I just want to point out that the term "A.I." gets used pretty loosely in these articles, as if A.I. is a monolithic commodity that you plugin to your software to make it do chatGPT.
The example in the article is an in house developed "A.I." to help radiologists assess images. Digging a bit deeper it seems they are using mostly old CNN type architectures with a few million parameters.[1]
I think it still remains to be seen what a 1T+ parameter transformer trained specifically for radiology will do. I think anyone would be confident that a locally run CNN will not hold a candle to it.
There are many, many papers and projects out there about tuning foundation models on various types of medical imaging data, and many organized efforts to produce large medical imaging datasets to feed that training. This stuff is well-known in the trenches and can improve on the older, smaller CNNs in some ways, but not in a way that's produced any step change in automated capabilities. People are certainly working on it!
seesthruya · 26m ago
Agreed
seesthruya · 2h ago
Working radiologist here, 20 years experience.
This article is surprisingly accurate. I fully expect to finish my career without being 'replaced' by AI.
Happy to debate/answer questions :-)
belly_joe · 1h ago
I would say generally speaking that people who assume AI will replace somebody else's job believe that these jobs are merely mechanical and there is no high-level reasoning involved that would basically require AGI (when that comes about nobody is safe). So the model of the AI radiologist assumes the only job of a radiologist is to classify images, which is pretty vulnerable to near-future disruption.
I imagine, given the training involved, the job involves more than just looking at pictures? This is what I would like to see explained.
The analogy would be the "95% of code is written by AI" stat that gets trotted out, replacing code with image evaluation. Yes AI will write the code but someone has to tell the AI what to write which is the tricky part.
TuringNYC · 8m ago
>> jobs are merely mechanical and there is no high-level reasoning involved
This is a very binary way of thinking about it. More usual is that components of many professions are mechanical and can be automated, while other components are not mechanical and thus harder to automate. Regardless, if some % of the mechanical work goes away, it is unlikely that human workers just work less. Instead, they will work just as much and the overall demand for workers is reduced by %
tbrownaw · 44m ago
We already have AI taxis (in specific limited areas, but still). Driving isn't something I'd usually call "merely mechanical".
tintor · 21m ago
Driving (in US) is considered unskilled labor.
seesthruya · 1h ago
100%
Al-Khwarizmi · 1h ago
If (as acknowledged in the article) AI automates at least part of the work of radiologists (e.g. tool that "saves her 15 to 30 minutes each time she examines a kidney image"), don't you fear that the demand of radiologists will decline? Even if some are still needed, surely if a hospital needs X reports per day and now Y radiologists are sufficient to provide them rather than the current Z (Y<Z), that should be something for people considering your career to take into account?
On the other hand, how much of your confidence in not being replaced stems from AI not being able to do the work, and how much from legal/societal issues (a human needing to be legally responsible for the diagnoses)? Honestly the description in the article of what a radiologist does "Radiologists do far more than study images. They advise other doctors and surgeons, talk to patients, write reports and analyze medical records. After identifying a suspect cluster of tissue in an organ, they interpret what it might mean for an individual patient with a particular medical history, tapping years of experience" doesn't strike me as anything impossible for AI within a few years, now that models are multimodal and they can work with increasing amounts of text (e.g. medical histories).
postexitus · 1h ago
No. There is no area of medicine where a boost in productivity will cause doctors to have idle time. The wait times may decrease, throughput may increase, diagnosis accuracy may improve, even costs may decrease (press x to doubt) but no, there will never be a case where we will need less radiologists.
TuringNYC · 5m ago
>> No. There is no area of medicine where a boost in productivity will cause doctors to have idle time. The wait times may decrease, throughput may increase, diagnosis accuracy may improve, even costs may decrease (press x to doubt) but no, there will never be a case where we will need less radiologists.
I dont think this is how market participants may think about it. If costs decrease, some group of radiologists will drop out of the market. We may not "need" less radiologists, but we're signaling we need less of them by not paying them as much as before.
Much like I still "need" a photographer, but short of weddings, I'm not willing to pay as much as before. I may well acquire a photogrpher for a portrait, but it would have to be priced competitively to a selfie.
whynotminot · 59m ago
Which may take us to a sort of “Jevens Paradox” kind of place except for medical care.
Like there are times already where I’ve put off or not sought medical care because of the hassle involved.
If I could just waltz into the office and get an appointment and have an issue seen to same day I would probably do it more often.
KerrAvon · 7m ago
To be clear, we also need more medical professionals in general -- they're not keeping up with the population and it's making us all less healthy. Three to six months, or more, in the SF bay area for some critical appointments is really unacceptable, but there's not really an option given supply and demand.
I'm sure this will all get better with captain brainworms at the helm.
seesthruya · 1h ago
There is a national shortage of radiologists in the US, with many hospital systems facing a backlog of unread cases measuring in the thousands. And, the baby boomers are starting to retire, it's only going to get worse. We aren't training enough new radiologists, which is a different discussion.
Askl to your question on where my confidence stems from, there are both legal reasons and 'not being able to do the work' reasons.
Legal is easy, the most powerful lobby in most states are trial attorneys. They simply won't allow a situation where liability cannot be attached to medical practice. Somebody is getting sued.
