321–330 of 368 posts
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As they should. If you hear hooves, think horses not unicorns.
If you google around there's tons of stories of people with legitimate novel illnesses that are ignored or misdiagnosed for years.
I am highly unimpressed by this piece. It reads as if its whole purpose is to grab headlines rather than conduct serious scientific inquiry into the current state -- and limitations -- of these AI methods. 1. Which version of GPT did the author use? There's a huge difference. (The article says "the current version".) 2. How did he choose the subject cohort? (The author doesn't seem to even know how many subjects ther…
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"Seeing the patient" is an important step towards "patient getting better". > have not had their problems validated and have been to many doctors and seen no results or poor results, Also, being validated or not is not going to change with AI as you yourself state that seeing actual physical doctors is not helping in the cases you allude to. I agree that having access to professionals that care about their profession…
> Who thought it was a good idea to have a fixed amount of medical students? A major limiter on the amount of trained medical doctors is not to do with someone "deciding" to have an artificially scarce number of medical students. Two important things come immediately to mind: 1) Medical schools rely on clerkships and preceptors to deliver actual clinical experience critical for learning. These cannot be created out o…
I don't understand why you need to walk around a hospital (Meta/Google/etc) to be a GP. Some leveling would be appropriate (IMO - which is shit/ignorant). Future surgeons need to walk different paths than GPs.
I get that experience is hard to come by, but I don't really feel we are working really, really hard on solving that problem.
Again I am ignorant, but I am also not naive. I know money and status factors greatly into all this.
As a developer, i'm pretty interested in static and dynamic code analysis as a way to easily find bugs, and it does do this pretty well. If developers use it as a tool to use as a reason to walk through code and examine it yourself, it is really quite powerful. It seems invariably, however, that people start trusting what the analysis tool says, and don't question whether the recommendations are correct or worth it.
It's a powerful cognitive effect that would be interesting to study, that probably happens with all kinds of tech. Some are more dangerous than others.
I am highly unimpressed by this piece. It reads as if its whole purpose is to grab headlines rather than conduct serious scientific inquiry into the current state -- and limitations -- of these AI methods. 1. Which version of GPT did the author use? There's a huge difference. (The article says "the current version".) 2. How did he choose the subject cohort? (The author doesn't seem to even know how many subjects ther…
An IRB for deidentified HPI? Got it…
I think this level oversight would be very appropriate here, given how the author doesn't even seem to have a good handle on how many patient case histories he's given to the chatbot.
Being a scifi geek and AI geek and neuroscience geek for pretty much the past 40 years, I've read countless predictions and scenarios and stories about society's response as "true" AI begins to emerge. So watching it play out for real is creating this bizarre sense of deja vu combined with fascination and frustration and also some anxiety. This article and the comments in this thread are right up that alley. I mean,…
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> ChatGPT just doesn't do anything on its own and will never follow through with anything. Yeah, I should be clear: the specific context in which I often see junior developer quality performance is when I'm essentially "pair programming" with it. I can say, "Write a program that does X. No, there's a closed-form solution for that, so we shouldn't write it recursively. OK, now write some tests similar to the following…
Yes, I see what you mean. But just like you're being less productive when you try to instruct someone else on how to do things, if you follow that path with ChatGPT you'll likely be less productive too. I think ChatGPT adds more value when you ask things you don't quite know or figured out yet. Sometimes it hallucinates, which you can usually figure out quickly, but sometimes it does give good insights which would ta…
No existing AI system seems to have achieved personhood in a sense that would incline me to refer to it as "they." And when asked, GPT 4 informs me that "as an AI model I have no preferences" (of course), but it suggests that "it" would be appropriate.
Do you have an argument why using "it" to refer to a current-generation AI persona is inappropriate? If so, I would be genuinely interested to hear it!
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What I didn't predict is so many AI boosters being so miffed at regular folks pointing out the obvious: a half-working system may be tremendously exciting to AI enthusiasts, but it's not that useful to society. Recently we've had all these people complaining of moving goalposts, when in fact most people never had goalposts for AI in the first place, and certainly never had goalposts that remotely resembled those that…
People pushing the curve get to the middle of the sigmoid and want to believe it's gonna be all vertical now. People observing from the outside heavily discount the hype because they know limits will be reached soon. It happens every time.
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I suspect an ER doctor who misdiagnosed patients 50% of the time would not be an ER doctor for very long. Also consider that, in this case, the 50% the AI got right was defined such somewhat generously. For each patient, the AI presented several possible diagnoses, only one of which was correct. If the AI were making all the decisions, would the AI also decide to treat the correct ailment in all those cases? In an em…
But it's also a ridiculous assessment. How much training material for ER doctors was in the training set? I wonder what my rate would be (having never done a single course in medicine)... It should be totally unsurprising that it produced bad results. That it got as much right is an indication there's a good chance you can do reasonably well by training a model with a lot of actual case studies.
Being a scifi geek and AI geek and neuroscience geek for pretty much the past 40 years, I've read countless predictions and scenarios and stories about society's response as "true" AI begins to emerge. So watching it play out for real is creating this bizarre sense of deja vu combined with fascination and frustration and also some anxiety. This article and the comments in this thread are right up that alley. I mean,…
What I didn't predict is so many AI boosters being so miffed at regular folks pointing out the obvious: a half-working system may be tremendously exciting to AI enthusiasts, but it's not that useful to society. Recently we've had all these people complaining of moving goalposts, when in fact most people never had goalposts for AI in the first place, and certainly never had goalposts that remotely resembled those that…
People will use and fund AI tools that have usefulness to them.
AI boosters love to see the capabilities because it unlocks a whole new verdant valley in the continent of useful ideas, but until a street is laid down and a general store is available it remains the domain of early adopters.
LLMs are genuinely impressive. They aren't yet AGI, but they are fantastic tools. More exciting to me as a practitioner is the Segment Anything foundational Model (SAM) since I can put that into immediate use for computer vision in a variety of domains. LLMs still require some baking for broad usefulness (though there are many places they are already useful, its not quite broad enough).
When folks use AI focused on augmenting capabilities rather than replacing people, you get a great return. Until AGI is clear (and we'll know, the AI will tell us without being prompted I reckon), let's treat AI as an exoskeleton rather than a new species.