Historical research taste in the AI era, told through Babylonian math
What happened
An article on the Hacker News front page discusses the "taste" needed for historical research in the AI era. The author argues language models are good at memorization and archive retrieval but stuck in a "median perspective," lacking the research taste the humanities require. The piece uses Oxford tutor Allan Chapman insisting the author learn Babylonian base-60 mathematics to show why historical research needs exposure to seemingly useless knowledge. Understanding alien epistemologies and obsolete ideas, rather than relying on memory and retrieval alone, is the foundation of historical research, the author writes.
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Coverage
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- Hacker News front pageResearch taste in history: the importance of learning Babylonian math
面对 AI 时代，历史学者认为语言模型虽擅长记忆与档案检索，却困于“中位视角”，缺乏人文学科的“研究品味”。作者以牛津导师 Allan Chapman 坚持让其学习巴比伦 base-60 数学为例，指出理解无用知识、异质认识论与过时观念，才是历史研究的根基。
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