Yep, and WSJ as well.

Say they're ready to replace their CEO with AI. Patient outcomes have improved significantly. Shareholders are crying.

Like “The Cloud” was going to get rid of the in-house computer department, this AI kool-aid is going to massively fail to deliver. A useful tool as long as it is applied in specific use cases and verified by a human. In this case, since you've fired all your radiologists and AIs are prone to hallucinations, you can't be sure its diagnosis is accurate. You would get lots of false positives or false negatives, with no one left to verify the results.

I'll agree as long as Mitchell H. Katz, MD signs off on AI making binding decisions for all of his and his family's healthcare!

So in our new world of irresponsibility and negligence by AI who takes on the liability and pays out the injury awards? Probably, some reverse Centaur...

There is a book coming out on this [1]topic soon! [macmillan.com]

We'll all be so happy when we are employed by AI which cannot legally be held liable for all the mistakes it makes and we see everyday.

[1] https://us.macmillan.com/books/9780374621575/thereversecentaursguidetolifeafterai/

There are two distinctly different types of errors when it comes to these kind of tests:

False Positives: This is where the test in question falsely says "You have Cancer!" when in fact you do not have it.

False Negatives: This is where the test in question falsely says "You are Healthy" when in fact you have cancer.

False Positives cost money and time, but it is fairly easy to double check them as they should be uncommon.

False Negatives cost human lives and are almost impossible to double check them as most people should test negative for cancer.

For an AI test, you want to have false positives. If it saves you money by not requiring humans to look things over, then costing you money and time to double check things is a fair trade. If it costs too much to double check, then do not use the AI.

False Negatives should be a no no. If the AI has more false negatives than human radiologists do, then do not use the AI test. No one cares how much money you are saving if people are dying.

Note, with regards to jobs, this will likely be relatively flat. There are not that many humans doing this job - they take the results from radiologist exams from all over the country and send them to just a few companies. Those companies find the few people that do it best and hire them. I bet we are talking about less than a hundred people in the US, especially as the best of the best will be kept to double check the results.

Therac-25 ?

Double checking. Haha. They barely look at the images when single checking. You think they are going to put any effort into double checking? What a joke.

> [CEO of America's Largest Public Hospital System] argued the technology presents an opportunity to simultaneously cut costs and expand access.

LOL! More like: "[CEO of America's Largest Public Hospital System] argued the technology presents an opportunity to simultaneously cut staffing costs and expand profits ."

Is that most situations could be more efficiently diagnosed by AI, but there's still a fair share of cases where experienced radiologists would be needed. In any case, I think it's just matter of time before AI can actually replace them. I mean, it's like the perfect use case for it.

For years now, radiology has been a poor career choice, but it only makes sense to send those digital images to the place with the cheapest doctors. Turns out one thing AI is really much better at than humans is analyzing digital images, so yes, radiology careers will soon be extent. All the job growth is in health care, but it's all in the jobs that require you to be in the same room as the patient. Administrators and back office staff are all getting laid off. The people that clean the rooms, body fluids and all? Hospitals can't get enough of them. (Five of my relatives all work at OSHU. Four are housekeeping, one is a pharmacy technician. They have pharmacy robots now...)

so, who gets sued for misdiagnosis? As long as liability remains with them- the CEO for making the decision.

But also... let me look at crystal ball...

-Costs go up, not down

-premium tier charge for human review

-waivers of liability

and of course- worse patient care outcomes

AI is not am effin replacement for life and death decision making - it is to inform and assist. Not Make them. Let me hallucinate lack of cancer... or better yet.. yet me hallucinate a cancer...

Just yesterday I stumbled on this substack post about a research paper whose authors found that AI scored well on x-ray evaluations even when the AI took the test WITHOUT ACCESS to the x-ray images.

[1]https://drjo.substack.com/p/wh... [substack.com]

The moral of this story is that properly evaluating AI performance in classification tasks requires very very carefully designed tests, because neural nets are very very good at picking up correlations between the desired outputs and utterly unintentional signals in the inputs.

[1] https://drjo.substack.com/p/who-needs-actual-x-rays

They will just get worse service. Anything else would be un-American.

will be when health insurance companies are replaced by AI

Where are the numbers? How about testing a radiologist + AI, rather than each against the other. I'll bet most people would prefer to have both involved in their care. I think they've skipped over the false negatives bit too. How do you ensure you're not missing a bunch of stuff? You'll need humans to find what the AI's miss. I'm not saying keep all the humans, but I am saying the vision and arguments presented are far from complete, and as usual, focus on the upfront costs rather than the overall cost

People who advocate for AI taking over tasks, should be help personally liable for the inevitable failure of the AI system

An accountability sink is a system or structure within an organization that obscures or deflects responsibility for decisions, making it difficult to identify who is accountable when things go wrong. This often occurs when decision-making is delegated to complex rules or automated processes, preventing effective feedback and learning from mistakes

Quoting thoughts from Cory Doctorow:

So there will be one Radioligist on staff whose job will be to vet and certify all AI determinations. This person will be the "

Twice, in fact -- once in an academic research lab and once at a company that designed and built medical imaging equipment.

In both cases we worked on image classification using digital image processing and statistical pattern recognition. (In one of the two cases we also used syntactic pattern recognition and machine learning.) It's very, very, very hard to make this accurate enough for clinical use even if you pour effort and time and money into it. There's no way this technology should be deployed w

I worked as a programmer at a medical billing company back in 2009, and let me tell you it was eye opening. We had radiologists working remotely (in 2009!) with mutliscreen setups that would show an original image on the left of one screen, a computer-enhanced version on the other side of the screen, with a computer generated opinion pre-generated at the bottom of the image (again: 2009 already had this). The other screen, usually rotated 90 degrees, would show minimal required relevant patient history/demographic on the top and offer a place to enter the radiologists opinion below, along with a button to copy over the computer-generated opinion.

Let's game out their options.

Let's say the agree with the computer, and they're right. No extra reward, they're just doing their job.

Let's say they agree with the computer, and they're wrong. Well, that must have been a hard case. Oh well.

Let's say they disagree with the computer, and they're right. Again, just doing their job./

But now if they disagree with the computer, and they're wrong, that is a world of malpractice lawsuit about to drop on their heads.

That is, every incentive this person has is to just always agree with the computer. There is no great bonus for doing better, and potentially huge consequences when they disagree. (And, by the way, this is now the training data for more recent AI options).

And it's this context we had at least one doctor billing $300,000.

Per month.

So, in this case at least, yes please bring on the AI. Because it's already doing it, and I'm sure the AI won't have to cost as much.

AI has never, ever gotten an image wrong ever. Anyway, "Sir, you have a 1910 model freight train in your kidneys. It simply cannot be mistaken."

Hospitals could potentially produce "major savings".....savings which in our for profit healthcare systems will no be passed down to the pati------er customers.