Intern to Toolmaker: Five Roles AI can Play in Productive Study

Dominik Lukeš told Oxford students they are at Oxford to change their brain and to change the world, and that AI is a good use when it makes both better. He set out five roles for AI in study: intern or assistant, tutor, consultant, translator and toolmaker. Each has a use and a danger, and the answer to errors is built-in verification, since people make errors too. The toolmaker role leads to desktop agents that use tools on your own computer, which is new in 2026. He called the lecture a menu of options and advised against trying everything at once.

You'll come away with

• Three rules for using AI in study: do not say you did something when AI did it, do not say you worked unaided when you had help, and do not use AI when told not to.
• What each of the five roles does, with his examples: a background search, a calendar file made from a description of his week, feedback on a tweet, a song and a mind map, and a Czech exercise website.
• Why asking for a summary of a hard passage fails, and the steps he uses instead, from bullets and propositions to definitions, sense checks and your own writing with feedback.
• A first task for a desktop agent, the downloads folder, and a way to use it on a paper: replicate one analysis rather than summarise.

Narration uses a synthetic voice. This video is an AI-assisted summary of the recorded lecture.