A confession from inside the system: higher education is not currently built to produce the people the AI economy needs.
I don’t mean this as provocation. I mean it structurally. We are organised around producing specialists — deep, narrow, credentialled — and we are rewarded, individually and institutionally, for going further in that direction. That model worked when the entry-level work surrounding a junior specialist gave them, by accident, the breadth they would need to become senior. The graduate trainee at the law firm wasn’t only drafting contracts; they were absorbing the firm, the client, the judgement, the politics. The work was the curriculum.
AI is now doing that work. Faster, cheaper, mostly well enough. Which means the curriculum has gone, and the specialists arriving on day one are turning up without the breadth that used to come bundled with the job.
This is the part of the AI-and-jobs debate that almost nobody is having. We argue about whether AI replaces jobs or augments them. We do not argue nearly enough about what happens to professional formation when the bottom rung disappears — and what it means that the entire architecture, from undergraduate degree to chartered qualification, was built on the assumption that the rung would be there.
Adam Riley and I have a piece on the PolymathMind Substack pulling at this thread, hung off Rishi Sunak’s two rather different positions on AI. Our provocation: AI-mediated work is collective intelligence, and the collective only performs if the human side is upgraded as deliberately as the machine side. Almost nobody is doing that deliberately yet.