As to what I do day to day, I don't think I'm just matching patterns. I believe what I do takes general intelligence. Therefore, when AI can do my job, it can do everyone else's job as well.
radiologist72 · 1m ago
You say "Legal is easy, the most powerful lobby in most states are trial attorneys."
The most powerful lobby in this case is the ABR which carefully constricts coveted residency spots in Radiology to create an artificial scarcity and keep up incomes. It is the opposite of, say, technology, where we have no gatekeeper and supply increases.
The ABR will say that Medicare doesnt fund enough residency spots, but all you need to do is look at an EoB and see that a week of residency billings covers the entire cost of the resident.
mullingitover · 20m ago
> We aren't training enough new radiologists, which is a different discussion.
About that, I think the AMA is ultimately going to be a victim of its own success. It achieved its goal of creating a shortage of medical professionals and enriching the existing ones. I don't think any of their careers are in danger.
However, long term, I think magic (in the form of sufficiently advanced technology) is going to become cost effective at the prices that the health care market is operating at. First the medical professionals will become wholly dependent on it, then everyone will ask why we need to pay these people eye-watering sums of money to ask the computers questions when we can do that ourselves, for free.
seesthruya · 16m ago
I agree with you on all points. The only question is how long will it take?
reissbaker · 13m ago
The trial lawyer angle doesn't seem accurate. Did trial lawyers prevent pregnancy tests from rolling out? COVID tests? Or any other automatic diagnostic, as long as it was reasonably accurate?
Not as far as I know. Once an automated diagnostic is reasonably accurate, it replaces humans doing the work manually. The same would be true of anything else that can be automatically detected.
No comment on whether radiology is close to that yet, although I don't think a few-million-param neural network would tell us much one way or another.
6stringmerc · 1h ago
A big wrinkle in AI evangelism is that proponents don’t understand the concept of human judgment as a “learned” skill - it takes practice and AI models / systems do not suffer consequences the way humans do. They have no emotions and therefore can not “understand” the implications of their decisions.
For context, generative AI music is basically unlistenable. I’ve yet to come across a convincing song, let alone 30 seconds worth of viable material. The AI tools can help musicians in their workflow, but they have no concept of human emotion or expression and it shows. Interpreting a radiology problem is more like an art form than a jigsaw puzzle, otherwise it would’ve been automated long ago (like a simple blood test). Like you note, the legal system in the US prides itself on “accountability” (said tongue in cheek) and AI suffers no consequences.
Just look how well AI worked in the United Healthcare deployment involving medical care and money. Hint: stock is still falling.
ToValueFunfetti · 39m ago
>For context, generative AI music is basically unlistenable. I’ve yet to come across a convincing song, let alone 30 seconds worth of viable material.
It's not really my genre, so my judgment is perhaps clouded. Also, I find the dumb lyrics entertaining and they were probably written by a human (though obviously an AI could be prompted to do just as well). I am a fan of unique character in vocals and I love that it pronounces "A-R-A" as "ah-ahr-ah", but the little bridge at 1:40 does nothing for me.
mullingitover · 18m ago
You may have missed the month or so where this[1] AI-generated track (remixed by a person, but nonetheless) dominated pop culture.
> A big wrinkle in AI evangelism is that proponents don’t understand the concept of human judgment as a “learned” skill
Which is ironic given how much variation in output quality there is based on the judgement of the person using the LLM (work scope, domain, prompt quality, etc.)
dingnuts · 1h ago
if the cost for preventative scans goes down, demand will rise. medical demand is incredibly constrained by price. people skip all kinds of tests they need because they can't afford it. the radiologists will have more work to do, not less.
bparsons · 54m ago
There is a perpetual shortage of these types of technicians, so it is unlikely that demand for those jobs will drop.
M95D · 1h ago
Respectfully, it doesn't matter what you expect or think. What matters is this:
- If the law allows AI to replace you.
- If the hospital/company thinks [AI cost + AI-caused law suits] will be less expensive that [your salary + law suites caused by you].
I'm almost in the same situation as you are. I have 22 years left until retirement and I'm thinking I should change my career before I'm too old to do it.
And, I didn't say I would never be replaced. I said I would finish my career, which is approximately 10 more years at this point.
candiddevmike · 1h ago
What career would you change to that would be safe, given the conditions you provided and your time horizon?
jerf · 1h ago
The original author of the paper about the technological singularity [1] defines it as simply the point where predictions break down.
If AI gets to the point where it is truly replacing radiologists and programmers wholesale, it is difficult to tell anyone what to do about it today, because that's essentially on the other side of the singularity from here. Who knows what the answer will be?
(Ironically, the author of that paper, being also a science fiction author, is also responsible for morphing the singularity into "the rapture for nerds" in his own sci-fi writing. But I find the original paper's definition to have more utility in the current world.)
I think that if AI can replace software engineers then AI can replace any job because the domain of software engineering is pretty much everything.
