No Pilots. Few Air Traffic Controllers. What Could Go Wrong?

On September 27, US transportation secretary Sean Duffy posted a video on X with the words “GAME CHANGER.” “Introducing ‘SMART’—the new air traffic management tool that saves YOU time, cuts back DELAYS, and makes your flying experience BETTER,” he wrote. This was a new AI-infused air traffic control system. Almost three weeks later, that post would get a new life, as a nervous joke, as the FAA issued a national groundstop on Friday the 13th that instantly threw the world’s airline schedules into chaos. The administration quickly announced that there was no evidence of a cyberattack, and no sign that SMART had anything to do with the communications failure at the heart of the government’s decision to suspend flights. But when asked on Friday night whether he could definitively rule out AI failure, Homeland Security secretary Markwayne Mullin could only say, “There’s nothing certain right now.”

New systems like SMART are only the tip of the iceberg when it comes to the AI aviation revolution currently underway. Take, for instance, the Cessna Caravan that took off from Buchanan Field Airport in Concord, California, and flew south to Phoenix on a calm September morning. The plane, a single-engine turboprop, then turned east to Fort Worth, stopped at Shaw Air Force Base in South Carolina, and finally arrived at Dare County Regional Airport off the coast of North Carolina. The zigzag, coast-to-coast trip covered 3,200 miles; along the way, the aircraft navigated busy airspace and maneuvered to avoid storms.

None of this would be remarkable, save for one fact: The entire journey took place without a single human hand touching the plane’s controls.

According to Joby Aviation, the company that carried out the project, a safety pilot was aboard the Cessna at all times—but never needed to intervene. The pilotless trip marked a major milestone in aviation. The air travel industry has long been technologically conservative, and with good reason: When human lives are at stake, it’s better to be time-tested and a little dated than cutting-edge and unpredictable. But AI is making inroads into aviation with unprecedented speed. The effects now are hard to see, but the changes in the offing are huge, promising to remake the economics of air travel and transform how people and things move around in the sky. A big question remains, though: Can we trust this technology to be reliable and safe?

Depends who you ask. “We're introducing all this new technology to improve the system, and it's going to be a disaster,” says a recently retired FAA employee. “This is literally a Pandora's box that we are going to regret.”

Aviation’s embrace of AI traces back to the early 2000s, when advances in batteries and microelectronics suddenly made drones much more capable and inexpensive. The surge convinced officials that robots and humans would eventually need to share the airways, and that new infrastructure would be necessary to allow that. At the time, virtually all aircraft were human-piloted, and there was no way for drones to avoid human-flown planes or each other.

Around the same time, a host of startups began working on a related kind of vehicle: electric vertical takeoff and landing aircraft, or eVTOLs, also known as electric air taxis. These are, essentially, oversized drones (with room for pilots, for now) designed to carry a small number of people a short distance. By 2022 there were 600 different models under development. Soon, their manufacturers promised, cheap, short aerial hops would be commonplace. Joby was among those leading the charge: In 2020, the company unveiled the design of its S4 model, which it said would be able to carry a pilot and four passengers 100 miles or more at speeds of up to 200 mph. The S4’s maiden flight took place last year.

A commercial launch seemed just around the corner. But deadlines kept getting pushed back. As it turned out, engineering a flying autonomous robot was just part of the overall problem. You also needed to design an airspace that they could operate in, train humans to pilot or supervise them, develop an economic framework within which they could earn money, and so on. “It's a very important, safe, careful dance,” says Bowles.

Silicon Valley’s speed has long been in conflict with air travel norms. “Aviation regulation has been conservative and prioritizes reliability, because the consequences of failure are severe,” says Mary Schiavo, an aviation lawyer and former inspector general in the Department of Transportation. “Certification standards and airworthiness require proof and demonstrated safety, and that usually means incremental rather than radical change.” The FAA was in no rush to let unproven robots go careening around the national airspace.

AI faced another kind of resistance in Europe. In 2017, aircraft manufacturers Airbus and Dassault asked the EASA, the European Union’s version of the FAA, to consider allowing airliners to operate with a single pilot in the cockpit. Traditionally, airliners require multiple pilots to divide the considerable workload of flying a plane and to ensure that if one pilot becomes incapacitated, the other can carry on. In Airbus’ vision, automated systems would shoulder the copilot’s workload and even take over entirely if needed.

That idea horrified pilots. The European Cockpit Association, a union of airline pilots, lodged a strong protest. Such a move “would remove an independent safety professional from the flight deck and give operators greater influence over the safety judgments that a pilot would otherwise make,” the union explained to me in an email. Last year, EASA shelved the plan.

Nevertheless, AI pressed onward. In 2023, the FAA began issuing waivers to allow delivery-drone flights beyond the visual range of operators; by the end of this year it could make the rule change permanent. Some of the biggest players are already pushing ahead aggressively. This past August, Amazon announced that it planned to expand its drone delivery service to 500 locations across the country by the end of the year. Walmart is planning drone delivery from 270 store locations by the end of 2027.

