AI, possibly. Algorithms, yes. Generative AI, fuck off all the way back to reddit where the training data came from.
High reliability organizations need deterministic tools that can be trained on so that operators can understand how they will work. They do not need an AI black box that might distract them with a hallucinated situation in the middle of a critical moment.
No one said this was generative AI, though. Which is good, because it’s not an LLM or genAI
AI/ML has long been used successfully to help predict future issues based on information from previous issues. It’s one of the things it excels at over humans, because it can process a much, much larger pool of data than a human can.
plus, AI is just a bunch of algorithms in a trench coat.
Give it few weeks, and they have collected meteics that the AI did the job just as good as the human within that timeframe. A few weeks down the line, the tables have turned, the humans are in charge of notifying the AI if it makes errors. A few weeks later, metrics will show that humans hasn’t really notified anything, and humans are removed from their position, leaving the AI fully in charge.
Within a year, a critical halucination or a job which AI lacks experience to handle will happen and a very preventable accident will occur. The owners will shrug it off as something that would definitely happen with humans in charge, and that the reduced costs outweigh the additional risk.
“Hallucinations” are produced by LLMs, which wouldn’t be appropriate for air traffic control. Automations of this type are done with Symbolic AI (aka “classical” or “logical” AI). Symbolic AI is built from sets of rules and conditions used by human beings to make the same decisions. This type of AI has been widely used in all kinds of control systems since the 1970s, and is completely unrelated to ChatGPT and other LLMs except by being called “artificial intelligence”.
It’ll probably be a deep learning model - some time series model that can factorise multiple input features like an RNN or LSTM. Those things work well within certain tolerances of their training data and are significantly more appropriate for this sort of thing than an LLM but as soon as something unusual happens they can react very weirdly - hopefully there are deterministic programmed guardrails that kick in and summon a human in edge cases.
It’s actually called Symbolic AI, which codifies clearly defined rules and behaviors - think decision trees and flowcharts. I doubt machine learning will be used in this case, since the rules and reasoning used by air traffic controllers have evolved over almost a century and are well understood. Machine learning is more for situations where the software has to discover the best way to operate because the rules aren’t well established.
Machine learning is more for situations where the software has to discover the best way to operate because the rules aren’t well established.
Or the machine needs to look at messy input data and recognise what the situation is so it can apply the more structured decision processes. You can’t feed a radar image to a bunch of if/elif/elif/else statements. That pattern recognition is fallible, but so are humans. Exciting times!
You can’t feed a radar image to a bunch of if/elif/elif/else statements.
You don’t need to input the image. You just need to input call sign, latitude, longitude, altitude, heading, speed, and emergency status (none, pan pan, or mayday) for each aircraft on radar.
The ATC will set the last one based on radio communications but the rest are either directly from or can be calculated from their transponders.
My worry is that the hype was created by generative AI, so when they talk about AI I’m afraid they mean LLM.
Wouldn’t controlling traffic be a NP problem and we could have a hesitation algorithm to do it (ironically those algorithms we used to call AI).
I also would be surprised they already don’t have mechanisms to validate choices made by traffic controller. That probably be a polynomial difficulty problem.
I think the main reason why they want to introduce AI there is so they can fire traffic controllers as they are major headache for Republicans when they keep government hostage.
I also would be surprised they already don’t have mechanisms to validate choices made by traffic controller. That probably be a polynomial difficulty problem.
In the air, most planes are required to have a Traffic Collision Avoidance System onboard. It will alert pilots if they are too close to other aircraft and what action to take if they’re too close. Pilots are required to perform the action if alerted regardless of what the traffic controller says.
Yes, because people don’t tune out when they have a machine doing most of the work. This is ridiculously stupid and dangerous. Don’t do work for them in trying to reason around it.
NHTSA reports human drivers to 1.9 incidents per million miles, and self driving cars companies refuse to give the mileage data. They are forced to give incidents rate data, and we can somehow estimate their milage and then we arrive at over 12 incidents per million miles for self driving levels 3-5.