FeteCommuniste · 27m ago
I don't think robotics is progressing at nearly the same pace as AI so for a while there will still be a bunch of manual labor for us to fight over. :-)
pc86 · 1h ago
Crime?
tarunkotia · 1h ago
I worked on an autocontouring model but we could not get very high accuracy for it to be adopted commercially. The algorithm would work for some organs but would totally freak-out on the others. And if the anatomy was out of norm then it would not work at all. This was 5 years ago, I see Siemens [0] has a similar tool. I remember shadowing a dosimetrist contouring all the Organs-At-Risk (OAR) and it took about 3-4 hours to contour one CT image of thoracic region. Do you know how much better the autocontouring tools have become?
As my wife says: "Until it's as easy to sue AI as it is doctors, we probably won't see AI replacing doctors."
newyankee · 1h ago
May be in the West. However more practical countries like China with a huge population and clear incentive to provide healthcare to a large population at reduced cost will have incentives to balance accuracy and usefulness in a better way.
My personal opinion is that a lot of Medical professionals are simply gatekeeping at this point of time and using legal definitions to keep changing goalposts.
However this is a theme that will keep on repeating in all domains and I do feel that gradual change is better than sudden, disruptive change.
laborcontract · 20m ago
> May be in the West. However more practical countries like China with a huge population and clear incentive to provide healthcare to a large population at reduced cost will have incentives to balance accuracy and usefulness in a better way.
This is a really interesting point that I haven't considered. Namely, regulatory arbitrage is going to yield enormous benefits in the medical AI space. The sheer amount of data needed to train the model requires data centralization the west has no desire to move toward. But if China does crack the nut, it seems like it will necessarily create an upheaval in the west, whether we like it or not.
candiddevmike · 1h ago
AI in healthcare is going to add so many layers of indirection for malpractice lawsuits. You'll spend years and lots of $$$ trying to figure out who the defendant would ultimately be, only for it to end up being a LLC that unfortunately just filed for bankruptcy.
educasean · 1h ago
The worry isn't that you'll find an AI sitting on the chair that a radiologist used to sit. It's that the entire field of radiology gets reduced down to a button click on a software.
The other doctors will still be there for you to sue.
ogogmad · 1h ago
What if ppl just bought the equipment and did the scans at home?
mikestew · 1h ago
So the question is, “what if people bought an x-ray machine (affordably available on Amazon)and started using it without training on radiological safety”?
SketchySeaBeast · 41m ago
I assume followed shortly by "what is this weird red splotch on my skin?"
ceejayoz · 1h ago
Have you priced out a CT scanner and MRI?
Will you be able to source a radioactive source for your x-rays?
lostlogin · 1h ago
The X-Ray source is the X-ray machine. You may be referring to nuclear medicine which injects radioactive stuff, or radiation therapy.
DIY radiation therapy would be a whole new level.
ceejayoz · 44m ago
> The X-Ray source is the X-ray machine.
Healthcare-grade x-ray tubes to put in your (expensive) x-ray machine are not something you easily can obtain without a license.
ogogmad · 1h ago
Fair. But what if ppl instead got scans in "radiology shops" without waiting for a specialist? Specialists are expensive.
SketchySeaBeast · 1h ago
Isn't that 90% of going to get scan is right now? You'll still need the "shop" to provide the equipment and the tech with the training to know what/where to scan, but you might get the results a bit faster? Are the radiologists the chokepoint now, or is it the techs?
TuringNYC · 11m ago
>> Happy to debate/answer questions :-)
Curious -- do you think that is because
1. the technology isnt there, or
2. because it isnt a competitive market (basically, the American Board of Radiologists controls standards of practice and can slow down technologies seen as competitive to human doctors)?
3. or perhaps 1 doesnt happen because outsiders know the market is guarded by the market itsself?
janice1999 · 1h ago
Are AI models able to detect abnormalities that even an experienced radiologist can't see? i.e. something that would look normal to a human eye but AI correctly flags it for investigation? Or are all AI detections 'obvious' to human eyes and simply a confirmation? I suspect the latter since it was human annotated images the model was trained on.
seesthruya · 1h ago
Depends on what you mean by 'see'.
For example, let's say I'm looking at a chest x-ray. There is a pneumonia at the left lung base and I am clever enough to notice it. 'Aha', I think, congratulating myself at making the diagnosis and figuring out why the patient is short of breath.
But, in this example, I stop looking closely at the X-ray after noticing the pneumonia, so I miss a pneumothorax at the right lung apex.
I have made a mistake radiologists call 'satisfaction of search'.
My 'search' for the patient's problem was 'satisfied' by finding the pneumonia, and because I am human and therefore fundamentally flawed, I stopped looking for a second clinically relevant diagnosis.
An AI module that detects a pneumothorax is not prone to this type of error. So it sees something I did not. But it doesn't see something that I can't see. I just didn't look.
I'm skeptical to the claim that AI isn't prone to this sort of error, though. AI loves the easy answer.
the_sleaze_ · 39m ago
AI is overloaded. An LLM loves the easy answer, but that's not what is underlying an image classification model.
alabastervlog · 1h ago
> I have made a mistake radiologists call 'satisfaction of search'.
Ah, now I have a name for it.
When I've chased a bug and fixed a problem I found that would cause the observed problem behavior, but haven't yet proven the behavior is corrected, I'm always careful to specify that "I fixed a problem, but I don't know if I fixed the problem". Seems similar: found and fixed a bug that could explain the issue, but that doesn't mean there's not another one that, independently, would also cause the same observed problem.
