Number 2 Most Resistant Job To AI

Started by Groove
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You don't follow this space like I do and that's totally fine. You're talking about Moravec's paradox. Easy for humans, difficult for machines. AI operating in an unpredictable physical world with concerns for safety, regulatory approval, massive liability exposure, etc.. Radiology diagnostics and TLO are the complete opposite. Abundant training data. Verifiable outcomes. No real time physical risk during inference. Cloud scale compute. FSD is the absolute worst comparison. This whole principle is why robotics is nowhere near advancing as fast as AI. The cognitive/agentic areas are where these models thrive and is where the absolute greatest advancements will be observed first.

I leave you with the classic Will Smith eating spaghetti evolution within 3 years. But we don't have anything to worry about because these models move so slow, right?

Bruh, thats exactly what radiology is. Artifacts, poor positioning, different machines having different imaging appearance, the vast variety of anatomic variants in nature, concerns for safety, regulatory approval, massive liability exposure, etc etc. As much as I’m not in the AI development sphere, you’re not in the radiology sphere. Like I said, I’m planning to incorporate AI as much as I can, but the evidence for radiology just isn’t there at this point.

It’s likewise exhausting hearing AI doomers who have no understanding of what radiology truly entails proclaim that AI will fundamentally change the practice of radiology in the short to medium term, to which I have to point at all the prior people that have gotten it wrong for the past few decades and have them say “but it’s different this time, for real!” It’s all good though, you’re in good company with Geoffrey Hinton and the like.
 
Bruh, thats exactly what radiology is. Artifacts, poor positioning, different machines having different imaging appearance, the vast variety of anatomic variants in nature, concerns for safety, regulatory approval, massive liability exposure, etc etc. As much as I’m not in the AI development sphere, you’re not in the radiology sphere. Like I said, I’m planning to incorporate AI as much as I can, but the evidence for radiology just isn’t there at this point.

It’s likewise exhausting hearing AI doomers who have no understanding of what radiology truly entails proclaim that AI will fundamentally change the practice of radiology in the short to medium term, to which I have to point at all the prior people that have gotten it wrong for the past few decades and have them say “but it’s different this time, for real!” It’s all good though, you’re in good company with Geoffrey Hinton and the like.
Good luck my friend. The next few years will be a wild and exciting time for both of us. God speed!

PS. I adore Geoffrey Hinton!
 
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I truly hope the mass AI skepticism and distrust continues for at least a few more years so all of us early adopters can continue to leap frog everyone else by adopting and leveraging it early. I feel like that guy from inception every time I try to convince people.


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I use multiple LLMs daily. I’m using it to accelerate my learning about countless things. It’s helped me immensely already. But I feel like my imagination (or lack thereof) is holding me back from truly using it explosively. In your opinion, what’s the best way to take the leap from using AI to search, learn and gather information, to truly innovating?
 
Blame over-utilization and lack of understanding regarding the role of imaging.
These days getting a CTA for PE seems to be protective for the pt from actually having one.
AI for rads as of now is pretty subpar.
God forbid you miss anything in my lawsuit happy state. Not worth a suit or patient complaint to the board.
 
I use multiple LLMs daily. I’m using it to accelerate my learning about countless things. It’s helped me immensely already. But I feel like my imagination (or lack thereof) is holding me back from truly using it explosively. In your opinion, what’s the best way to take the leap from using AI to search, learn and gather information, to truly innovating?
You're on the right path. Remember med school? It was an enormous amount of high quality information overload that your brain had never had to process before and you learned that you could process, retain, analyze and memorize MUCH more information than you had been used to in college. The whole neuroplasticity thing. AI is no different. The amount of "high quality" information reminds me of med school in a way. No longer am I toiling for hours trying to dredge up information in a data retrieval method over days or weeks to assimilate information into a format that I can process and analyze in a high quality manner over a fraction of the time it took me to acquire, produce and format the data. It's immediate. Most days that I spend with AI, it's so much overwhelming high quality information that for the first time in years....I'M the bottleneck. Learning prompt engineering greatly enhances the quality of output.

