started shortly before covid—I’ve abandoned most of the tools of measurement I spent a decade collecting. I’ve largely given up on social media. I stopped using apps to track my health and well-­being. The watch I currently wear tells me the time and the date and nothing else. 

In fact, the only holdover from my days of obsessive self-quantification is a dogmatic devotion to walking—without all the step counting, of course. These days, I walk when I’m feeling disillusioned or overwhelmed; I walk when I can’t figure out how to finish an essay; I also walk because I enjoy spending time outdoors with my dog and catching up on the details of my neighbors’ lives. The benefits of pursuing this daily activity are as clear and obvious to me as anything could be in life. I just can’t express them in a number. 

Bryan Gardiner is a writer based in Oakland, California.

China’s Expanding Surveillance State: Takeaways From a NYT Investigation (NY Times)

nytimes.com

Isabelle Qian, Muyi Xiao, Paul Mozur, Alexander Cardia


Times reporters spent over a year combing through government bidding documents that reveal the country’s technological road map to ensure the longevity of its authoritarian rule.

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A New York Times analysis of over 100,000 government bidding documents found that China’s ambition to collect digital and biological data from its citizens is more expansive and invasive than previously known.

June 21, 2022

China’s ambition to collect a staggering amount of personal data from everyday citizens is more expansive than previously known, a Times investigation has found. Phone-tracking devices are now everywhere. The police are creating some of the largest DNA databases in the world. And the authorities are building upon facial recognition technology to collect voice prints from the general public.

The Times’s Visual Investigations team and reporters in Asia spent over a year analyzing more than a hundred thousand government bidding documents. They call for companies to bid on the contracts to provide surveillance technology, and include product requirements and budget size, and sometimes describe at length the strategic thinking behind the purchases. Chinese laws stipulate that agencies must keep records of bids and make them public, but in reality the documents are scattered across hard-to-search web pages that are often taken down quickly without notice. ChinaFile, a digital magazine published by the Asia Society, collected the bids and shared them exclusively with The Times.

This unprecedented access allowed The Times to study China’s surveillance capabilities. The Chinese government’s goal is clear: designing a system to maximize what the state can find out about a person’s identity, activities and social connections, which could ultimately help the government maintain its authoritarian rule.

Here are the investigation’s major revelations.

Analysts estimate that more than half of the world’s nearly one billion surveillance cameras are in China, but it had been difficult to gauge how they were being used, what they captured and how much data they generated. The Times analysis found that the police strategically chose locations to maximize the amount of data their facial recognition cameras could collect.

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The Chinese government bidding documents analyzed by The Times outline the authorities’ surveillance ambitions. Credit: The New York Times

In a number of the bidding documents, the police said that they wanted to place cameras where people go to fulfill their common needs — like eating, traveling, shopping and entertainment. The police also wanted to install facial recognition cameras inside private spaces, like residential buildings, karaoke lounges and hotels. In one instance, the investigation found that the police in the city of Fuzhou in the southeast province of Fujian wanted to install a camera inside the lobby of a franchise location of the American hotel brand Days Inn. The hotel’s front desk manager told The Times that the camera did not have facial recognition capabilities and was not feeding videos into the police network.

A document shows that the police in Fuzhou also demanded access to cameras inside a Sheraton hotel. In an email to The Times, Tricia Primrose, a spokeswoman for the hotel’s parent company, Marriott International, said that in 2019 the local government requested surveillance footage, and that the company adheres to local regulations, including those that govern cooperation with law enforcement.

These cameras also feed data to powerful analytical software that can tell someone’s race, gender and whether they are wearing glasses or masks. All of this data is aggregated and stored on government servers. One bidding document from Fujian Province gives an idea of the sheer size: The police estimated that there were 2.5 billion facial images stored at any given time. In the police’s own words, the strategy to upgrade their video surveillance system was to achieve the ultimate goal of “controlling and managing people.”

