By Jim Clifford
It is never fun to watch friends argue. Generative AI has created multiple fractures across our universities and the community of historians. The stakes are high and we are all dealing with the repercussions. I spent a few weeks in August rebuilding my second-year course for the third time. Two years ago, I swapped the traditional research essay for a StoryMap project, thinking that even if the students used GenAI, they’d still learn something making the map. But now, a student with Claude in Chrome could get the LLM to build the whole map without any real engagement. This year I’m trying a hybrid of contract grading and ownership. It was a lot of work and I still worry about what we’ve lost without a traditional essay.
The frustration and anger with the tech companies make it hard to hold a conversation. I’m worried about the future of higher education at the scale it has operated for the past half century. If machines are starting to displace recent graduates in the employment market, then the basic promise of working hard to earn a fulfilling and remunerative career is under threat. I understand the decision to simply refuse: not to engage with this technology and not to pay Anthropic or OpenAI a monthly subscription. I also understand why people are skeptical about any claims about the ability of LLMs. In 2024, OpenAI claimed PhD-level intelligence for models that couldn’t count the number of Rs in “strawberry.” Professors saw the regular failure of LLMs hallucinating historical arguments and citations. But a lot has changed in the past fifteen months, with the emergence of agentic systems, and then in mid-2026, with the launch of the Fable and Astra models. The problem is that both of these systems take investment to learn how to use and high-tier subscriptions. So, the vast majority of historians have not seen how they work.
My proposal here is to engage with those of us who are using the tools to understand where we stand in 2026 so we can collectively start to talk about what needs to change as we move into 2027 and 2028. I am not asking anyone to change their ethical stance, and I acknowledge there are large problems with the current build-out of data centres without enough regulations to mitigate environmental concerns. These issues are real, but I have decided, for myself, that critical engagement is how I can best understand the technology and think through its implications. The profession needs some of us working inside these tools; it does not need all of us to.
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