I think innovation potential will change over the next couple of years. Right now...coding is an extremely strong point in many models, especially Anthropic. The models are extremely good in that domain as well as learning, idea generation, analysis, etc.. I think if you've got any element of that entrepreneurship bug then it's extremely beneficial brainstorming ideas with AI and then obtaining guidance for the easiest ways to manifest that idea into reality. I think coders have an edge right now since there's so much programming potential with Claude. It's difficult for me to come at it from a non developer perspective since I was programming since the age of 12. That being said, I've seen more and more very cool projects in vibe coding communities from people with zero programming experience. You might think of joining some of those. Vibe coding is slang these days for application development from a developer/nondeveloper using natural language prompting and you essentially let the AI build the application and aren't directly involved in syntax. You might consider joining r/ClaudeAI and r/ClaudeCode to get some ideas. You'd be pretty amazed at what people are creating in there.

Once you get used to creating tools and applications to benefit your life then you can lean into automation using n8n and things like open claw, etc.. Or just wait for true agentic AI which will probably be here before the end of the year or sometime next year. At that point, the bottleneck will most definitely be you because you'll have to come up with ideas, projects, research, building, whatever you have on your plate and hand it off to multiple agents to go work on that task and they'll be working together, forming teams and touching back with you to present information or obtain guidance with whatever you've tasked them with, etc.. Very cool times.
 
Also, get used to leveraging MCP servers in Claude. You greatly enhance the output based on how many tools you can connect, etc.. It's like asking it to build something with its hands versus giving it access to a Lowe's or HomeDepot.

Automate your agents as much as possible once you identify those high yield work flows. Like, I'm waking up today and it has already scoured the internet and news sources for any portfolio related news, has analyzed options positioning, retrieved any geo-political news, AI related news, gotten my local weather, checked my calendar and email and has presented me with a 7 page pre-market report like a good little agent. It's the first thing I read in the morning. It's already suggesting ideas for things to work on today.
 
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Also, get used to leveraging MCP servers in Claude. You greatly enhance the output based on how many tools you can connect, etc.. It's like asking it to build something with its hands versus giving it access to a Lowe's or HomeDepot.

Automate your agents as much as possible once you identify those high yield work flows. Like, I'm waking up today and it has already scoured the internet and news sources for any portfolio related news, has analyzed options positioning, retrieved any geo-political news, AI related news, gotten my local weather, checked my calendar and email and has presented me with a 7 page pre-market report like a good little agent. It's the first thing I read in the morning. It's already suggesting ideas for things to work on today.

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You're on the right path. Remember med school? It was an enormous amount of high quality information overload that your brain had never had to process before and you learned that you could process, retain, analyze and memorize MUCH more information than you had been used to in college. The whole neuroplasticity thing. AI is no different. The amount of "high quality" information reminds me of med school in a way. No longer am I toiling for hours trying to dredge up information in a data retrieval method over days or weeks to assimilate information into a format that I can process and analyze in a high quality manner over a fraction of the time it took me to acquire, produce and format the data. It's immediate. Most days that I spend with AI, it's so much overwhelming high quality information that for the first time in years....I'M the bottleneck. Learning prompt engineering greatly enhances the quality of output.

I think innovation potential will change over the next couple of years. Right now...coding is an extremely strong point in many models, especially Anthropic. The models are extremely good in that domain as well as learning, idea generation, analysis, etc.. I think if you've got any element of that entrepreneurship bug then it's extremely beneficial brainstorming ideas with AI and then obtaining guidance for the easiest ways to manifest that idea into reality. I think coders have an edge right now since there's so much programming potential with Claude. It's difficult for me to come at it from a non developer perspective since I was programming since the age of 12. That being said, I've seen more and more very cool projects in vibe coding communities from people with zero programming experience. You might think of joining some of those. Vibe coding is slang these days for application development from a developer/nondeveloper using natural language prompting and you essentially let the AI build the application and aren't directly involved in syntax. You might consider joining r/ClaudeAI and r/ClaudeCode to get some ideas. You'd be pretty amazed at what people are creating in there.

