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People & subjects

Ethan Mollick

Ethan Mollick is a Wharton researcher and author exploring how AI changes work, learning and decision-making.

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In the conversation

Getting the answer is different from learning

Mollick argues that AI can support learning when it guides the learner through the work. An assistant that simply supplies answers can remove the practice that builds understanding, even when the user has good intentions.

Open conversation

From the terminal

Current models already leave an overhang of unused work

Ethan Mollick argues that GPT-6 Astra and Fable 5.1 already do long stretches of guided work, and that the useful human edge is deep knowledge, wide knowledge, taste, and agency. The demos are his own projects, not a measured labor study.

An early look at working with a Mythos-class model

Ethan Mollick describes early access to 5 Fable, says it outperformed other public models he had used, and says he tested it on work other than the software-security uses dominating the discussion.

Source library

One Useful Thing

Connect evolving AI use to work, learning and practical choices people face.

Context and limitations

Demonstrations and personal experience are not controlled estimates; follow cited studies for methods and limits.

Public essays and RSS from Ethan Mollick with links to demonstrations and research