Devices known as WiFi sniffers and IMSI catchers can glean information from phones in their vicinity, which allow the police to track a target’s movements. It’s a powerful tool to connect one’s digital footprint, real-life identity and physical whereabouts.

The phone trackers can sometimes take advantage of weak security practices to extract private information. In a 2017 bidding document from Beijing, the police wrote that they wanted the trackers to collect phone owners’ usernames on popular Chinese social media apps. In one case, the bidding documents revealed that the police from a county in Guangdong bought phone trackers with the hope of detecting a Uyghur-to-Chinese dictionary app on phones. This information would indicate that the phone most likely belonged to someone who is a part of the heavily surveilled and oppressed Uyghur ethnic minority. The Times found a dramatic expansion of this technology by Chinese authorities over the past seven years. As of today, all 31 of mainland China’s provinces and regions use phone trackers.

The police in China are starting to collect voice prints using sound recorders attached to their facial recognition cameras. In the southeast city of Zhongshan, the police wrote in a bidding document that they wanted devices that could record audio from at least a 300-foot radius around cameras. Software would then analyze the voice prints and add them to a database. Police boasted that when combined with facial analysis, they could help pinpoint suspects faster.

In the name of tracking criminals — which are often loosely defined by Chinese authorities and can include political dissidents — the Chinese police are purchasing equipment to build large-scale iris-scan and DNA databases.

The first regionwide iris database — which has the capacity to hold iris samples of up to 30 million people — was built around 2017 in Xinjiang, home to the Uyghur ethnic minority. Online news reports show that the same contractor later won other government contracts to build large databases across the country. The company did not respond to The Times’s request for comment.

The Chinese police are also widely collecting DNA samples from men. Because the Y chromosome is passed down with few mutations, when the police have the y-DNA profile of one man, they also have that of a few generations along the paternal lines in his family. Experts said that while many other countries use this trait to aid criminal investigations, China’s approach stands out with its singular focus on collecting as many samples as possible.

We traced the earliest effort to build large male DNA databases to Henan Province in 2014. By 2022, bidding documents analyzed by The Times showed that at least 25 out of 31 provinces and regions had built such databases.

The Chinese authorities are realistic about their technological limitations. According to one bidding document, the Ministry of Public Security, China’s top police agency, believed the country’s video surveillance systems still lacked analytical capabilities. One of the biggest problems they identified was that the data had not been centralized.

The bidding documents reveal that the government actively seeks products and services to improve consolidation. The Times obtained an internal product presentation from Megvii, one of the largest surveillance contractors in China. The presentation shows software that takes various pieces of data collected about a person and displays their movements, clothing, vehicles, mobile device information and social connections.

In a statement to The Times, Megvii said it was concerned about making communities safer and “not about monitoring any particular group or individual.” But the Times investigation found that this product was already being used by Chinese police. It creates the type of personal dossier authorities could generate for anyone, that could be made accessible to officials across the country.

China’s Ministry of Public Security did not respond to faxed requests for comment sent to its headquarters in Beijing, nor did five local police departments or a local government office named in the investigation.

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. ■

Coronavírus anuncia revolução no modo de vida que conhecemos (Folha de S.Paulo)

www1.folha.uol.com.br

Domenico De Masi – 22.3.2020


[RESUMO] Sociólogo italiano narra situação dramática em seu país e argumenta que as imposições em decorrência da pandemia, como o trabalho em casa, a solidariedade e o papel da esfera pública, demonstram que é possível e desejável mudar a lógica mercadista da economia e criar modos de viver mais racionais e proveitosos para o mundo contemporâneo.

A Itália de onde escrevo, um dos países mais vivazes e alegres do mundo, é hoje apenas um deserto. Cada um dos seus 60 milhões de habitantes acha que é imortal, que o vírus não o tocará, que irá matar não ele mas alguma outra pessoa. Porém, no silêncio do seu coração, cada um sabe que essa ilusão é pueril e que essa pandemia misteriosa, abstrata e tangível ao mesmo tempo, escolhe suas vítimas ao acaso, como numa roleta russa.