Once you get used to creating tools and applications to benefit your life then you can lean into automation using n8n and things like open claw, etc.. Or just wait for true agentic AI which will probably be here before the end of the year or sometime next year. At that point, the bottleneck will most definitely be you because you'll have to come up with ideas, projects, research, building, whatever you have on your plate and hand it off to multiple agents to go work on that task and they'll be working together, forming teams and touching back with you to present information or obtain guidance with whatever you've tasked them with, etc.. Very cool times.
I recently tried to vibe code an ap that would access my macbook microphone, transcribe patient interactions into our EMR, access and analyze labs, imaging and old records and formulate potential diagnoses, treatment plan and code the encounter for me. Claude told me it would be a HIPAA violation to route this through it's servers and that Athena Health would require me to get their permission. I stopped there, considering those roadblocks combined with the fact EMR companies have their own versions in the process. I just figured it'd be a cool project to do on my own, but decided it's probably not worth it with those two regulatory roadblocks.

I haven't tried the open claw thing yet, since a programmer friend of mine warned me to be careful with these agents mucking things up if you give them too much access.

Just joined r/Claude and r/Claude AI for ideas.

Thanks, man.
 
You're on the right path. Remember med school? It was an enormous amount of high quality information overload that your brain had never had to process before and you learned that you could process, retain, analyze and memorize MUCH more information than you had been used to in college. The whole neuroplasticity thing. AI is no different. The amount of "high quality" information reminds me of med school in a way. No longer am I toiling for hours trying to dredge up information in a data retrieval method over days or weeks to assimilate information into a format that I can process and analyze in a high quality manner over a fraction of the time it took me to acquire, produce and format the data. It's immediate. Most days that I spend with AI, it's so much overwhelming high quality information that for the first time in years....I'M the bottleneck. Learning prompt engineering greatly enhances the quality of output.

I think innovation potential will change over the next couple of years. Right now...coding is an extremely strong point in many models, especially Anthropic. The models are extremely good in that domain as well as learning, idea generation, analysis, etc.. I think if you've got any element of that entrepreneurship bug then it's extremely beneficial brainstorming ideas with AI and then obtaining guidance for the easiest ways to manifest that idea into reality. I think coders have an edge right now since there's so much programming potential with Claude. It's difficult for me to come at it from a non developer perspective since I was programming since the age of 12. That being said, I've seen more and more very cool projects in vibe coding communities from people with zero programming experience. You might think of joining some of those. Vibe coding is slang these days for application development from a developer/nondeveloper using natural language prompting and you essentially let the AI build the application and aren't directly involved in syntax. You might consider joining r/ClaudeAI and r/ClaudeCode to get some ideas. You'd be pretty amazed at what people are creating in there.

Once you get used to creating tools and applications to benefit your life then you can lean into automation using n8n and things like open claw, etc.. Or just wait for true agentic AI which will probably be here before the end of the year or sometime next year. At that point, the bottleneck will most definitely be you because you'll have to come up with ideas, projects, research, building, whatever you have on your plate and hand it off to multiple agents to go work on that task and they'll be working together, forming teams and touching back with you to present information or obtain guidance with whatever you've tasked them with, etc.. Very cool times.

Groove, you're finally becoming a little self-aware about this regarding your massive head start as a result of your CS/coding/programming background.

I'm kind of like @Birdstrike in that I use AI everyday, it's increased my ability to learn, find information, and wrestle with ideas that I have, but despite being VERY up to date with what's happening in the field, I simply haven't been able to create any useful tools in my daily life.

I mentioned my failed attempt at creating a personalized property management app for my rentals. In terms of news and AI updates, I already have my various info streams for that, same with my stocks and BTC. Because I'm not trading in and out of names it's actually helpful to NOT have updates on a daily basis, in fact I only want to look at the chart every week or so, at most (except for BTC since that's an obsession).

AI can't yet make a perfect pour-over, though it has helped me dial in my game in terms of knowledge, but that took all of 5 minutes with AI months ago.

So yea, while I wouldn't call myself an early adopter by any means, all of this proves to me that 99% of people won't accept/care/do anything about this AI wave until we literally have humanoids showing up to interviews in suits for jobs.

Yes the tech/AGI/ASI will be there to "replace" radiologists in 2 years or whatever (I am as accelerationist as you when it comes to the core abilities), but where I think you get it wrong is that there are so many human obstacles, and factors, and friction that will keep the roll-out fairly slow and unnoticeable for much longer than you think.

Just take a look at healthcare now. We are still using fax machines. Enough said.
 
So yea, while I wouldn't call myself an early adopter by any means, all of this proves to me that 99% of people won't accept/care/do anything about this AI wave until we literally have humanoids showing up to interviews in suits for jobs.