I've been going to RSNA for over 25 years, in all that time, the best I've seen from any model presented to me was the smack the radiologist on the head and say, "you dummy, you should have seen that!" model.
That is, the models spot pathologies that 99.9999% of rads would spot anyway if not overworked, tired, or in a hurry. But, addressing the implication of your question, the value is actually in spotting a pathology that 99.9999% of rads would never spot. In all my years developing medical imaging startups and software, I've never seen it happen.
I don't expect to see it in my lifetime.
SketchySeaBeast · 56m ago
I'm sure it's a matter of training data, but I don't know if it's a surmountable problem. How do you get enough training data for the machine to learn and reliably catch those exceptions?
seesthruya · 56m ago
I have a fairly strong background in tech, and I've been programming computers since 1979 when my dad bought me a TRS-80. Tape drives FTW!
I agree with almost everything you've said here.
Except 'not in my lifetime', because I plan on living for a very long time, and who knows what those computer nerds will come up with eventually ;-)
LanceH · 34m ago
At the same time it can be a handy tool to be a first cut at triage.
It's really not a matter of "full replacement or bust".
stackedinserter · 1h ago
What's accurate in this article? It's very vague, it can be tldred into "we won't go anywhere, although AI does more and more of our work"
> Radiologists do far more than study images. They advise other doctors and surgeons, talk to patients, write reports and analyze medical records. After identifying a suspect cluster of tissue in an organ, they interpret what it might mean for an individual patient with a particular medical history, tapping years of experience.
AI will do that more efficiently, and probably already does. "tapping years of experience" is just data in training set.
> A.I. can also automatically identify images showing the highest probability of an abnormal growth, essentially telling the radiologist, “Look here first.” Another program scans images for blood clots in the heart or lungs, even when the medical focus may be elsewhere.
> “A.I. is everywhere in our workflow now,” Dr. Baffour said.
> “Five years from now, it will be malpractice not to use A.I.,” he said. “But it will be humans and A.I. working together.”
Maybe you'll be able to happily retire because inertia, but overall it looks like elevator operator job.
What's so special about radiology?
seesthruya · 1h ago
There's nothing special about radiology. And I do believe inertia will carry me through the end of my career, which has approximately 10 years left.
However, it's my opinion that my job takes general intelligence, not just pattern matching.
Therefore, when I lose my job to AI, so does everyone else.
doctorpangloss · 24m ago
On the one hand, you’re totally right. The job takes general intelligence.
On the other hand, a lot of jobs take general intelligence. You’re right about that too.
It’s difficult to guess the specifics of your life, but: maybe you’ve engaged a real estate agent. Some people use no real estate agent. Some have a robo agent. No AI involved. Maybe you have written a will. Some people go online and spend $500 on templates from Trust & Will, others spend $3,000 on a lawyer to fill in the templates for them, some don’t do any of that at all. Even in medicine, you know, a pharma rep has to go and convince someone to add their thing to the guidelines, and you can look back at the time between the study and adoption as, well people were intelligent and there was demand, but doctors were not doing so and so thing due to lack of essentially sales. I mean you don’t have to be generally intelligent to know that flossing is good for you, and yet: so few people floss! That would maybe not put tons of dentists out of business. But people are routinely doing (or not doing) professional services stuff not for any good (or bad) reason at all.
Clearly the thing going on in the professional services economy isn’t about general intelligence - there’s already lots of stuff that is NOT happening long before AI changes the game. It’s all cultural.
If you’ve gotten this far without knowing what I am talking about… listen, who knows what’s going to happen? Clearly a lot of behavior is not for any good reason.
How do you know where the ball is going to go for culture? Personally I think it’s a kind of arrogant position: “I’m a member of the guild, and from my POV, if my profession is replaced, so is everyone else’s.” Arrogance is not an attractive culture, it’s an adversarial one! And you could say inertia, and yet: look who’s running the HHS! There are kids right now, that I know in my real life, who look like you or me, who went to fancy Ivy League school, and they are vaccine skeptical. What about inertia and general intelligence then? So I’ll just say, you know, putting yourself out here on this forum, being all like, “I will AMA, I am the voice,” and then to be so arrogant: you are your own evidence for why maybe it won’t last 10 years.
seesthruya · 10m ago
All good points! Nobody knows the future!
I jumped into this thread to share my thoughts, and my thoughts alone, because I'm not sure there are a lot of radiologists on HN. I certainly don't speak for all radiologists.
But, I would submit to you, that rapid, radical changes to the practice of medicine are rare, if not impossible.
bilbo0s · 1h ago
Medical Imaging tech entrepreneur here.
Been going to RSNA for longer than you've been a radiologist. In all that time, I've never come across an AI that I felt was fit for purpose.
I wholeheartedly agree with you.
Many many reasons for this, and I'm happy to chime in from the tech side of things and fill in any blanks outside your knowledge domain.
The key to the power of the LLM is that the training process can learn effectively from vast corpora of unlabelled text. Unfortunately, there is no comparably vast database of medical images.
