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The industry calls AI even the dumbest linear system, I don't think it is right to blame non industry people if they don't use the right words after that.

I think the effort to keep the definition of AI narrow is not useful (and futile, besides). By both common usage and even most formal definitions, it's an umbrella term, and sometimes refers to a specific thing under that umbrella that we already have other words for if we would like to be more specific (ML, deep learning, LLM, GPT, genAI, neural net, etc).

> If it sucks and hallucinates information it's not going to go live anywhere.

It hallucinates and it's live in many places. My doctor uses it.

AFAICT the hallucination rate is fairly low. It's transcription and summarization which has a lower hallucination rate than when it's asked for an answer.

It's massively better than the alternative. Taking the time to write down proper notes is the difference between 4 patients per hour and 6 and a commensurate drop in income. So notes virtually always get short-changed.

Very occasionally hallucinated notes are better than notes that are almost always incomplete.

What about increasing the supply of doctors rather than decreasing the time they spend with patients?

I question the underlying premise that efficiency needs to increase.

Because the USA is for-profit healthcare industry they need to optimise and increase efficiency. That's the only way to make the numbers go up. Therefore fewer doctors, fewer nurses, fewer administrators (maybe), and more paying patients.

> more paying patients

that's a chilling thought; don't give them ideas

Surprising that you imply they haven't already been capitalizing (ha!) on that idea since the 1970s :D

It's no better in other countries. Other country's health care systems are typically monopsonies, which means we get crappier results for lower prices. So instead of the doctor choosing to do 6 patients per hour instead of 4, it's the government.

In the case of summarizing it is not time spent with patient is time recording what was discussed.

I recently heard a talk from doctolib (French company that among other offers now the summarization service to doctors) and they mentioned that before AI, doctors were writing on average 144 characters after a patient visit. I doubt half a tweet is the ideal text to convey information.

Note taking is not about the time spent with patients. It's about keeping a good record for next time and insurance and is a major reason for physician burnout. Some doctors will finish up charting when after hours.

Yes physicians could still see fewer patients but filling out their mandatory notes is annoying regardless of it's a manageable amount of patients or a work extra hours amount.

> AI converging with medical technology is a really dangerous space, for obvious reasons. An article like this does make me worry it's being rushed through, but not because of the author's objections, instead because of their ignorance of what is and what isn't AI

I mean, worth pointing out that OpenAI has been shoving LLMs into people's faces for going on about a year and half now at global scale and calling it AI, to a degree that now we have to call AI AGI, and LLM's get called AI, even though there is nothing intelligent about them whatsoever.

Just saying when the marketing for a tech is grinding the edge of being misinformation itself, it's pretty normal for the end users to end up pretty goddamn confused by the end.

For 60 years the Turing Test was the standard benchmark for artificial intelligence. Now machines can pass the test. The only goalpost moving I can see is the moving done by the people who insist that LLM's aren't AI.

The simple state machines and decision trees that make enemies move and attack in video games, we also call AI.

AI is a loose term and always has been. It's like the term "robot": we call any machine a robot which either a) resembles a human or part of one (e.g., a robotic arm), or b) can perform some significant human labor that involves decision making (e.g., a robot car that drives itself). Similarly, AI is anything that makes, or seems to make, judgements that we think of as the exclusive purview of humans. Decision trees used to be thought of as AI, but today they are not (except, again, in the context of video games where they're used to control agents intended to seem alive).

> The simple state machines and decision trees that make enemies move and attack in video games, we also call AI.

Yes but no game companies have ever marketed their game asserting that the things your shooting are, in fact, self-aware conscious intelligences.

Tell me you weren't around for the PlayStation 2 marketing blitz without telling me you weren't around for the PlayStation 2 marketing blitz.

They actually named the thing's CPU the Emotion Engine.

That's been the technical definition in the AI research community for at least 50 years. "AI = machines that think like people" is the sci-fi definition.

Yes but OpenAI is flagrantly using the people's sci-fi defintion understanding to radically overvalue it's, to be blunt, utterly mid products.

> AI = machines that think like people" is the sci-fi definition

It's also the layman's definition

Which does matter because laymen are the ones who are treating this current batch of AI as the silver bullet for all problems

> No matter how many tech bros try to force it through.

Are you sure about that? My wife is a nurse and she has to deal with multiple machines that were put in her unit just because the hospital has a contract with XYZ brand. It doesn't matter at all if these machines are 5x more expensive, x10 slower, x80 less effective, etc... compared with the "other" machines (from other brands).

I'm actually terrified the same might happen with this.