Demand for human radiologists is at an all-time high

Not only that but they are even less capable of taking off on their own (see the work done by Airbus' ATTOL project [0] on what some of the more recent successes are).

So I'm not sure what "planes can land on their own" gets us anyway even if autopilot on modern airliners can do an awful lot on their own (including following flight plans in ways that are more advanced than before).

The Garmin Autoland basically announces "my pilot is incapacitated and the plane is going to land itself at " without asking for landing clearance (which is very cool in and of itself but nowhere near what anyone would consider autonomous).

[0] https://www.youtube.com/watch?v=9TIBeso4abU (among other things, but this video is arguably the most fun one)

Edit: and yes maybe the "pilots are basically superfluous now" misconception is a pet peeve for me (and I'm guessing parent as well)

Self driving cars in 2025 in USA is like Solar PV in China in 2010, it will take a while, but give them time to learn, adapt and expand.

I think its the other way around AI would certainly have better accuracy than a human, AI can see things pixel by pixel.

You can take a 4k photo of anything, change one pixel to pure white and a human wouldn't be able to find this pixel by looking at the picture with their eyes. A machine on the other hand would be able to do it immediately and effortlessly.

Machine vision is literally superhuman, For example Military camo can easily fool human eyes. But a machine can see through it clear as day. Because they can tell the difference between

Black Hex #000000 RGB 0, 0, 0 CMYK 0, 0, 0, 100

and

Jet Black Hex #343434 RGB 52, 52, 52 CMYK 0, 0, 0, 80

> Most tools can only diagnose abnormalities that are common in training data, and models often don’t work as well outside of their test conditions.

I don’t understand this. All data in existence is fodder for training. Barring the privacy issue which the article implies as orthogonal, training data and actual data are the same set of things.

Test conditions should be identical to real conditions. What in the world is the article saying. What actual differences are there?

The only issue I can think of is when there is LLM like language logic in looking at the results of a scan. Like for example the radiologist looks at 30 sections of the image and they all have different relationships with each other and those relationships end up influencing the outcome. But I doubt it’s like that, radiology should be much simpler than learning a foreign language.

You know the crazy thing about this? For this application I think it’s similar to spam. AI can easily be trained to be better than a human.

And it’s definitely not a 0.05 percent difference. AI will perform better by a long shot.

Two reasons for this.

1. The AI is trained on better data. If the radiologist makes a mistake that mistake is identified later and then the training data can be flagged.

2. No human indeterminism. AI doesn’t get stressed or tired. This alone even without 1. above will make AI beat humans.

Let’s say 1. was applied but that only applies for consistent mistakes that humans make. Consistent mistakes are eventually flagged and shows up as a pattern in training data and the AI can learn it even though humans themselves never actually notice the pattern. Humans just know that the radiologists opinion was wrong because a different outcome happened, we don’t even have to know why it was wrong and many times we can’t know… just flagging the data is enough for the AI to ingest the pattern.

Inconsistent mistakes comes from number 2. If humans make mistakes that are due to stress the training data reflecting those mistakes will be minuscule in size and also random without pattern. The average majority case of the training data will smooth these issues out and the model will remain consistent. Right? A marker that follows a certain pattern shows up 60 times in the data but one time it’s marked incorrectly because of human error… this will be smoothed out.

Overall it will be a statistical anomaly that defies intuition. Similar to how flying in planes is safer than driving. ML models in radiology and spam will beat humans.

I think we are under this delusion that all humans are better than ML but this is simply not true. You can thank LLMs for spreading this wrong intuition.