[dluan]

Scientists have been obsessed with over-optimzing for FOMO for the past decade - what papers should I read that I don't have time for, what grants should I apply for that I don't know about, what projects should I work on that will give me the best ROI, who in my field is poised to disrupt or make a big leap, etc.

Some even think that the end goal is actually an autonomous research agent that can make decisions about what questions to ask and why, and that's one of the true marks of AGI. That to me is insane and misses the entire point of science altogether, even once we reach that technical feasibility. We ask questions about the universe to expand our human relationship with the universe, not to just amass more research capital for the sake of it. And the fact that the AI snake oil has infected big chunks of science reveals which parts of it are just gold rush speculation and which aren't.

There's a more fundamental challenge of training scientists to understand why we ask the questions we ask. You can't just offload that to some background task and trust that it makes sense.

[Onawa]

I understand the point that you're making about overoptimizing for FOMO in science. I wanted to give you another perspective from a scientist working within the US government that doesn't care about playing that game.

Our governmental research agency, and NIH as a whole has TONS of research data that we don't have the manpower to screen and provess. There are also gaps in data that AI/ML could help us simulate. AI research assistants could potentially help us process and evaluate "what questions to ask" by, for example, looking for trends in QSAR (quantitative structure-activity relationship) models for novel chemicals and help us direct our attention to compounds of toxicological interest.

We've also been trying to use the AI research assistants to speed up the process of evaluating the scientific literature for toxicologists who have to make regulatory decisions. Our agency has a backlog of chemicals that we would love to evaluate, but lacks the manpower to do so.

No profit motive or much "clout" interest, at least that I've seen. Just a lot of public servant scientists who need some extra help protecting the public.