The left is missing out on AI – by Dan Kagan-Kans
February 19, 2026
“Somehow all of the interesting energy for discussions about the long-range future of humanity is concentrated on the right,” wrote Joshua Achiam, head of mission alignment at OpenAI, on X last year. “The left has completely abdicated their role in this discussion. A decade from now this will be understood on the left to have been a generational mistake.”
It’s a provocative claim: that while many sectors of the world, from politics to business to labor, have begun engaging with what artificial intelligence might soon mean for humanity, the left has not. And it seems to be right.
This idea, that large-language models merely produce statistically plausible word sequences based on training data, without having any idea about what the words refer to, has become the baseline across much of the left-intellectual landscape. Thanks to it, fundamental questions about AI’s capabilities, now and in the future, are considered settled.
I’m not entirely sure that the claim from Joshua Akyem from OpenAI is entirely true, but it may well be directionally so. Through mostly anecdotal evidence (people I follow on social media, events that I attend), I find folks who might call broadly of the left are much more likely to be resistant towards and even antithetical toward AI technologies.
In some ways, that’s not without reason, and I think there are genuinely very important conversations to be had about everything from the environmental impact to the impact on the eternal tension between labour and capital, and the enclosure of the intellectual commons that large language models in many ways represent.
I think the observation that, by steadfastly and often increasingly irrationally or erroneously critiquing the technologies themselves, as Dan Kagan-Kans observes here (“just next token prediction…”), simply deals you out of the conversation of what these technologies might look like and how they may be applied in the future.