Em algum tempo vamos saber se o vírus pode ser debelado ou se nos matará em massa, assim como fez no século passado a famosa gripe espanhola, que matou 1 milhão de pessoas por semana durante 25 semanas seguidas.

Moro há 50 anos no centro de Roma, na rua mais movimentada da cidade, que leva da praça Veneza à Basílica de São Pedro.

Normalmente, essa rua está 24 horas por dia entupida de trânsito, de turistas e peregrinos. Há duas semanas, está muda e deserta. Só de vez em quando ouve-se o grito de uma sirene de ambulância e algum sem-teto passa. A cidade inteira está fantasmagórica como a Los Angeles de “Blade Runner”. Aqui, porém, desapareceram até os replicantes extraterrestres.

Fechados os lugares públicos, as escolas, as fábricas, as lojas, as estações, os portos e os aeroportos, a Itália é agora um país separado do resto da Europa e do mundo. Cada cidade está parada, cada família trancafiada em casa. Quem sai à revelia dos pouquíssimos motivos permitidos é interceptado imediatamente pelas rondas policiais que aplicam penas bastante severas.

Os gregos antigos consideravam que, quando algo é indispensável e todavia impossível, a situação é trágica. Foram necessários 50 dias, milhares de doentes e mortos para que os italianos entendessem que a situação é, enfim, irremediavelmente trágica.

O que significa uma pandemia como essa para Roma, para a Itália, para a humanidade como um todo? Como ela age nas mentes e nos corações de todos nós que, armados com tecnologias poderosas e inteligência artificial, até poucas semanas atrás nos sentíamos os senhores do céu e da terra?

Subitamente nos descobrimos frágeis pigmeus diante da onipotência imaterial de um vírus que, por vias misteriosas, escapou de um morcego chinês para vir matar homens e mulheres em nossas cidades.

A sujeição a um vírus desconhecido, para o qual não há nem cura nem vacina, transformou a Itália numa enorme caserna blindada e os 60 milhões de italianos noutros tantos dóceis soldadinhos empenhados num gigantesco exercício militar no qual estão obrigados a aprender a verdade que antes ignoravam obstinadamente. O que não quer dizer que irão apreendê-la.

Numa Europa onde, até ontem, era permitida a livre circulação de pessoas, mercadorias e dinheiro, agora cada país, em vez de abraçar uma colaboração ainda mais solidária com os demais, tranca suas próprias fronteiras, iludindo-se de forma cínica e infantil que seja possível deter o vírus com barreiras aduaneiras.

Contudo, hoje, mais do que nunca, os soberanismos parecem tentativas fantasiosas contra a globalização. Hoje, mais do que nunca, a difusão da pandemia e sua rápida volta ao mundo demonstraram que deter a globalização é como se opor à força de gravidade. Nosso planeta já é aquela “aldeia global” da qual falava McLuhan, unida por infortúnios e pela vontade de viver, precisando de uma direção unitária, capaz de coordenar a ação sinérgica de todos os povos que desejam se salvar. Nessa aldeia global, nenhum homem, nenhum país é uma ilha.

Talvez tenhamos aprendido que o caso agora é de vida ou morte e que ninguém pode enfrentar sozinho um vírus tão ardiloso e potente. Por isso, são necessários recursos, inteligências, competências, ações e instituições coletivas. Coordenação e coesão geral. É necessária uma cabine de comando, um governo competente que tenha autoridade, uma equipe formada por um vértice político de grande inteligência e apoiada pelos máximos representantes das ciências médicas, da economia, da sociologia, da psicologia social e da comunicação.

Talvez tenhamos aprendido que os fatos e os dados devem prevalecer sobre as opiniões, a competência reconhecida deva prevalecer sobre o simples bom senso, a prudência e a gradualidade das intervenções devem prevalecer às tomadas de decisões arrogantes e à improvisação imprudente. Por outro lado, é necessário tolerar os erros de quem possui a responsabilidade terrível de tomar decisões, líder que deve ser generosamente amparado para que sejam melhoradas.