Oh in 2025 NHTSA changed reporting requirements, to more relaxed, with less supervision and oversight, and no pushback or controls, laid off 25% of workers and changed it’s director to Morrison who was at the time Apple Self Driving Car Chief Council.
And even now it’s almost twice the rate of human driver per million miles.
Better drivers than the average human driver. Take male drivers out of the equation and it tips. Women drivers may be less secure at times (compared to male overconfidence) but they are far less likely to be reckless or cause lethal accidents.
A computer can’t get intoxicated, tired, or distracted. Humans can’t monitor dozens of sensors millions of times a second.
There are definitely still steps that need to be made to advance the technology, but it already has us beat. And it’s great. Traffic related deaths are a huge issue.
Human drivers: people die due to reckless driving and human mistakes - and in most situations a good driver can anticipate a lot of dangers and avoid them.
ML “assistants” getting control over cars: people die of unpredictable mis-assessments of inputs vs. outputs, and there’s no way to anticipate any danger or try to avoid it.
People who advocate for non-deterministic systems taking control in cars are irresponsible and have blood on their hands.
Your description of a human driver is no different than a self driving vehicle.
An input/output error is the equivalent to a human mistake. And those happen far less often than a human mistake. People make unpredictable stupid mistakes driving all the time.
If you think people make unpredictable mistakes all the time, you shouldn’t be driving a motorized vehicle. Because you clearly do not know what to anticipate.
Do unpredictable mistakes happen? Sure thing. But they are the rare exception, and almost all the time an aware driver will be cautious about situations so as not to get caught unaware.
I mean, this is potentially a good area where AI could augment human judgement.
Leave the human in control and have the AI note to them if they made an error or forgot about a plane or something.
Do not try and make it “self driving” or something.
Luckily the people in charge seem to have great judgement with this sort of thing
If you ever do stand-up, put me down for a ticket.
Depends on what level of “in charge” he means.
The career people who have run these things regardless of party in office have tended to be pretty good, historically.
Of course now many of these positions have been reclassified so that political stooges could be put in.
It’s unclear which level is actually implementing this and how much the Nero administration has their stupid, incompetent hands in it.
You mean the A.I. in charge.
AI, possibly. Algorithms, yes. Generative AI, fuck off all the way back to reddit where the training data came from.
High reliability organizations need deterministic tools that can be trained on so that operators can understand how they will work. They do not need an AI black box that might distract them with a hallucinated situation in the middle of a critical moment.
No one said this was generative AI, though. Which is good, because it’s not an LLM or genAI
AI/ML has long been used successfully to help predict future issues based on information from previous issues. It’s one of the things it excels at over humans, because it can process a much, much larger pool of data than a human can.
plus, AI is just a bunch of algorithms in a trench coat.
Then you have to say Machine Learning out front or everyone is going to assume you mean an LLM
Give it few weeks, and they have collected meteics that the AI did the job just as good as the human within that timeframe. A few weeks down the line, the tables have turned, the humans are in charge of notifying the AI if it makes errors. A few weeks later, metrics will show that humans hasn’t really notified anything, and humans are removed from their position, leaving the AI fully in charge.
Within a year, a critical halucination or a job which AI lacks experience to handle will happen and a very preventable accident will occur. The owners will shrug it off as something that would definitely happen with humans in charge, and that the reduced costs outweigh the additional risk.
“Hallucinations” are produced by LLMs, which wouldn’t be appropriate for air traffic control. Automations of this type are done with Symbolic AI (aka “classical” or “logical” AI). Symbolic AI is built from sets of rules and conditions used by human beings to make the same decisions. This type of AI has been widely used in all kinds of control systems since the 1970s, and is completely unrelated to ChatGPT and other LLMs except by being called “artificial intelligence”.
It’ll probably be a deep learning model - some time series model that can factorise multiple input features like an RNN or LSTM. Those things work well within certain tolerances of their training data and are significantly more appropriate for this sort of thing than an LLM but as soon as something unusual happens they can react very weirdly - hopefully there are deterministic programmed guardrails that kick in and summon a human in edge cases.
It’s called Machine Learning. AI is synonymous with LLM crap now.
