The late Dr. Allan Chapman, an Oxford history of science scholar from a working-class background, exemplified the human research taste that automated systems lack. While advanced language models excel at memorization and archival tasks, they typically converge on median viewpoints and intellectual blandness. Chapman combated conventional thinking by holding tutorials at the King’s Arms pub and having students master ancient base-60 mathematics and Sumerian-Babylonian astronomy. His immersive methods demonstrate how unexpected intellectual paths remain essential in an era dominated by artificial intelligence.
Key points
Human qualities like creativity and eccentricity provide a vital counterweight to artific…: Human qualities like creativity and eccentricity provide a vital counterweight to artificial intelligence systems that converge on median viewpoints.
True research taste in the humanities requires the ability to immerse oneself directly in…: True research taste in the humanities requires the ability to immerse oneself directly in unfamiliar worlds of thought.
Finding meaning within seemingly useless historical knowledge helps scholars cultivate un…: Finding meaning within seemingly useless historical knowledge helps scholars cultivate unique perspectives that machines cannot easily replicate.
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“Variety, not uniformity, is more likely to be the key to progress. The genius of being is whimsical rather than consistent. Our strata show broken bones of histories all forgotten.” — Benjamin Blood, as quoted by William James, 1911
I’m sometimes asked how I think history education and research will change in an era being reshaped by AI. I don’t trust anyone who claims certainty on the topic, because “AI” is such a moving target (and its impacts on the humanities so poorly understood) that any views are provisional.
But, it seems to me that we are entering an era in which traits like eccentricity and creativity are going to matter much more than before. Language models excel at pedagogies involving memorization, spaced repetition, and customized feedback. They are also getting good at “brute force” archival research. Yet they remain stuck in a median perspective, a sort of averaged-out, clichéd intellectual blandness that helps explain why frontier models still lack “research taste” in humanistic disciplines. (I think this is also why different frontier models converge on an oddly similar tone…
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