Academics Must Wake Up on AI (with Alexander Kustov)

The political scientist Alexander Kustov recently published a Substack post with a provocative claim: that AI can already do social science research better than most professors. The post went viral. It attracted more than a million views and over a thousand responses, many of them very angry. (Some people even demanded that Alex’s university fire him.)

In this conversation, we talk about this controversy and the claims that triggered it, including:

* What agentic AI tools like Claude Code and Codex can already do for research, from coding and data analysis to literature reviews, translation, and brainstorming, and why only around 20% of quantitative social scientists currently use them.

* What best predicts whether researchers adopt or reject AI: ignorance, openness to experience, methodological background, or the awkward role of self-interest.

* How much published academic research is genuinely mediocre, and whether the cause is laziness, lack of skill, or a broken incentive structure, with a detour through the replication crisis and some high-profile fraud cases.

* Whether AI will raise the quality of research or simply flood the literature with more slop, and what journal editors could do about it.

* Whether AI can be genuinely creative or only recombine what already exists, by way of Margaret Boden’s three kinds of creativity, Thomas Kuhn on paradigm shifts, and AlphaGo’s “Move 37”.

* The fight over AI writing and detection tools like Pangram, and why current disclosure norms end up punishing the honest.

* The angry response to Alex’s series, and what is really driving reflexive opposition to AI among academics.

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Links and further reading

* Alexander Kustov — Alex’s homepage, with an overview of his research on immigration, public opinion, and effective governance.