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”.
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.
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.
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.
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.
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.
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”.
Luckily the people in charge seem to have great judgement with this sort of thing
You mean the A.I. in charge.
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.
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.
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.
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
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.
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.
Just wait til the next government shutdown. All AI baby. They don’t need canned goods or toothpaste.