Yes the tech/AGI/ASI will be there to "replace" radiologists in 2 years or whatever (I am as accelerationist as you when it comes to the core abilities), but where I think you get it wrong is that there are so many human obstacles, and factors, and friction that will keep the roll-out fairly slow and unnoticeable for much longer than you think.
I really hope you're right to be honest. That gives all of us more time to use it as our own secret sauce. I suspect though that the sheer economic pressure will ultimately override and ram through all the friction from antiquated systems and industries. That economic whip is cracking in software, legal, finance, etc.. and I suspect in the end...healthcare will prove to be no different. After all, money drives everything. We'll find out soon enough that's for sure.

Oh, and I think some of you are going to find agentic AI way more useful than what we have right now for all the reasons you all have posted.
 
I really hope you're right to be honest. That gives all of us more time to use it as our own secret sauce. I suspect though that the sheer economic pressure will ultimately override and ram through all the friction from antiquated systems and industries. That economic whip is cracking in software, legal, finance, etc.. and I suspect in the end...healthcare will prove to be no different. After all, money drives everything. We'll find out soon enough that's for sure.

Oh, and I think some of you are going to find agentic AI way more useful than what we have right now for all the reasons you all have posted.

You're not wrong, but that economic whip has always been there. For every industry, including healthcare. This is capitalism. Nothing has changed. It's been that way since the inception of our modern society.

Regarding the agentic AI being useful. I'm taking the Naval Ravikant approach to this and generally DGAFing and only interacting with AI as I interact with another human. There's no point in me learning every new Q6month iteration of agentic development, or how to prompt engineer for this newest model, Look at how fast things like n8n and its predecessors are already being made obsolete, I already forgot the name of that one everybody was using after it, and now no longer use because of openclaw.

Knowledge along all those points will eventually drop to zero. I like Graham Weaver's take on the layers. The physical layer is worth investing in, as is the top. The rest in the middle is either full moat (frontier models) or going to zero (app layer).
 
You don't follow this space like I do and that's totally fine. You're talking about Moravec's paradox. Easy for humans, difficult for machines. AI operating in an unpredictable physical world with concerns for safety, regulatory approval, massive liability exposure, etc.. Radiology diagnostics and TLO are the complete opposite. Abundant training data. Verifiable outcomes. No real time physical risk during inference. Cloud scale compute. FSD is the absolute worst comparison. This whole principle is why robotics is nowhere near advancing as fast as AI. The cognitive/agentic areas are where these models thrive and is where the absolute greatest advancements will be observed first.

I leave you with the classic Will Smith eating spaghetti evolution within 3 years. But we don't have anything to worry about because these models move so slow, right?

Radiology AI also has concerns for safety, regulatory approval, and massive liability exposure. FSD models also have abundant training data. If you take away the unpredictable physical environment, they are actually pretty good analogies.
 
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Like I'm so tired of these posts. I'm tired of replying to them to be honest. Alpha Fold anyone? You used x-ray crystallography and cryo-EM over 60 years to produce only 200K proteins and AI+deep machine learning enabled us to produce over 200+ million in a single year. How long would that have taken us otherwise? That's miraculous. AND that's a system that's a few years old at this point! You guys need to stop with these statements. It's ridiculous in 2026.
I think he’s saying what we have for AI in radiology is trash. That’s a true statement. If you used the AI applications that get forced on radiologists, which are frequently inaccurate and constantly give false positives, you’d get it.
 
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So, I want you rads guys to take a look at that chart. It may mean nothing to you and that's fine but that's the "The Last Ones" security AI test build by the UK AI Security Institute to test AI cyber capabilities. It's a 32 step simulated corporate network red-team penetration testing attack chain. It takes the absolute best of the best humans in the world about 20 hours of focused work to complete it. GPT-4o could only get 1.7 steps. Opus 4.6 got around 10 steps. Claude Mythos preview is the first model to ever complete it. Look at those massive generational leaps in capability. We're talking mid-20025 models to one year later. If you guys think these models can't and won't overtake your ability to safely, efficiently and accurately diagnose radiology imaging, you are crazy. And it won't take 15 years either. That's just the scary reality of a medical specialty that has little to no patient interaction. It's pure cognitive work. (Diagnostics) ANY job centered about human cognitive work WILL absolutely be overtaken by AI. It's inevitable. Does that mean you'll be without a job in a few years? Of course not. What it means is that the AI that you dismiss as (AI slop) will become good enough that it starts to impress you and then impressed you even more and then you will find yourself relying on it more and more. That's the key to keeping your jobs. Leveraging it to make you MORE productive. Who knows, you might find that you finish the day feeling less stressed than you do now because you could get so much done with AI and the reads have lower medicolegal risk because it's getting checked over and over by the systems QA.

