DOGE/SpaceX AI coming to FAA ATC- what’s really involved and already ready
As exhibited in the first three attached articles from Fast Company, AOL and Politico, the #47’s E.O.ed DOGE cost cutters have descended on the FAA ATC. The team arrived, now designated as computer experts, at the David J. Hurley Air Traffic Control Center in VA on President’s Day; a curious choice for learning about the FAA’s recent issues, since the ARTCC is a macro facility (flow) v. the towers (micro) where the computer/communications/DEI were involved. Faulty altimeters, open mike switches, etc. would not be as visible as assessing the massive complex of radars, computers and scopes at ATCTs and TOWERs. But as Mr. Musk has explained they are smarter!!!
The three articles that follow reveal (really?) what the DOGErs intend to do:
- “make rapid safety upgrades” to the complex web of software, hardware, facilities and people;
- squad plans to “plug in” to the air traffic control system to help make unspecified upgrades to unknown systems…
- Details about WHAT ROLE MUSK and his employees might play in changing the air traffic control system — or even what parts of the system are under their microscope — are MURKY.
- WHAT EXACTLY the effort may examine is UNCLEAR. But earlier Wednesday Duffy promised to “remake our airspace.”
- Musk… “pretty remarkable guy” who has “access to the best technological people, the best engineers in the world.”
- “…get a firsthand look at the current system, learn what air traffic controllers like and dislike about their current tools, and envision how we can make a new, better, modern and safer system,”
AI is a favorite tool of Mr. Musk and his techies. Not here but in other countries, this advanced application is being tested:
There are several real-world examples of AI being used in the UK’s air traffic control system:
1.LONDON HEATHROW AIRPORT: Heathrow is piloting an AI system called AIMEE (Artificial Intelligence for Monitoring and Event Extraction). This system integrates radar and video data to monitor aircraft movements, providing a comprehensive visualization of their positions. AIMEE helps controllers manage air traffic more efficiently, especially during low visibility conditions.
2. LONDON CITY AIRPORT: This airport became the world’s first major international airport to operate with a remote digital air traffic control tower. The technology uses ultra HD 4K cameras and AI to provide controllers with a detailed view of the airfield, even from a remote location.
- This technology could be immediately installed at lower level towers, freeing up experienced controllers for the short-staffed facilities- Might a proven ATC technology help diminish the Controller shortage? – JDA Journal
3.NATS Digital Tower Laboratory: NATS, the UK’s leading provider of air traffic control services, has invested in a ‘digital tower laboratory’ at Heathrow. This lab uses AI and machine learning technology to enhance landing capacity and improve passenger punctuality.
click on link to see video display
Rather invent a new wheel, maybe these SYSTEM already in-operation may really be able to be PLUGGED in NOW?
Artificial intelligence[1] is the subject of another paper attached here– Why the Aviation Industry Is Taking a More Cautious Approach to A.I. in the Cockpit. There are very useful references to FAA’s and EASA’s early thoughts on this subject. An expert, an aerospace engineer, a certified airline pilot, and a current partner at McKinsey & Company, adds insights from the tripartite background.
Its focus is the use of this super computational hardware and software, but the author’s sole focus is application in the cockpit. The lengthy analysis of this application to the flight crew does identify some broad concerns applicable to ATC systems. Most relevantly to the DOGE team, the following apt precaution is articulated:
…SLOWER, MORE CAUTIOUS approach to its potential applications in the cockpit. After all, the implications of a sophisticated A.I. system acting as copilot raise serious questions—such as, will it second-guess or even stop the human pilot from flying if the computer perceives an imminent emergency, which may or may not exist?
There are several significant programing markers identified, points to be carefully considered in designing AI for FAA ATC:
The initial focus is on DETERMINISTIC A.I., a form of machine learning in which the outcomes do not deviate from predefined rules. According to Riedel, that technology should be certifiable because the results are predictable. “Ultimately, it’s about reducing the pilot’s workload and making flying safer,” he says.
Then there’s NONDETERMINISTIC A.I., which is designed to learn, adapt, and offer a variety of responses to the same input. This form worries regulators, especially if the computer initiates a maneuver based on its own logic rather than a realistic flight situation. “We know we can’t rely on it 100 percent, but we can test and test and get to a level where we think we can trust it,” says Riedel, noting that, in any scenario, human pilots will be able to overrule the process. Of more concern is the potential for a breach in cybersecurity, allowing hackers to control the aircraft remotely.
The standard work of ATCers involves long strings of “IF-THEN” statements as the speed, altitude, direction, etc. for an aircraft at a point in the airspace. Standard proceedings generally fit the Deterministic AI logic; the information provided by NATS’ AIMEE fit the parameters of this AI programming. More on the characteristics of this specific function
Where these ATC professionals really earn their pay is when something unexpected occurs. That’s when the NONDETERMINISTIC A.I. becomes the relevant discipline and it is there that long lead times for iterative situational programming is mandated. Again, some reference material.
Promises of swift solutions have been made; it will be interesting to see what the AI wizards use as their risk tolerance for the soon-to-be implemented PLUG Ins.
Musk’s cost-cutters target U.S. aviation system
Story by Sam Ogozalek, Chris Marquette and Oriana Pawlyk
But wait there’s more excerpt from
ELON MUSK has pledged to deploy his “DOGE”[2] cost-cutting squad inside the innards of America’s air traffic control system, promising Wednesday to “make rapid safety upgrades” to the complex web of software, hardware, facilities and people that keep planes from crashing into each other.