It’s actually called Symbolic AI, which codifies clearly defined rules and behaviors - think decision trees and flowcharts. I doubt machine learning will be used in this case, since the rules and reasoning used by air traffic controllers have evolved over almost a century and are well understood. Machine learning is more for situations where the software has to discover the best way to operate because the rules aren’t well established.
Or the machine needs to look at messy input data and recognise what the situation is so it can apply the more structured decision processes. You can’t feed a radar image to a bunch of if/elif/elif/else statements. That pattern recognition is fallible, but so are humans. Exciting times!
You don’t need to input the image. You just need to input call sign, latitude, longitude, altitude, heading, speed, and emergency status (none, pan pan, or mayday) for each aircraft on radar.
The ATC will set the last one based on radio communications but the rest are either directly from or can be calculated from their transponders.
Well, it’s neither. This is not about to be used in the tower per other comments.
You’d be surprised what symbolic AI can do with messy data - in medical diagnosis, for example - but LLMs suck at it.
My worry is that the hype was created by generative AI, so when they talk about AI I’m afraid they mean LLM.
Wouldn’t controlling traffic be a NP problem and we could have a hesitation algorithm to do it (ironically those algorithms we used to call AI).
I also would be surprised they already don’t have mechanisms to validate choices made by traffic controller. That probably be a polynomial difficulty problem.
I think the main reason why they want to introduce AI there is so they can fire traffic controllers as they are major headache for Republicans when they keep government hostage.
In the air, most planes are required to have a Traffic Collision Avoidance System onboard. It will alert pilots if they are too close to other aircraft and what action to take if they’re too close. Pilots are required to perform the action if alerted regardless of what the traffic controller says.
Yes, because people don’t tune out when they have a machine doing most of the work. This is ridiculously stupid and dangerous. Don’t do work for them in trying to reason around it.
Although actual self driving cars are already better drivers than humans, although the bar is so low that Satan would have to dig for it.
Note, Teslas are not self driving. They’re mislabeled lane assist.
Where did you get that information from?
NHTSA reports human drivers to 1.9 incidents per million miles, and self driving cars companies refuse to give the mileage data. They are forced to give incidents rate data, and we can somehow estimate their milage and then we arrive at over 12 incidents per million miles for self driving levels 3-5.
Oh in 2025 NHTSA changed reporting requirements, to more relaxed, with less supervision and oversight, and no pushback or controls, laid off 25% of workers and changed it’s director to Morrison who was at the time Apple Self Driving Car Chief Council.
And even now it’s almost twice the rate of human driver per million miles.
That data includes Tesla
No, I excluded level 2, so excluding tesla shitty assistant
What definition of “lane assist” includes the ability to manage city driving while following a gps route with turns and stoplights?
Better drivers than the average human driver. Take male drivers out of the equation and it tips. Women drivers may be less secure at times (compared to male overconfidence) but they are far less likely to be reckless or cause lethal accidents.
Signed: a male :p
No, it still doesn’t tip.
A computer can’t get intoxicated, tired, or distracted. Humans can’t monitor dozens of sensors millions of times a second.
There are definitely still steps that need to be made to advance the technology, but it already has us beat. And it’s great. Traffic related deaths are a huge issue.
What’s not great is who owns the cars.
Human drivers: people die due to reckless driving and human mistakes - and in most situations a good driver can anticipate a lot of dangers and avoid them. ML “assistants” getting control over cars: people die of unpredictable mis-assessments of inputs vs. outputs, and there’s no way to anticipate any danger or try to avoid it.
People who advocate for non-deterministic systems taking control in cars are irresponsible and have blood on their hands.
Your description of a human driver is no different than a self driving vehicle.
An input/output error is the equivalent to a human mistake. And those happen far less often than a human mistake. People make unpredictable stupid mistakes driving all the time.
If you think people make unpredictable mistakes all the time, you shouldn’t be driving a motorized vehicle. Because you clearly do not know what to anticipate. Do unpredictable mistakes happen? Sure thing. But they are the rare exception, and almost all the time an aware driver will be cautious about situations so as not to get caught unaware.
Just wait til the next government shutdown. All AI baby. They don’t need canned goods or toothpaste.