The absolute worst thing any of us can do is dismiss the technology which is the human thing to do when we all feel like our job is threatened. (Nobody can do it as well as ME, etc..) What's important is for all of us to jump on board leveraging this technology. I think what most of us will find is that we are probably as physicians one of the last human workers to be replaced by AI because as some of you have said, the human interaction is important. Discussing the read with the surgeon who's planning a surgical approach. The ER doc that wants to talk with you about the clinical presentation and ask you a few questions about the read. That kind of stuff can't readily be replaced by AI (Yet) and I think that's going to be true for quite a long time so I don't think any of us need to worry about that.

If you DO get replaced, it's more than likely going to be a new radiology grad, nowhere near your level of experience or expertise that jumped on the AI bandwagon early and can knock out reports in half the time that you can leading to them being overwhelmingly productive and your employer deciding to let you go and keep the young guy.

As for the rest of the discussion in here, I hope none of the rad guys see us as enemies because I was honestly a bit surprised to see some of the snarky comments in here. There's no way any of us could do our jobs without you. 100% of management and disposition depends on DIAGNOSTICs and you guys are the gatekeepers. If you feel overwhelmed with the amount of reads, don't project that onto us please. We are slammed each and every day and forced to see more and more people in les and less time in a growing medicolegal environment and diagnostic imaging is just part of that beast. You guys are being forced to read more and more reads when you probably need MORE people and that's just admin screwing both of us but we truly are not enemies and I hope we can always remember that.
There’s a hard reality here which is that if AI is truly effective at image interpretation, it will result in massive job loss among radiologists. It may not replace them entirely, but it would cause massive efficiency gains if highly accurate - resulting in one rad doing the current work of 10. Therefore every group can cut their workforce down by 90%. The $/rvu would hit the bottom and people would be scrambling to retrain.

Realistically there isn’t much to “leveraging the technology” in the field of radiology. An AI algorithm will interpret a scan and spit out a pre drafted report - that’s already happening. It’s just that the draft is gobbledeygook. I don’t think there will even be an old/young difference. If an effective AI is produced, more or less any radiologist will be able to use it. I just don’t see this future of “radiologists who use AI will replace those who dont”. It just doesn’t seem likely that some obstinate radiologist is willing to be fired because they refuse to use a software that literally does their work for them.

As for the meat of the discussion, no I don’t know what that chart means, but I do know that as the other poster mentioned, there’s a lot of internal articles on AIs supposed exponential capability growth but it doesn’t come through in real world use cases. So, I’m not worried. I’ve been hearing this from people on the AI side for decades, as I’ve mentioned. There’s always some new model or learning software that suggests “it’s going to really take off now”. I’ll believe it when I see it. There are so many AI products that show utility “better than radiologists” in the training data set, usually highly curated data sets of optimal images, but when deployed in the real world it completely falls flat.
 
A smart radiologist would already be using AI to over-read his/her studies. I see enough misses by human radiologist that it's likely AI would pick up some findings and alert the radiologist.
 
There’s a hard reality here which is that if AI is truly effective at image interpretation, it will result in massive job loss among radiologists. It may not replace them entirely, but it would cause massive efficiency gains if highly accurate - resulting in one rad doing the current work of 10. Therefore every group can cut their workforce down by 90%. The $/rvu would hit the bottom and people would be scrambling to retrain.

Realistically there isn’t much to “leveraging the technology” in the field of radiology. An AI algorithm will interpret a scan and spit out a pre drafted report - that’s already happening. It’s just that the draft is gobbledeygook. I don’t think there will even be an old/young difference. If an effective AI is produced, more or less any radiologist will be able to use it. I just don’t see this future of “radiologists who use AI will replace those who dont”. It just doesn’t seem likely that some obstinate radiologist is willing to be fired because they refuse to use a software that literally does their work for them.