In order to "crack" radiology, the AI companies would need to launch an enormous data collection program involving thousands of hospitals across the world. Every time you got an MRI or X-Ray, you would sign some disclosure form that allowed your images to be anonymously submitted to the central data repository. This kind of project is very easy to describe, but very difficult to execute.
seesthruya · 28m ago
I agree with you, but here is where things get tricky:
Everyday I see something on a scan yhat I've never seen before. And, possibly, no one has ever seen before. There is tremendous variation in human anatomy and pathology.
So what do I do? I use general intelligence. I talk to the patient. I talk to the referring doctor. I compare with other studies, across modalities and time.
I reason. I synthesize. I think.
So my point is, basically, radiology takes AGI.
physicsguy · 32m ago
They’ll have better luck in countries like the U.K. where medical data is at least somewhat more organised by virtue of being under the NHS umbrella
justlikereddit · 23m ago
>Unfortunately, there is no comparably vast database of medical images.
Even a tiny hospital with radiology services will produce many thousands of images with accompanying descriptions every year. And you are allowed to anonymize and do research on these things in many places as neither image nor accompanying description is a personal identifier.
So this is yet another Hinton-ish prediction, any time soon radiologist are going dodo. This time LLMs will crack the nut that image recognition have failed at for 20 years.
Where LLMs have succeeded is in doing hot takes that miss the mark, they should be really good at cornering the "prematurely predicting demise of radiologist"-market
EcommerceFlow · 42m ago
So are datasets/currently available data the limitation here?
Let's say a major healthcare leak occurred, involving millions of images and associated doctor notes, diagnostics, etc... would this help advance the field or is it some algorithmic issue?
pj_mukh · 1h ago
"The staff has grown 55 percent since Dr. Hinton’s forecast of doom, to more than 400 radiologists."
Wonder what other forecasts of doom he is wrong about :|.
yread · 1h ago
They are also all driving themselves to the hospital instead of using self-driving cars. Different forecaster though
No comments yet
airstrike · 20m ago
So will it cost me less than $1.5k the next time I need an x-ray?
bobowzki · 1h ago
The thing I find most interesting about ML in radiology is that a computer can observe the entire dynamic range of the sensor at once. A human will only look at a window or a compressed window.
husarcik · 1h ago
This is a very key point. Perhaps that discrepancy can be leveraged in image generation to save time.
bilbo0s · 1h ago
It already is, which is why rads input window/level settings.
roenxi · 1h ago
This reminds me of the idea that Human-Chess partnerships would be the ultimate manifestation of Chess genius. I'm not sure whether the idea is still holding on but engines are so far ahead of human play that I doubt a human in the loop can add anything these days given how devastatingly far ahead the engines are and the advent of machine learning techniques.
husarcik · 1h ago
Chess reminds me more of programming given the set of defined rules in each. However, I'm biased as I work in radiology and program more as a hobby. So far I've seen way more tools to help me code than to accurately detect radiologic findings.
ogogmad · 1h ago
So far. Computer vision is currently lagging NLP, but I wouldn't expect that to last.
johnmaguire · 1h ago
> but I wouldn't expect that to last
Do you have any links to research or work being done on computer vision that leads you to this conclusion? Would love to check it out!
startupsfail · 1h ago
You can compare best image synthesis and image understanding from two decades ago (SIFT / HOG), from a decade ago (CNN, SdA) and now (Transformer). Very rapid progress that went from being able to unreliability recognize a face to getting to outperforming human professionals (see MMMU) is quite remarkable.
johnmaguire · 18m ago
AIUI, and I may be wrong, but each of the mentioned technologies was a "breakthrough" technology - not iterative improvement. Along this vein, I was wondering if there was some promising, novel research OP was aware of for image understanding.
The most recent of which you mentioned, Transformers, is used by both LLMs and image synthesis/understanding. The parent posits that while image understanding lags behind LLMs, this may not continue. While your comment points out that image synthesis and understanding has improved over time, I'm not sure I follow the argument that it may soon leapfrog or even catch up with LLMs (i.e. text understanding and synthesis.)
michaelbuckbee · 47m ago
My understanding is that the way that chess.com and other online services detect cheating is by comparing the human-made moves to a "perfect" version of what the chess engine would play.
Which gives credence to your theory that people aren't bringing much to the table.
sulam · 1h ago
“Radiologists do far more than study images. They advise other doctors and surgeons, talk to patients, write reports and analyze medical records. After identifying a suspect cluster of tissue in an organ, they interpret what it might mean for an individual patient with a particular medical history, tapping years of experience.”
Now think about how much of software development is typing out the code vs talking to people, getting a clear definition of the problem, debugging, etc. (I would love an LLM that could debug problems in production — but all they can do is tell me stuff I already know). Then layer on that there are far more ideas for what should be built than you have time to actually build in every organization I’ve ever worked in.
I’m not worried about my job. I’m more worried my coworkers won’t realize what a great tool this is and my company will be left in the dust.
No comments yet
qwertox · 5m ago
TL;DR: “Five years from now, it will be malpractice not to use A.I.,” he said. “But it will be humans and A.I. working together.”
29athrowaway · 1h ago
For an ML model, a sofa with a tiger pattern might be a tiger, if in its training dataset tiger stripes always means tiger.
