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I'm going to shamelessly steal @Scimitar's post from the Friday Fun thread because I think we need to talk about LLMs in a CW context:
A few months ago OpenAI dropped their API price, from $0.06/1000 tokens for their best model, to $0.02/1000 tokens. This week, the company released their ChatGPT API which uses their "gpt-3.5-turbo" model, apparently the best one yet, for the price of $0.002/1000 tokens. Yes, an order of magnitude cheaper. I don't quite understand the pricing, and OpenAI themselves say: "Because
gpt-3.5-turboperforms at a similar capability totext-davinci-003but at 10% the price per token, we recommendgpt-3.5-turbofor most use cases." In less than a year, the OpenAI models have not only improved, but become 30 times cheaper. What does this mean?https://old.reddit.com/r/singularity/comments/11fn0td/the_implications_of_chatgpts_api_cost/
...or about $0.13 per hour. Yes technically it overlooks the fact that OpenAI charge for both input and output tokens, but this is still cheap and the line is trending downwards.
Full time minimum wage is ~$20k/year. GPT-3.5-turbo is 100x cheaper and vastly outperforms the average minimum wage worker at certain tasks. I dunno, this just feels crazy. And no, I wont apologize for AI posting. It is simply the most interesting thing happening right now.
I strongly agree with @Scimitar, this is the most interesting thing happening right now. If you haven't been following AI/LLM progress the last month, it has been blazingly fast. I've spent a lot of time in AI doomer circles so I have had a layer of cynicism around people talking about the Singularity, but I'll be damned if I'm not started to feel a bit uncomfortable that they may have been right.
The CW implications seem endless - low skill jobs will be automated, but which tribe first? Will HR admins who spend all day writing two emails be the first to go? Fast food cashiers who are already on their way out through self ordering consoles?
Which jobs will be the last to go? The last-mile problem seems pretty bad for legal and medical professionals (i.e. if an LLM makes up an answer it could be very bad) but theoretically we could use them to generate copy or ideas then go through a final check by a professional.
Outside of employment, what will this do to human relations? I've already seen some (admittedly highly autistic) people online saying that talking to ChatGPT is more satisfying than talking to humans. Will the NEET apocalypse turn into overdrive? Will the next generation even interact with other humans, or will people become individualized entirely and surround themselves with digital avatars?
Perhaps I'm being a bit too optimistic on the acceleration, but I can't help but feel that we are truly on the cusp of a massive realignment of technology and society. What are your thoughts on AI?
I predict absolutely nothing will happen to medical professionals because of AI. We've already had "AIs" (aka expert systems) that perform as well or better as trained medical professionals in diagnosis for decades, yet they're used approximately nowhere.
They don’t perform as well. Someone has to actually examine the patient, observe his state and put the findings into the expert system. The expert system cannot do that. What it can do, on the other hand, is relatively trivial for the doctor who does the examination.
I find that most people who think doctors (well, medical professionals) are easy to replace have a pretty limited understanding of what actually happens in healthcare. Sure if you occasionally have an ear infection or a sprained muscle that seems pretty easy and simple and replaceable. Even something like anesthesia, what this guy is just pushing some buttons right?
Well no.
You go into the hospital with trouble breathing, your doctor comes to see you. Your heart rate is elevated. Do you have a growing infection? Are you nervous talking to the doctor? Were you trying to work out because you have a date next week? Is this a side effect from the breathing medication we gave you? Were you just fucking your girlfriend? One of these requires immediate start of antibiotics, and patients can have more than one of them happening at the same time (and in my experience, have).
The algo is just going to start abx which is not harmless by any means. Decision support exists but it's uniformly terrible because it can't take into account the gestalt and patients usually have multiple things going wrong (both inpatient and outpatient). Young and healthy people with a single sick complaint is approximately zero percent of the work in healthcare but also 100% of what is replaceable with decisions support right now.
In a U.S. ED we have multiple layers of triage and knowledge running from triage nurses, to mid level providers, to ED physicians to IP docs and consultants. We know that the lower levels on this scale are inferior (and that includes ED physicians) because we observe it on a daily basis.
Current decision support tools can't even read an EKG, the amount of development required to deal with the messy complexity of people (including the fact that people will misinform you both intentionally and unintentionally) is immense and god help us if the people like Cim who think we aren't doing anything useful or important get their way.
Thanks, this sounds more like how I was thinking about it. Like, maybe the algorithm can, or at least could, make okay decisions if it had all of the information. But then isn't actually gathering all of the information and getting it into a form that could be entered or written down somewhere like 80% of what doctors do anyways? I'm not sure if it matters how good the algorithm is if any professional could have already made the best practical decision before they even would have been able to enter all of the information into some system anyways.
So we have a ton of top of the line decision support tools right now, (including things like auto-read for EKGs, suggestions to put in antibiotic if the computer thinks someone is septic, etc.) the problem is that they suck and are intrusive and annoying. This is important, not only do they need to be more right but they also need to be consistently right - people are trained just to ignore them and if you go from being helpful from 5% of the time to 30% of the time they'll still be functionally useless. If we get to a 70% range situation people will ignore them out of habit and ingrained mistrust.
That problem aside...why is this shit so hard?
It's not because medicine is complicated (it is, but that's not the problem*), LLM are perfect for digging through a bunch of data and such. It's because people are complicated. People come in with a severe illness and complain about something else, ignore a diagnostically critical symptom, report pain in the "wrong" quadrant for the pathology (happens all the damn time).
The decision support tool needs to handle this ambiguity gracefully, have some mechanism for sussing out the correct shit from the patient, and have graceful way of handling the editorializing of whoever is recording and entering the data (and ideally in a timely fashion as you mention).
And then you have super significant but more arcane layers to the problem. Okay my patient has a kidney issue and a heart issue. My decision support tool can help and send me the most updated guidelines. Well where are we pulling from? Cards or Neph? One is shouting Blue and the other is shouting Yellow and depending on which Ivory Tower Institution you pull from the shades of those colors are going to be wildly different.
Research in medicine is difficult and fraught and ethically complicated and we don't have enough high quality recommendations to load this stuff with.
In Europe they manage appendicitis mostly medically, in the U.S. we operate. You ask a surgeon here why the difference and they'll probably say it's because we are fatter. Is that right? Fuck if I know, but we can't agree on the most simple of management.
*I have no idea why the EKG reads are bad, that's pretty damn simple and doesn't bode well for getting anything more complicated done.
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