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Comment by wl | Hacker News Reader

If nurses are to do more of the work of physicians, nursing education needs to drastically change. Nurses are mostly taught the how of nursing and not the why of medicine. If you look at the curricula of DNP programs, which are often touted as a way to get nurses practicing with lots of autonomy in places where they are short on physicians, they're heavy on nonsense nursing theory and light on things that actually matter like pathophysiology and pharmacology.

We actually do have a better model in the form of physician assistants. They're taught the same kinds of things physicians are taught, just in less depth.

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That is the kind of thing makes me wonder how much of "things that actually matter like pathophysiology and pharmacology" can be factored out into the automation land now.

AI isn't perfect, but even loosely scaffolded generalist systems show promise in the field of medicine now. And the alternative isn't some hypothetical "perfect healthcare" - the status quo is often closer to "nurses running near the limits of their competence" or "physicians stretched thin almost to the breaking point".

The fundamental problem of healthcare is that it struggles to scale. The need for well educated, well paid professionals is inescapable. Or, was inescapable? We might be at the point where this can start changing.

> That is the kind of thing makes me wonder how much of "things that actually matter like pathophysiology and pharmacology" can be factored out into the automation land now.

I would say not much. AI is still often wrong and a clinician needs to know when the LLM is saying something crazy. I think AI has the most promise for increasing the productivity of well trained professionals, not replacing them (or their training) entirely.

Human clinicians are also "often wrong", for a given definition of "often". "Get a second opinion" didn't originate with AI.

Are AIs wrong more often or less often?

Would the healthcare get better or worse if the "first opinion" was AI more often than not?

"Increasing the productivity" and "replacing them" is two sides of the same coin. If a human can do five times the work, because AI does most of the work and the human performs "exception handling"? You need less humans. And healthcare, historically, is almost always human-constrained. That's why you get insane wait times and overworked clinicians. Most other inputs scale more readily than human expertise.

Thus the impetus to figure out where "human expertise" can be substituted for that of a scalable machine system - and what would be the best ways to implement that.

I was replying to "how much of 'things that actually matter like pathophysiology and pharmacology' can be factored out into the automation land"

I'd argue they aren't being factored into automation land if they're still the responsibility of a human expert, even if there are fewer more productive human experts.

(Though I do think AI will have a role in pathophysiology and pharmacology, initially catching errors, and probably some day taking responsibility, but not soon.)

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