Talvez tenhamos aprendido que, perante um vírus desconhecido, assim como diante de um problema complexo, as decisões sobre a pandemia não apenas devem ser tomadas pelas pessoas competentes mas também ser comunicadas de forma unívoca, com autoridade, prontamente, de forma abrangente e clara. Todo o alarmismo, todo o exagero, toda a subestimação é terrível porque confunde as ideias e nos faz perder um tempo precioso. Carência e excesso de informações são parâmetros nocivos. Talk shows superficiais e fake news delirantes levam ao cinismo e à desumanização.

Talvez tenhamos aprendido que, nos países civilizados, o bem-estar é uma conquista irrenunciável. Por sorte e pela sabedoria dos nossos pais, a Constituição italiana de 1948 considera a saúde como um direito fundamental de cada ser humano. Já a reforma sanitária de 1978 instituiu um serviço nacional universal que considera a saúde não como meramente a ausência de doença, mas como o bem-estar físico, psíquico e social completo.

Graças a esse regime de saúde, todos os residentes (e também os turistas) fruem dos cuidados médicos sem qualquer custo. Isso nos possibilitou descobrir e curar prontamente os contágios e reduzir o número de mortes.

No país mais rico e mais poderoso do mundo, os EUA, onde o bem-estar é estupidamente mortificado, os suspeitos de Covid-19 precisam desembolsar o equivalente a 1.200 euros pelo teste. O vírus corona, ao se difundir, causaria uma verdadeira hecatombe entre 90 milhões de estadunidenses que, desprovidos de seguro-saúde, seriam cinicamente rejeitados pelos hospitais.

A propaganda neoliberal, que se alastrou sob a bandeira insana de Reagan e Thatcher, desacreditou tudo o que é público em favor do setor privado. Porém, pelo contrário, nessas semanas trágicas, a reação eficiente dos hospitais e dos funcionários públicos diante do surgimento da pandemia nos ensinou que a nossa saúde pública, da mesma forma que outras funções públicas, dispõe, muito mais do que o setor privado, de pessoas preparadas profissionalmente, motivadas e generosas até o heroísmo.

Toda noite, às 18h, todas as janelas da Itália se escancaram e cada um canta ou toca o hino nacional para agradecer aos médicos e a todos os profissionais da saúde.

A pandemia está nos ensinando que o pensamento de Keynes permanece precioso. Em 1980, o prêmio Nobel Robert Lucas Jr. observou: “Não é possível encontrar nenhum bom economista com menos de 40 anos que se diga ‘keynesiano’. Nas universidades, as teorias keynesianas não são levadas a sério e provocam sorrisinhos de superioridade”.

Hoje, essa crise histórica, com seus mortos e com suas tragédias, se porum lado nos leva à recessão, por outro nos lembra que, para evitar uma crise irreparável, em vez de políticas de austeridade, é preferível dar lugar aos investimentos públicos maciços e “open-ended”, ainda que isso leve ao déficit público.

Talvez tenhamos aprendido tudo isso e várias outras coisas com aquilo que ocorreu fora do recinto doméstico, isto é, entre o governo e todo o povo do país. Entretanto, hoje, a nossa vida está segregada entre as paredes domésticas. Todos estão restritos entre as quatro paredes da própria casa: não só as famílias que vivem em harmonia e acordo, mas também os solitários, os casais em crise e os núcleos familiares em que o diálogo entre pais e filhos há muito tempo andava claudicante.

A sociedade industrial nos habituara a separar o local de trabalho do local de vida, nos fazendo passar a maior parte do nosso tempo com chefes e colegas nas empresas: os que a sociologia chama de grupos “secundários”, frios, formais, nos quais as relações são quase exclusivamente profissionais. Uma parte mínima do nosso tempo nos via reunidos em família ou com os amigos, ou seja, com grupos “primários”, calorosos, informais, envolventes.

