This is an empirical question, right? We could have three teams of researchers, team A focusing purely on understanding, team B focusing purely on solving problems, and team C focusing on a combination of the two. See which one makes the most breakthroughs on problems we actually care about.

I respect Tao and I believe he's trying to think deeply about the issues, but a lot of his thinking seems to revolve around preserving the current roles and prestige of mathematicians, and also makes a lot of assumptions about the capabilities of AI years or decades into the future.

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mrlongroots an hour ago | parent [-]

> This is an empirical question, right? We could have three teams of researchers, team A focusing purely on understanding, team B focusing purely on solving problems, and team C focusing on a combination of understanding and solving problems. See which one makes the most progress.

This is not me being snarky, but all meaningful questions can be settled empirically---e.g., "what happens to my body if I jump off the cliff". But empirical trials have a cost (time, money, irreversibility etc.) and we model and predict because it's cheaper than the trial.

	▲	fasterik an hour ago \| parent \| next [-]
		My point is that pushing for human understanding as the primary goal assumes an answer to an empirical question that we don't yet have evidence for. How do we know that human understanding is the right instrumental goal, as opposed to solving open problems as fast as possible? Even if we think human understanding has intrinsic value, how do we know which approach will maximize human understanding in the long run? The idea that all meaningful questions can be answered empirically is known as "verificationism" and is philosophically quite dubious. https://en.wikipedia.org/wiki/Verificationism
	▲	pmoriarty an hour ago \| parent \| prev [-]
		> all meaningful questions can be settled empirically This is a logical positivist view, that not everyone agrees with.