alt Hacker News> 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.