“With the support of President @realDonaldTrump, the @DOGE team will aim to make rapid safety upgrades to the air traffic control system,” Musk posted to his social media platform X. Musk’s comment came shortly after Transportation Secretary Sean Duffy posted that he’d spoken to DOGE and that the squad plans to “plug in” to the air traffic control system to help make unspecified upgrades to unknown systems…
.
Details about WHAT ROLE MUSK and his employees might play in changing the air traffic control system — or even what parts of the system are under their microscope — are MURKY. But Musk’s social media post referenced problems the agency has had with a system of notifying pilots about hazards, called “notice to air missions” (NOTAMs). The system went down over the weekend, though a backup system kicked in to ensure there were no major disruptions.
WHAT EXACTLY the effort may examine is UNCLEAR. But earlier Wednesday Duffy promised to “remake our airspace.”
Duffy said that he’d spoken with Musk on Tuesday, calling him a “pretty remarkable guy” who has “access to the best technological people, the best engineers in the world.”
“We’re gonna remake our airspace,” Duffy continued. “And we’re gonna do it quickly, and we have the support of the Congress, I think right now, to say, you know what, we’re using like 1960s, World War II technology in much of the components of the airspace. We’re gonna upgrade it.”
Controllers currently use antiquated equipment, including a radar-based system of keeping track of planes. An effort to transition to a satellite-based air traffic control system known as NextGen has been underway for years, but has been beset by cost overruns and delays…
Why the Aviation Industry Is Taking a More Cautious Approach to A.I. in the Cockpit
Deterministic A.I. is the focus, but an alternate version could improve safety and create situational intelligence.
Published on February 16, 2025
By Daniel Cote Robb Report
While the speed at which artificial intelligence (A.I.) is pervading mainstream society could seemingly break the sound barrier, aviation authorities are taking a SLOWER, MORE CAUTIOUS approach to its potential applications in the cockpit. After all, the implications of a sophisticated A.I. system acting as copilot raise serious questions—such as, will it second-guess or even stop the human pilot from flying if the computer perceives an imminent emergency, which may or may not exist?
The answer is not yet definitive. The Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) both published papers acknowledging A.I.’s future in aircraft operations, EMPHASIZING THAT SAFETY NEEDS TO BE THE PRIMARY CRITERION FOR CERTIFICATION. EASA forecasts a three-stage implementation: A.I. first assisting human pilots with information, then human and A.I. “teams” working together through 2035, and, finally, advanced automation and autonomous flight after 2035.
“People feel comfortable with a human pilot in the cockpit,” says Robin Riedel, an aerospace engineer, a certified airline pilot, and a current partner at McKinsey & Company. “Elevators used to be run by humans for much the same reason, but there aren’t many elevator operators these days.”
Riedel points to the fact that A.I. already exists across private aviation, including aircraft design, operations, and maintenance scheduling. Autopilot systems, fly-by-wire controls, and synthetic vision, while not the equivalent of an A.I. copilot, are also all heavily computer dependent[3]. “A.I.’s not 30 years away,” he says. “It’s already in the cockpit.”
The initial focus is on DETERMINISTIC A.I., a form of machine learning in which the outcomes do not deviate from predefined rules. According to Riedel, that technology should be certifiable because the results are predictable. “Ultimately, it’s about reducing the pilot’s workload and making flying safer,” he says.
Then there’s nondeterministic A.I., which is designed to learn, adapt, and offer a variety of responses to the same input. This form worries regulators, especially if the computer initiates a maneuver based on its own logic rather than a realistic flight situation. “WE KNOW WE CAN’T RELY ON IT 100 PERCENT, but we can test and test and get to a level where we think we can trust it,” says Riedel, noting that, in any scenario, human pilots will be able to overrule the process. Of more concern is the potential for a breach in cybersecurity, allowing hackers to control the aircraft remotely.
Despite public apprehension and certification hurdles, Swiss start-up DAEDALEAN[4] AI has created a vision system named PILOTEYE that uses a neural network to identify and categorize approaching aircraft or other airborne objects. It’s poised to be one of the first nondeterministic cockpit applications. “The goal is to improve safety and create situational intelligence,” says Yemaya Bordain, Daedalean AI’s chief commercial officer and president of the Americas. Bordain assures that it WON’T MAKE DECISIONS FOR THE PILOT BUT WILL PROVIDE VISUAL AND VERBAL ALERTS AND EVEN GUIDANCE ON LANDINGS. She asserts that the program differs from other nondeterministic A.I. “because we trained our model in the field, so it’s representative of the real world.”
In 2023, Daedalean successfully flight-tested the system with Leonardo Helicopters, and its research collaboration with EASA helped inform the agency’s guidelines. The Zurich-based company is working toward certification of PilotEye later this year. “We’re showing how nondeterministic doesn’t have to mean non-certifiable,” says Bordain. Realistically, though, with no clear regulations and little public understanding, it could take advanced A.I. considerably more time to earn its wings.
[1] For those like me who need a primer on AI –The Alignment Problem is highly recommended
[2] The Department of Government Efficiency, officially the U.S. DOGE Service Temporary Organization, is an initiative of the second Trump administration led by Elon Musk. Despite its name, DOGE is not a Cabinet-level department but rather a temporary contracted organization under the United States DOGE Service.
[3] Actually, many of these AI features were first introduced in commercial aircraft.
[4] Daedalean refers to something that is ingeniously or cunningly designed, often intricate or skillful. It can also describe something that is complex or difficult to understand.