As for the meat of the discussion, no I don’t know what that chart means, but I do know that as the other poster mentioned, there’s a lot of internal articles on AIs supposed exponential capability growth but it doesn’t come through in real world use cases. So, I’m not worried. I’ve been hearing this from people on the AI side for decades, as I’ve mentioned. There’s always some new model or learning software that suggests “it’s going to really take off now”. I’ll believe it when I see it. There are so many AI products that show utility “better than radiologists” in the training data set, usually highly curated data sets of optimal images, but when deployed in the real world it completely falls flat.

Did you read the MASAI study from Lancet 2026? 12% interval reduction in cancers on the AI supported arm. 44.3% reduction in radiologist workload. Lancet confirmed the AI supported arm demonstrated cancer detection accuracy beyond the 2 radiologist standard all while reducing radiologist work load. Isn't that exactly the type of evidence you're asking to see? What's curated about that? It's using real world data.

You do realize that radiology accounts for around 75% of all FDA cleared AI medical devices now right? That's not pilots or lab toys, that's real deployments. You don't have vendors such as GE, Siemens, Philips, Aidoc, etc.. pouring this kind of money into a technology that's going to be "just as good or worse" than humans. There's a reason radiology dominates FDA clearances right now.

Like...think about that MASAI study for a second. One radiologist + AI vs 2 radiologists reading independently. What does that tell the industry? You can cut your radiologist head count in half on screening mammography and get BETTER outcomes. What inferences can we take from that? What's funny is that none of these types of studies that are being used right now were using frontier multimodal models. Even the MASAI models were like 2-3 generations behind current state of the art models. What do you think Mythos would be able to do fine tuned for mammography or other narrow task diagnostic radiology use cases?

Also, I'm not sure what you mean by the whole decades thing. Pre-2017 and even pre-2023 are completely different tech eras. I mean, hey...you take your own chances but if I were you guys I'd be "over preparing" for AI not under preparing. Early adoption productivity gains are real and you and I both know there's huge lag when comparing early adopters to laggards. EMR, dictation, PACS, etc...
 
Radiology AI also has concerns for safety, regulatory approval, and massive liability exposure. FSD models also have abundant training data. If you take away the unpredictable physical environment, they are actually pretty good analogies.
That's like saying chess and combat are similar once you take away the guns, explosions, violence, people dying, unpredictability and life and death. Me and the massive old oak tree in my front yard I just fertilized are pretty similar once you take away the flesh, blood, organs, brain, etc.. I mean, we both stand upright and sway from side to side, right?

FSD has challenges because the edge cases are where the data lacks. That's insufficient data during "uncommon" scenarios. Not the case in medicine or radiology. Finite pathology. Finite anatomy. Finite imaging modalities. You get the picture. Way easier to solve than FSD.
 
There’s a hard reality here which is that if AI is truly effective at image interpretation, it will result in massive job loss among radiologists. It may not replace them entirely, but it would cause massive efficiency gains if highly accurate - resulting in one rad doing the current work of 10. Therefore every group can cut their workforce down by 90%. The $/rvu would hit the bottom and people would be scrambling to retrain.

Realistically there isn’t much to “leveraging the technology” in the field of radiology. An AI algorithm will interpret a scan and spit out a pre drafted report - that’s already happening. It’s just that the draft is gobbledeygook. I don’t think there will even be an old/young difference. If an effective AI is produced, more or less any radiologist will be able to use it. I just don’t see this future of “radiologists who use AI will replace those who dont”. It just doesn’t seem likely that some obstinate radiologist is willing to be fired because they refuse to use a software that literally does their work for them.

As for the meat of the discussion, no I don’t know what that chart means, but I do know that as the other poster mentioned, there’s a lot of internal articles on AIs supposed exponential capability growth but it doesn’t come through in real world use cases. So, I’m not worried. I’ve been hearing this from people on the AI side for decades, as I’ve mentioned. There’s always some new model or learning software that suggests “it’s going to really take off now”. I’ll believe it when I see it. There are so many AI products that show utility “better than radiologists” in the training data set, usually highly curated data sets of optimal images, but when deployed in the real world it completely falls flat.

You'd like this....it's only 6 mins.



