AI Alignment Research Is Science Fiction, and the Field Knows It

A Substack post arguing that AI alignment research is "more science fiction than science"[¹] landed this week in a community that has spent years insisting otherwise — and the reaction wasn't outrage. It was recognition.

That's the detail worth sitting with. The safety establishment has spent months arguing about hypothetical superintelligence while mundane misuse compounds in the background. Now the critique is coming from inside: a Cambridge University Press piece proposing that the field "reverse its logic" entirely[²], a pointed takedown of the xAI alignment plan on Astral Codex Ten[³], and a Scale AI entry urging researchers to get chatbot alignment done before some unspecified too-late moment arrives[⁴]. These aren't outsider provocations. They're published by people who read the same papers, cite the same researchers, and attend the same workshops. The self-criticism has reached a kind of critical mass.

What makes this moment different from previous rounds of alignment skepticism is the specific target. Earlier critiques tended to focus on timelines — "AGI is further away than you think" — or on priorities — "worry about bias before superintelligence." This week's cluster of writing goes after the epistemics. The argument, roughly, is that alignment research has developed the aesthetic of science without the substance: thought experiments dressed as theorems, intuition pumps labeled as frameworks, blog posts peer-reviewing blog posts. One Bluesky commenter who has written sympathetically about AI risk made the case plainly: anti-AI concern rooted in genuine safety worries needs to find "materially productive action targeting specific goals" rather than circling the same abstractions.[⁵] The frustration there isn't with the concern — it's with the form the concern keeps taking.

The WSJ's "Monster Inside ChatGPT" framing[⁶] suggests mainstream outlets are still happy to run the gothic version of the alignment story, complete with menacing subtext and vague dread. That framing coexists uneasily with the more rigorous self-critique happening in alignment-adjacent publishing — and the gap between them is itself the story. Popular coverage keeps the existential drama alive for general audiences while practitioners increasingly question whether the field has produced anything falsifiable. Nobody at the top is claiming they know how to keep AI safe, and now a growing number of researchers are asking whether the people claiming to study the problem have actually been doing science at all. That's a harder question than the one the field usually fields — and the fact that it's being asked loudly, in credentialed venues, by people with skin in the game, means it won't go away when the next capability announcement arrives.