De repente, o descanso compulsório em casa nos obrigou de forma inédita ao isolamento total, a uma convivência forçada que para alguns parece agradável e tranquilizadora, mas que para outros é invasiva e até opressora. Os mais sortudos conseguem transformar o ócio depressivo em ócio criativo, conjugando a leitura, o estudo, o lúdico com a parcela de trabalho que é possível desempenhar em regime de “smart working”.

Sabíamos teoricamente que essa modalidade de trabalho à distância permite aos trabalhadores uma preciosa economia de tempo, dinheiro, stress e alienação; e às empresas, evita os microconflitos, despesas na manutenção do local de trabalho e promove incremento da eficiência, recuperando de 15 a 20% da produtividade; à coletividade, evita a poluição, o entupimento de trânsito e despesas de manutenção das estradas.

Agora que 10 milhões de italianos, forçados pelo vírus, rapidamente adotaram o teletrabalho, minimizando seu sentimento de inutilidade e os danos à economia nacional, nos perguntamos por que as empresas não haviam adotado antes uma forma de organização tão eficaz e enxuta. A resposta está naquilo que os antropólogos definem como “cultural gap” —lacuna cultural— das empresas, dos sindicatos, dos chefes.

O tempo livre que, até um mês atrás, nos parecia um luxo raro, hoje abunda. O espaço, que nas cidades vazias se dilatou, por sua vez falta nas casas. Por isso, estamos apreciando a ajuda que nos chega da internet, graças à qual, mesmo permanecendo forçosamente distantes, é possível nos reunirmos virtualmente, nos informarmos, nos confrontarmos, nos encorajarmos.

Nessa reclusão, os jovens têm a maior vantagem, graças à sua facilidade com os computadores, enquanto os velhos têm mais vantagem por serem mais independentes, mais acostumados a estar em casa, fazendo pequenos trabalhos e jogos sedentários, contentando-se com a televisão.

Em todos se insinua o medo de que, mais cedo ou mais tarde, possa terminar o abastecimento dos mantimentos. O colapso da economia torna-se cada vez mais inevitável, já que tanto a produção como o consumo encontram-se bloqueados.

Há alguns anos, Kennet Building, um dos pais da teoria geral dos sistemas, comentando a sociedade opulenta, afirmou: “Quem acredita na possibilidade do crescimento infinito num mundo finito ou é louco ou é economista”. E Serge Latouche acrescentou: “O drama é que agora somos todos mais ou menos economistas. Aonde estamos nos encaminhando? Diretamente contra um muro. Estamos a bordo de um bólido sem piloto, sem marcha a ré e sem freios que irá se chocar contra os limites do planeta”. Latouche propõe abandonar a sociedade de consumo com um decrescimento planificado, progressivo e sereno.

A marcha a ré e os freios que a cultura neoliberal se recusou obstinadamente a usar agora foram desencadeados: não graças a uma revolução violenta, mas sim a um vírus invisível que um morcego soprou sobre a sociedade opulenta, obrigando-a a se repensar.

“A Peste” (1947), obra-prima profética de Albert Camus, talvez possa nos ajudar nesse repensar. Naquele romance, a ciência era protagonista, ou seja, o médico Bernardo Rieux, ocupado até o fim, como médico e como homem, de socorrer os contagiados, enquanto “o cheiro de morte emburrecia todos os que não matava”.

Hoje, nós também, como o nosso tão humano irmão Rieux, estamos presos num limbo entre o pesar e a esperança, no qual temos que aprender que “a peste pode vir e ir embora sem que o coração do homem seja modificado”; que “o bacilo da peste não morre nem desaparece nunca, que pode permanecer adormecido por décadas nos móveis e nas roupas, que espera pacientemente nos quartos, nas adegas, nas malas, nos lenços e nos papéis, que talvez chegue o dia em que, infortúnio ou lição aos homens, a peste acordará seus ratos para mandá-los morrer numa cidade feliz”.


Domenico De Masi, sociólogo italiano, é autor dos livros “Ócio Criativo” e “O Futuro do Trabalho”.

Tradução de Francesca Cricelli.

Texto original