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I'm curious @Groove, what do you think of the impact AI will have on cognitive or lightly procedural patient-facing specialties? I can see a world in which NPs/PAs (or a physician making the same salary as an NP/PA) + AI do most of the decision making. Platforms like openevidence can already generate decent assessments and plans for common issues. If this continues to be the case, seems like there will be no need to pay cognitive specialty physicians six figure salaries given our main leverage is our knowledge. As someone just starting residency this July, it feels pretty inevitable and does give me anxiety over whether it will all be worth it in the end. I don't have a good counter argument for why this won't become the norm in the near future unfortunately. I'm going into IM so at least I have options, but every IM subspecialty except GI, IC, and EP (i.e. the most competitive) is going to be facing this problem so that's not much reassurance.
 
PAs/NPs/AI are no where near replacing docs. Even the “good” midlevels I know are trash providers. I think AI would do well replacing them. I’d rather work alongside an AI bot than the idiotic midlevels who can’t even see 1.5/hr low acuity.
 
I'm curious @Groove, what do you think of the impact AI will have on cognitive or lightly procedural patient-facing specialties? I can see a world in which NPs/PAs (or a physician making the same salary as an NP/PA) + AI do most of the decision making. Platforms like openevidence can already generate decent assessments and plans for common issues. If this continues to be the case, seems like there will be no need to pay cognitive specialty physicians six figure salaries given our main leverage is our knowledge. As someone just starting residency this July, it feels pretty inevitable and does give me anxiety over whether it will all be worth it in the end. I don't have a good counter argument for why this won't become the norm in the near future unfortunately. I'm going into IM so at least I have options, but every IM subspecialty except GI, IC, and EP (i.e. the most competitive) is going to be facing this problem so that's not much reassurance.
Healthcare demand is going up (aging pouulation + chronic disease). Even if AI produces productivity per physician, we probably STILL need more docs. That's just reality. Plus, I think salaries between "AI augmented physicians" vs "old school average with no AI" is going to widen in your favor if you learn to leverage the tech early. That's the biggest thing that's going to be a boon to your future productivity.

The job is going to change, no doubt about it. BUT the docs who thrive will the ones who help build the next layer.... clinical AI oversight, quality/safety around the tools, digital health strategies, etc.. Hell, even new "medical models", etc.. IM gives you great ability to pivot into those realms at any point. Leveraging the tech early allows you to aggressively use AI and critically. You will know when to override the model where others won't.

It's going to be a long time before that human layer gets replaced. Even if AI can help your diagnostics and everything else, patients pay for trust and judgement, a human face, a human touch, human concern. AI might thrive in clean, textbook cases but medicine is anything but and you're going to have patients with tons of comorbidties, their own theory about what they are willing to do and what they aren't that doesn't coincide with a pure logic system. There will be ridiculously weird social situations, conflicting priorities. AI currently hallucinates or bull***ts when the data is messy. You'll be able to see through all that. Plus, let's face it...regulators and courts aren't going to hand the keys of the kingdom over to an LLM anytime soon so I think most of your career is safe. Will it look more like something out of Star Wars after that? Maybe....or maybe not. Nobody can tell. However, out of all the careers in the world, I think physicians are the best insulated at the moment. Next to plumbers!

Don't think of AI as a threat as you go through residency. That's the absolute worst thing you can do. Think about it as another type of stethoscope. LEARN to use it and learn to use it well and you'll be well positioned to thrive going forward. You guys that learn to be "AI power users" are going to lead the pack in the future I promise you.
 
Curiously, I've seen very little (or no) talk about the sustainability of AI on this thread.
I get that we're a tech-y bunch - but if these data centers suck all the water up, what are we going to eat?
 
Curiously, I've seen very little (or no) talk about the sustainability of AI on this thread.
I get that we're a tech-y bunch - but if these data centers suck all the water up, what are we going to eat?
That’s one of my biggest complaints.

Why are they building these crazy data center designs that use so much fresh water?

Much less the Grok/xAI monstrosities in Tennessee where they are burning diesel generators.
 
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I'm pretty sure these AI companies could easily foot the bill for solar panels and solar storage batteries to power their AI centers, but they want the same socialist style government tax payor funded handouts that they want to remove from the common person.
 
And now you see the underpinnings of why the upper echelon of the tech bros want most humans gone.

I want most humans gone, too - but for entirely different reasons.

I don't want to live crammed atop one another like in India/Brazil/Wherever.
We can't sustain 8 billion+ people on this planet.