Paul Alivisatos, president of the University of Chicago, proposes an educational sequence rather than a choice between banning AI and using it everywhere: first develop independent writing, reasoning, and judgment; then deliberately integrate computational tools. Students should learn to think without machines, with machines, and critically about machines, becoming ethical, skeptical, and ambitious users of AI.
The distinction is between producing an answer and forming the person who can evaluate it. This connects ai-and-mental-effort to institutional safeguards against cognitive-surrender.
The intended mechanism is foundational apprenticeship before tool-assisted acceleration. Protected unaided work develops the judgment needed to scrutinize later machine-assisted results. AI literacy also includes authorship, ethical use, and legal and democratic governance—not merely prompting skill.
This parallels code-reading-as-cognitive-labor: work can be valuable because it builds expertise, even when a machine could produce the immediate artifact faster. This connection is wiki synthesis, not a result demonstrated by the article.
The source is an opinion column and a first-person account of planned reforms, not a comparative evaluation of educational outcomes. It offers no measured evidence that this sequence produces better learning than alternatives. Faster advances in knowledge and well-being are the author's aspiration.
Open questions: how to assess unaided capability, when students are ready for AI integration, how to distinguish formative effort from unnecessary friction, and how to verify compliance outside the classroom.
“Teach Students to Think With, Without and About AI,” Paul Alivisatos, The Wall Street Journal, September 20, 2026. Captured from the full article text supplied by Andrey; direct WSJ access was blocked by device verification.
Related pages: ai-and-mental-effort, cognitive-surrender, code-reading-as-cognitive-labor.