An essay published by Tom Renner takes aim at a familiar argument in tech policy and AI debate: the idea that a future dominated by large language models is inevitable.
The piece uses the term “inevitabilism” to describe a rhetorical move in which speakers frame a projected future as unavoidable, then recast disagreement as denial of reality. Once that frame is accepted, the argument shifts away from whether a technology should dominate public life and toward how everyone else must adapt to it.
Renner’s argument is not that AI is unimportant. Instead, he says the problem is the language used to discuss it. He points to lines from high-profile tech leaders about learning to coexist with AI or being displaced by people who use AI more effectively. In his view, those claims do more than forecast change. They also set the terms of the conversation before that conversation has really begun.
The essay draws on Shoshana Zuboff’s work on surveillance capitalism to show how naming a pattern can make it easier to resist. Renner argues that “inevitabilism” is one such pattern. By giving the tactic a name, he says readers can see how it works: it turns a contested direction of travel into a supposedly settled fact.
That matters because the rhetorical move is persuasive. It can create momentum, social pressure and a sense that resistance is naïve. It can also subtly suggest that the only responsible response is to accept the future being offered. Renner describes that as a narrowing of choice, not a neutral prediction.
The essay’s central claim is that people still have agency over what technological future they want, including how machines are used and what kinds of systems deserve to be built. Rather than treating AI as destiny, the article argues that the public should ask what kind of future would actually be worth choosing.
The piece is opinionated, but its broader point is easy to recognize in current tech discourse. Companies announcing new tools often frame them as unavoidable steps in an already moving direction. Investors and executives do the same when they describe adoption as inevitable and resistance as temporary. Those claims can be true in a narrow market sense while still being politically loaded.
Renner’s warning is that inevitability language can drain energy from democratic debate. If the public is told that a future has already arrived, it may stop asking whether that future is desirable, who benefits from it or what trade-offs should be negotiated now rather than later.
In that sense, the essay is less about one model or one company than about a habit of argument. It suggests that the more often AI is described as something society must simply adapt to, the less room remains to decide how it should fit into work, culture and power.
Whether readers agree with the conclusion or not, the argument lands because it names something many people already feel: that “inevitable” is often less a prediction than a strategy.
