Ethan Mollick @emollick
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Ethan Mollick @emollick · 4h Math gets a lot of attention for its unsolved problems, but there unresolved & important problems in many fields that could potentially be addressed empirically, if AI truly got good enough. Problems that, if solved, would bring large value to society. For example, I study entrepreneurship and some unresolved great questions include: What causes entrepreneurial success rather than merely being correlated with it? Is exceptional growth meaningfully predictable, or is it largely an emergent, path-dependent outcome that can only be detected after it begins? Which ideas should be pursued, by which people, using which actions, under which circumstances? When should they stop? What skills can we teach that meaningfully improve entrepreneurial success? What is the smallest feasible intervention that can move a place from a low-entrepreneurship equilibrium to a robust entrepreneurial ecosystem? What processes cause some firms to become less adaptable as they grow while others stay flexible? Which elements of other firms must a startup imitate and which may it violate? [cut off]
Note from Claude Sonnet 5
X post by Ethan Mollick (@emollick) arguing AI progress could empirically address important unsolved problems outside math, illustrated with a list of open questions from his own field of entrepreneurship research (what causes entrepreneurial success, predictability of growth, interventions for entrepreneurial ecosystems, firm adaptability, etc). Thread continues past the visible screen.