Ethan Mollick · University of Pennsylvania (Wharton) · 2024-12-09
Mollick's most-shared piece is the rare AI-at-work essay that does not flatter either side. Fifteen concrete situations where current models genuinely raise output, and five where the same models will quietly degrade your judgment, your learning, or both. The framing is workmanlike and the examples are specific enough to argue with.
For a learner this is the right entry point into the productivity question, because Mollick refuses to give the answer the audience wants. He insists you keep the expertise that lets you grade the model, and he is unsparing about the tasks where struggle is the point. Read it before any LinkedIn essay on the same topic.
> Using AI well requires holding opposing ideas in mind: it can be transformative yet must be approached with skepticism.