AI doomerism will recede from public consciousness because frequent release of AI models shows that they are harmful in prosaic, rather than existential, ways
If I'm being honest, my immediate reaction to the news that Sam Altman had been fired as C.E.O. of OpenAI was something like ... relief? Threads: @technicallymims . Mastodon: @carnage4life@mas.to Threads: Christopher Mims / @technicallymims : this is the best summary I've ever seen of why so many people within tech touted AI doomerism which on the surface is a strange thing for people building and funding AI to do tl;dr - profit motive brilliant stuff (as usual) from Max Read https://maxread.substack.com/ ... Mastodon: Dare Obasanjo / @carnage4life@mas.to : I agree with Max Read's take that the OpenAI drama is the end of mainstreaming of AI doomerism. Doomerism was convenient for cynical players, including Sam Altman, to attempt to co-opt governments into slowing down their competitors. …
Context & Ripple Effects
The piece arrives just after OpenAI's leadership crisis, in which Ilya Sutskever reportedly cast Altman's removal as protecting a mission to benefit humanity the mission-first rationale for Altman's ouster. Related coverage also described a fault line between OpenAI's profit-oriented and nonprofit constituencies the clash between its profit and nonprofit camps.
It reframes AI-risk rhetoric as a political and commercial narrative rather than a reliable guide to observed product harms. That argument follows an earlier weakening of the pause movement, as some supporters of the proposed training pause reconsidered their position support for an AI-training pause fractured.
First-order effects
- The immediate effect is rhetorical: public discussion can shift from extinction scenarios toward concrete harms associated with deployed models, making claims of existential danger harder to sustain on their own.
- For OpenAI and other frontier-model developers, safety language becomes more closely scrutinized for whether it is paired with practical safeguards rather than invoked as a broad justification for control or intervention.
Second-order effects
- Competitors may differentiate by emphasizing tangible reliability, misuse, and user-impact controls, instead of treating generalized catastrophe narratives as the primary safety case.
- Policy debate could put greater weight on evidence from deployed systems and less on blanket pauses, though the corpus does not establish that governments will adopt that framing.
Third-order effects
- If repeated releases keep normalizing frontier models, AI governance may evolve from a singular existential-risk debate into a more conventional contest over product accountability, market power, and institutional oversight.
- The OpenAI episode suggests that safety framing can remain strategically important even as public attention moves toward everyday harms; the durable question is who gets to define and enforce safety.
The trend: AI risk discourse is moving from abstract catastrophe claims toward governance of increasingly routine, commercially released AI systems.