I'm a bit more optimistic in that it might just be able to effect that change through brute force: Scaling a call center is more expensive than scaling phone robots/agents.

You could counter that health insurers will just start staffing their call centers with their own robot army, but I suspect that the occasional incredibly expensive hallucination will put an end to that at least in the medium term.

Bruteforce trial and error to change something like healthcare would still take years even with superintelligence.

What it can do is create the best simulation and a model representation and bruteforce on top of that and then take actions, but the model will still be far from perfect and it likely just will help do a bit wiser or optimal decisions, that are like 10 percent efficiency gain here, 20 percent there, etc. And it will take years to see results.

Many of the urgent problems in US healthcare are man-made and economic/organizational, not scientific, in nature.

This is actually one of the areas where I'm pretty optimistic about LLMs (at least if used defensively against, not aggressively by, sprawling bureaucracies).

LLMs can be the email-to-dozens-of-hours-on-the-phone-for-personal-reasons adapter anyone other than billionaires and company execs could only dream of until now.

You're assuming health insurers will give a shit about phone robots/agents' hold times.

Individually, "I'm unable to reach anyone" is much easier to chalk off to "maybe I just wasn't patient enough, so this is partially on me".

But if you can provide statistics that a given health insurer is practically not answering 90% or so of their calls (because they time out at the phone level), that's probably not something they can ignore in the long term.

There is some gap between AGI and a singularity, at least in principle. The term "singularity" doesn't mean "black swan that disrupts society", it means "intelligence trends to ~infinity (or at least something incomprehensible to humans) recursively in a very short period of time". That's (on paper) a much stronger result than an AI that can reason as well as humans in a domain-general way.

An AGI that is 20% better than humans at everything might be able to recursively improve itself effectively without limit, but it also might not. It took billions of humans millennia to invent things smarter than ourselves even in limited domains; such an AGI - even if it is significantly smarter than humans at everything - might take decades or centuries to produce a similar relative improvement. No doubt it would still change our world in massive ways, but it wouldn't be a singularity.

Even if AGI was reached, turning around the current system could still take years.

So it is easier to start from the edges, even for AGI.

AGI would still need unfathomable processing power in order to predict which system would work to everyone's needs.

> figure out how to actually provide healthcare to people who meed it

But what if the proposed solution costs lots of people their jobs?

Is the scientist's analysis the blocking part of innovating in medicine and healthcare? I would have though the main problem is experiment time to actually get useful results back, and even approval to attempt the experiment.