It does not have common sense.
qgin · 13m ago
For small models, yes. But for the kind of massive multimodal models getting trained these days, the concept of "a pattern on an object" will exist. It doesn't need to have seen a tiger sofa before. But tiger + sofa + patterns on an object is enough to not run from the tiger print.
xnx · 2h ago
Glad to hear that this is one area that AI is conclusively useful.
Still not clear that the already superhuman capabilities of AI won't still fully supplement radiologist interpretive skills with every additional bit of training data that comes in.
qgin · 17m ago
People get tripped up by thinking "there is a subset of what I do that only humans can do and so that means AI will not eliminate my profession entirely and my job is safe".
Let's assume for now that it's true that AI can't do a certain subset of your work. Your profession won't be eliminated from the earth, that's true. But if 80% of your work can be done by AI, 80% of your work will be done by AI. There will still be humans kept around for that remaining 20%, but fewer of them will be needed.
nradov · 8m ago
The demand for radiologists is effectively infinite. Right now the healthcare system is supply constrained. If AI tools reduce the work of reading an image then more imaging studies will be ordered.
Also, many radiologists do interventional procedures directly with patients. We're a long, long way from being able to significantly automate that work.
The example in the article is an in house developed "A.I." to help radiologists assess images. Digging a bit deeper it seems they are using mostly old CNN type architectures with a few million parameters.[1]
I think it still remains to be seen what a 1T+ parameter transformer trained specifically for radiology will do. I think anyone would be confident that a locally run CNN will not hold a candle to it.
[1]https://mayo-radiology-informatics-lab.github.io/MIDeL/index...
This article is surprisingly accurate. I fully expect to finish my career without being 'replaced' by AI.
Happy to debate/answer questions :-)
I imagine, given the training involved, the job involves more than just looking at pictures? This is what I would like to see explained.
The analogy would be the "95% of code is written by AI" stat that gets trotted out, replacing code with image evaluation. Yes AI will write the code but someone has to tell the AI what to write which is the tricky part.
This is a very binary way of thinking about it. More usual is that components of many professions are mechanical and can be automated, while other components are not mechanical and thus harder to automate. Regardless, if some % of the mechanical work goes away, it is unlikely that human workers just work less. Instead, they will work just as much and the overall demand for workers is reduced by %
On the other hand, how much of your confidence in not being replaced stems from AI not being able to do the work, and how much from legal/societal issues (a human needing to be legally responsible for the diagnoses)? Honestly the description in the article of what a radiologist does "Radiologists do far more than study images. They advise other doctors and surgeons, talk to patients, write reports and analyze medical records. After identifying a suspect cluster of tissue in an organ, they interpret what it might mean for an individual patient with a particular medical history, tapping years of experience" doesn't strike me as anything impossible for AI within a few years, now that models are multimodal and they can work with increasing amounts of text (e.g. medical histories).
I dont think this is how market participants may think about it. If costs decrease, some group of radiologists will drop out of the market. We may not "need" less radiologists, but we're signaling we need less of them by not paying them as much as before.
Much like I still "need" a photographer, but short of weddings, I'm not willing to pay as much as before. I may well acquire a photogrpher for a portrait, but it would have to be priced competitively to a selfie.
Like there are times already where I’ve put off or not sought medical care because of the hassle involved.
If I could just waltz into the office and get an appointment and have an issue seen to same day I would probably do it more often.
I'm sure this will all get better with captain brainworms at the helm.
Askl to your question on where my confidence stems from, there are both legal reasons and 'not being able to do the work' reasons.
Legal is easy, the most powerful lobby in most states are trial attorneys. They simply won't allow a situation where liability cannot be attached to medical practice. Somebody is getting sued.
As to what I do day to day, I don't think I'm just matching patterns. I believe what I do takes general intelligence. Therefore, when AI can do my job, it can do everyone else's job as well.
The most powerful lobby in this case is the ABR which carefully constricts coveted residency spots in Radiology to create an artificial scarcity and keep up incomes. It is the opposite of, say, technology, where we have no gatekeeper and supply increases.
The ABR will say that Medicare doesnt fund enough residency spots, but all you need to do is look at an EoB and see that a week of residency billings covers the entire cost of the resident.
About that, I think the AMA is ultimately going to be a victim of its own success. It achieved its goal of creating a shortage of medical professionals and enriching the existing ones. I don't think any of their careers are in danger.
However, long term, I think magic (in the form of sufficiently advanced technology) is going to become cost effective at the prices that the health care market is operating at. First the medical professionals will become wholly dependent on it, then everyone will ask why we need to pay these people eye-watering sums of money to ask the computers questions when we can do that ourselves, for free.
Not as far as I know. Once an automated diagnostic is reasonably accurate, it replaces humans doing the work manually. The same would be true of anything else that can be automatically detected.
No comment on whether radiology is close to that yet, although I don't think a few-million-param neural network would tell us much one way or another.
For context, generative AI music is basically unlistenable. I’ve yet to come across a convincing song, let alone 30 seconds worth of viable material. The AI tools can help musicians in their workflow, but they have no concept of human emotion or expression and it shows. Interpreting a radiology problem is more like an art form than a jigsaw puzzle, otherwise it would’ve been automated long ago (like a simple blood test). Like you note, the legal system in the US prides itself on “accountability” (said tongue in cheek) and AI suffers no consequences.
