Look up validated and benchmarked against. AI will only be implemented if it is proven superior to humans. We are not there yet in medicine. The difference between chess and medicine is that the board is much larger in the latter so I am less optimistic about an all ruling AI. Furthermore, you need data to feed these systems. Are we gathering the correct data today? Furthermore, my experience from the field is that a bio marker that causes a disease is superior to any combination of proxy biomarker that a AI typically uses. See you own description of noisy data. I discussed the quality of data with a math professor working with AI earlier this week and his conclusion was that the amount of data was less important compared to diagnostic power of the data.But that’s just it.
Sure, the AI was bootstrapped by feeding it data from human pathologists. But by now we not only know that there’s no magic sauce that the humans provide, we know that there is information in the data that the computers can suss out that humans are completely unaware of, almost certainly including features that won’t ever “make sense” to humans.
So what you do is you train the AI not on the information provided by pathologists, but on the actual raw data. You don’t just feed the tagged X-ray images to the AI; you feed it all the medical history that the hospital network has on every patient. In addition to the images, you feed it lab work, you feed it all diagnoses of every condition, you feed it blood pressure, you feed it prescription refill records … you feed it everything.
Of course, the imagery is going to provide most of the information for a diagnosis. But I guarantee you that there’s some cluster of data that’s not on anybody’s radar that also correlates with cancer, and that’s going to let the AI uncover cases that no radiologist would ever notice. And that, in turn, will correlate with some feature on a scan that the radiologist will again be unaware of, so the AI re-reviews all stored images for that feature … which leads to follow-up diagnostics, and so on.
You yourself point to this: “One analysis or opinion is seldom sufficient for large decisions.” And that’s the whole point of “big data”: it automates the process of having teams of experts compare notes.
If you want a simpler case, think of chess. I remember the days when it was taken for granted that no computer would ever beat a grandmaster at chess — and, if it ever happened, it would be a sure sign of human-level intelligence in a computer. We now know otherwise, of course. But today, the thought that you need humans to “validate” a chess computer’s strategy is laughable. The chess computers are having tournaments amongst themselves that no human will ever be able to appreciate.
With ChatGPT passing the bar exam, we’re now at the stage where chess computers were when they started winning individual games in tournaments. They still didn’t have a chance at that time of winning a tournament, but they were running with the pack. Not long after, Deep Blue beat Kasparov. I won’t be surprised if, this time next year — and certainly no more than five years from now — ChatGPT (or some other AI) is consistently cranking out legal opinions that the lawyers who grade the bar exam admit are superior to their own. Will the humans still need to “validate” those machine-generated opinions?
The same will be true of every other academic discipline, sooner rather than later.
So … yeah. Worrying about students having ChatGPT write their essays for them is much ado about nothing. The entire professional class is about to face competition from robots that will make the threat Henry Ford’s assembly line posed to manufacturing jobs seem like a giant nothingburger.
b&
Images, blood values etc are proxy markers, at least for cancer. Cancer is not something strange. There is always a precise molecular mechanism involved and the medicine are developed against these molecular mechanisms.
At some point the AI will run out of compute power. There are 3 Gbases DNA in a human cells, >10 million SNP that modulated cellular processes, about 200 basic cell types (+all the intermediates) where each gene is expressed differently and the level and activity is modulated by SNP that may or may not cross talk. There are >100000 protein expressed at different levels. Furthermore, there are morphological differencies between humans and I am not talking about the face or body mass that influences clinical outcomes. These markers activity are not independent form each other a may cross react and we know not how yet. Furthermore, the immune activity differs between people so it is not an easy equation to solve. Currently cancer diagnostics, we are not measuring all of these markers and we certainly do not understand what each of them are doing. So you see, the board is far larger than chess or the law.
What scares me is the student blindly trust what comes out of a computer. A calculation maybe 6 order of magnitudes off and they still insist the computer is correct because it is a computer. If they do the same with AI we are far from a multifaceted vision needed to push society forward.