The ultimate goal is far larger. Industry insiders say that in a maximal vision of the technology’s build-out, hundreds of thousands of drones will be servicing most or all of the US population. “In five to 10 years, it’s going to be completely ubiquitous,” Anthony Vittone, chief operating officer of the drone technology company DroneUp, told me in a story for Sherwood News last year. “People are going to be, like, ‘I don’t know how I lived without it.’"

Joby and other eVTOL companies haven’t progressed quite as fast, but they, too, are moving ahead. In April, Joby flew the first-ever point-to-point eVTOL flight within New York City, from John F. Kennedy Airport to three heliports in Manhattan. The company has carried out similar flights in California and Texas, all under the auspices of the eVTOL Integration Pilot Program (eIPP), a federal initiative rolled out by the Trump administration this past March to demonstrate the capabilities of modern drones and eVTOLs.

These demo flights, Bowles says, are just the “front edge” of the Joby S4’s operational rollout. Next will come demonstration flights with nonpaying passengers, demonstration flights with paying passengers, and finally flights that will take passengers from A to B. “All of that is permitted under eIPP, with increasing levels of oversight,” he says.

To start, these flights will have human pilots, but it’s very expensive to pay one human to fly around a handful of paying passengers; for the model to make any economic sense, the aircraft will have to fly themselves. And if self-driving is a tough challenge for cars, it’s all the more so for aircraft, where an unexpected control system failure isn’t just dangerous but likely deadly.

Given the scale of the challenge, the entry point of AI into human passenger flight won’t be as flashy as piloting eVTOLs; it’ll occupy a more modest, behind-the-scenes role. Already, data companies like Palantir and aviation industry stalwarts like Jeppesen and Thales are selling AI-enabled software that lets regulators, airlines, and flight dispatchers sift through masses of data to identify risks and plan aircraft and crew scheduling.

In September, the FAA announced that it deployed software built by the Boston-based data company Air Space Intelligence. The new AI-powered tool is called “Strategic Management of Airspace, Routes and Trajectories,” or SMART, and it’s aimed at “fundamentally reshaping how we manage our airspace.” The program isn’t intended to replace controllers, the government says, but to make doing their jobs easier by using predictive AI to head off scheduling snags. “Combining SMART with our ongoing hardware upgrades gives us the tools to cut flight delays, optimize traffic, and keep airspace capacity across the country open—all while maintaining our gold standard of safety,” FAA administrator Bryan Bedford said in a press release.

Then there’s the question of whether SMART could worsen the chronic shortage of air traffic controllers. The FAA hopes that the technology lessens the shortage by requiring fewer workers; other industries, though, have yet to see AI-generated efficiencies actually materialize. Even if the software doesn’t directly replace humans, the efficiency could be used to justify a workforce reduction. In May, the FAA reduced its staffing target for active air traffic controllers from the 2024 goal of 14,633 down to 12,563, citing “modern staffing models and scheduling tools.”

Some are more optimistic than others. “I think the SMART program is an important improvement,” Schiavo says. “No one wants the current aviation environment with midairs, runway incursions, myriad near misses, delays, groundings, loss of separation, and long taxi or clearance wait times.”

Michael McCormick, a professor of air traffic management at Embry-Riddle Aeronautical University, also sees advantages to a predictive tool. “When you have the computing capability to look at the entire trajectory of the aircraft, you can see where the conflicts are going to be,” he says. “And the general axiom in air traffic control is that the sooner you know about a potential conflict, the less effort is required to resolve it.”

That sounds great, but building machines that do a good job most of the time is one thing; machines that can function at the level of reliability required by aviation is another. At present, researchers are focusing on so-called deterministic neural networks—models trained offline whose weights are frozen before being deployed in the real world. These can’t hallucinate, but they may harbor other risky failure modes. In a 2021 paper, Darren Cofer, a researcher at Collins Aerospace, pointed out that when such systems find themselves in situations they haven’t encountered before in training, they can generate “unexpected (and potentially dangerous) outputs.”

The stakes will be even higher when AI software starts making real-time air traffic control decisions, which will start in airspace devoted to autonomous aircraft. According to McCormick, that’ll most likely be select corridors near drone hubs and eVTOL vertiports. With swarms of robot aircraft zipping back and forth, things will be too hairy for human pilots and controllers. “The objective is not to use traditional air traffic control,” he says, “because it would overwhelm the national airspace system if it tried to handle that volume and complexity of airframes moving around.”

With two systems working side by side—one with human decisionmakers, the other with AI—we’ll have a real-time basis to compare the performance of both approaches. Any computer-based system can potentially be hacked; any AI system creative enough to ideate novel solutions could also hallucinate crucial details. Without a human in the loop, seemingly obvious mistakes might go unnoticed until it’s too late.