Just look how well AI worked in the United Healthcare deployment involving medical care and money. Hint: stock is still falling.
This one pops into my head every couple months:
https://youtube.com/watch?v=4gYStWmO1jQ
It's not really my genre, so my judgment is perhaps clouded. Also, I find the dumb lyrics entertaining and they were probably written by a human (though obviously an AI could be prompted to do just as well). I am a fan of unique character in vocals and I love that it pronounces "A-R-A" as "ah-ahr-ah", but the little bridge at 1:40 does nothing for me.
[1] https://www.youtube.com/watch?v=1uW_AUwEv-0
Which is ironic given how much variation in output quality there is based on the judgement of the person using the LLM (work scope, domain, prompt quality, etc.)
Can you please edit out swipes like that from your HN posts? (Prepending "respectfully" doesn't help much.) This is in the site guidelines: https://news.ycombinator.com/newsguidelines.html.
The rest of your comment is just fine of course.
And, I didn't say I would never be replaced. I said I would finish my career, which is approximately 10 more years at this point.
If AI gets to the point where it is truly replacing radiologists and programmers wholesale, it is difficult to tell anyone what to do about it today, because that's essentially on the other side of the singularity from here. Who knows what the answer will be?
(Ironically, the author of that paper, being also a science fiction author, is also responsible for morphing the singularity into "the rapture for nerds" in his own sci-fi writing. But I find the original paper's definition to have more utility in the current world.)
[1]: https://accelerating.org/articles/comingtechsingularity
[0] https://www.siemens-healthineers.com/en-us/radiotherapy/soft...
My personal opinion is that a lot of Medical professionals are simply gatekeeping at this point of time and using legal definitions to keep changing goalposts.
However this is a theme that will keep on repeating in all domains and I do feel that gradual change is better than sudden, disruptive change.
This is a really interesting point that I haven't considered. Namely, regulatory arbitrage is going to yield enormous benefits in the medical AI space. The sheer amount of data needed to train the model requires data centralization the west has no desire to move toward. But if China does crack the nut, it seems like it will necessarily create an upheaval in the west, whether we like it or not.
The other doctors will still be there for you to sue.
Will you be able to source a radioactive source for your x-rays?
DIY radiation therapy would be a whole new level.
Healthcare-grade x-ray tubes to put in your (expensive) x-ray machine are not something you easily can obtain without a license.
Curious -- do you think that is because
1. the technology isnt there, or
2. because it isnt a competitive market (basically, the American Board of Radiologists controls standards of practice and can slow down technologies seen as competitive to human doctors)?
3. or perhaps 1 doesnt happen because outsiders know the market is guarded by the market itsself?
For example, let's say I'm looking at a chest x-ray. There is a pneumonia at the left lung base and I am clever enough to notice it. 'Aha', I think, congratulating myself at making the diagnosis and figuring out why the patient is short of breath.
But, in this example, I stop looking closely at the X-ray after noticing the pneumonia, so I miss a pneumothorax at the right lung apex.
I have made a mistake radiologists call 'satisfaction of search'.
My 'search' for the patient's problem was 'satisfied' by finding the pneumonia, and because I am human and therefore fundamentally flawed, I stopped looking for a second clinically relevant diagnosis.
An AI module that detects a pneumothorax is not prone to this type of error. So it sees something I did not. But it doesn't see something that I can't see. I just didn't look.
https://www.npr.org/sections/health-shots/2013/02/11/1714096...
I'm skeptical to the claim that AI isn't prone to this sort of error, though. AI loves the easy answer.
Ah, now I have a name for it.
When I've chased a bug and fixed a problem I found that would cause the observed problem behavior, but haven't yet proven the behavior is corrected, I'm always careful to specify that "I fixed a problem, but I don't know if I fixed the problem". Seems similar: found and fixed a bug that could explain the issue, but that doesn't mean there's not another one that, independently, would also cause the same observed problem.
https://en.wikipedia.org/wiki/Inattentional_blindness
That is, the models spot pathologies that 99.9999% of rads would spot anyway if not overworked, tired, or in a hurry. But, addressing the implication of your question, the value is actually in spotting a pathology that 99.9999% of rads would never spot. In all my years developing medical imaging startups and software, I've never seen it happen.
I don't expect to see it in my lifetime.
I agree with almost everything you've said here.
Except 'not in my lifetime', because I plan on living for a very long time, and who knows what those computer nerds will come up with eventually ;-)
It's really not a matter of "full replacement or bust".
> Radiologists do far more than study images. They advise other doctors and surgeons, talk to patients, write reports and analyze medical records. After identifying a suspect cluster of tissue in an organ, they interpret what it might mean for an individual patient with a particular medical history, tapping years of experience.
AI will do that more efficiently, and probably already does. "tapping years of experience" is just data in training set.
> A.I. can also automatically identify images showing the highest probability of an abnormal growth, essentially telling the radiologist, “Look here first.” Another program scans images for blood clots in the heart or lungs, even when the medical focus may be elsewhere. > “A.I. is everywhere in our workflow now,” Dr. Baffour said. > “Five years from now, it will be malpractice not to use A.I.,” he said. “But it will be humans and A.I. working together.”
Maybe you'll be able to happily retire because inertia, but overall it looks like elevator operator job.
What's so special about radiology?
However, it's my opinion that my job takes general intelligence, not just pattern matching.
Therefore, when I lose my job to AI, so does everyone else.
On the other hand, a lot of jobs take general intelligence. You’re right about that too.
It’s difficult to guess the specifics of your life, but: maybe you’ve engaged a real estate agent. Some people use no real estate agent. Some have a robo agent. No AI involved. Maybe you have written a will. Some people go online and spend $500 on templates from Trust & Will, others spend $3,000 on a lawyer to fill in the templates for them, some don’t do any of that at all. Even in medicine, you know, a pharma rep has to go and convince someone to add their thing to the guidelines, and you can look back at the time between the study and adoption as, well people were intelligent and there was demand, but doctors were not doing so and so thing due to lack of essentially sales. I mean you don’t have to be generally intelligent to know that flossing is good for you, and yet: so few people floss! That would maybe not put tons of dentists out of business. But people are routinely doing (or not doing) professional services stuff not for any good (or bad) reason at all.
Clearly the thing going on in the professional services economy isn’t about general intelligence - there’s already lots of stuff that is NOT happening long before AI changes the game. It’s all cultural.
If you’ve gotten this far without knowing what I am talking about… listen, who knows what’s going to happen? Clearly a lot of behavior is not for any good reason.
How do you know where the ball is going to go for culture? Personally I think it’s a kind of arrogant position: “I’m a member of the guild, and from my POV, if my profession is replaced, so is everyone else’s.” Arrogance is not an attractive culture, it’s an adversarial one! And you could say inertia, and yet: look who’s running the HHS! There are kids right now, that I know in my real life, who look like you or me, who went to fancy Ivy League school, and they are vaccine skeptical. What about inertia and general intelligence then? So I’ll just say, you know, putting yourself out here on this forum, being all like, “I will AMA, I am the voice,” and then to be so arrogant: you are your own evidence for why maybe it won’t last 10 years.
I jumped into this thread to share my thoughts, and my thoughts alone, because I'm not sure there are a lot of radiologists on HN. I certainly don't speak for all radiologists.
But, I would submit to you, that rapid, radical changes to the practice of medicine are rare, if not impossible.
Been going to RSNA for longer than you've been a radiologist. In all that time, I've never come across an AI that I felt was fit for purpose.
I wholeheartedly agree with you.
Many many reasons for this, and I'm happy to chime in from the tech side of things and fill in any blanks outside your knowledge domain.
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In order to "crack" radiology, the AI companies would need to launch an enormous data collection program involving thousands of hospitals across the world. Every time you got an MRI or X-Ray, you would sign some disclosure form that allowed your images to be anonymously submitted to the central data repository. This kind of project is very easy to describe, but very difficult to execute.
Everyday I see something on a scan yhat I've never seen before. And, possibly, no one has ever seen before. There is tremendous variation in human anatomy and pathology.
So what do I do? I use general intelligence. I talk to the patient. I talk to the referring doctor. I compare with other studies, across modalities and time.
I reason. I synthesize. I think.
So my point is, basically, radiology takes AGI.
Even a tiny hospital with radiology services will produce many thousands of images with accompanying descriptions every year. And you are allowed to anonymize and do research on these things in many places as neither image nor accompanying description is a personal identifier.
So this is yet another Hinton-ish prediction, any time soon radiologist are going dodo. This time LLMs will crack the nut that image recognition have failed at for 20 years.
Where LLMs have succeeded is in doing hot takes that miss the mark, they should be really good at cornering the "prematurely predicting demise of radiologist"-market
Let's say a major healthcare leak occurred, involving millions of images and associated doctor notes, diagnostics, etc... would this help advance the field or is it some algorithmic issue?
Wonder what other forecasts of doom he is wrong about :|.
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Do you have any links to research or work being done on computer vision that leads you to this conclusion? Would love to check it out!
The most recent of which you mentioned, Transformers, is used by both LLMs and image synthesis/understanding. The parent posits that while image understanding lags behind LLMs, this may not continue. While your comment points out that image synthesis and understanding has improved over time, I'm not sure I follow the argument that it may soon leapfrog or even catch up with LLMs (i.e. text understanding and synthesis.)
Which gives credence to your theory that people aren't bringing much to the table.
Now think about how much of software development is typing out the code vs talking to people, getting a clear definition of the problem, debugging, etc. (I would love an LLM that could debug problems in production — but all they can do is tell me stuff I already know). Then layer on that there are far more ideas for what should be built than you have time to actually build in every organization I’ve ever worked in.
I’m not worried about my job. I’m more worried my coworkers won’t realize what a great tool this is and my company will be left in the dust.
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It does not have common sense.
Still not clear that the already superhuman capabilities of AI won't still fully supplement radiologist interpretive skills with every additional bit of training data that comes in.
Let's assume for now that it's true that AI can't do a certain subset of your work. Your profession won't be eliminated from the earth, that's true. But if 80% of your work can be done by AI, 80% of your work will be done by AI. There will still be humans kept around for that remaining 20%, but fewer of them will be needed.
Also, many radiologists do interventional procedures directly with patients. We're a long, long way from being able to significantly automate that work.