Researchers Use AI To Analyze Life Histories
Economists David Lagakos, Stelios Michalopoulos and Hans-Joachim Voth analyzed the Depression-era American Life Histories archive in 2025, using ChatGPT to scale classification across nearly 3,000 memoirs. They found that, alongside family and friendships, respondents—especially women—frequently cited work as central to meaning. The finding underscores work’s psychosocial importance and informs policy discussions about potential AI-driven labour displacement.
Key Points
- 1Used ChatGPT to classify nearly 3,000 Depression-era American Life Histories corpus.
- 2Revealed recurring emphasis on work as central source of meaning, especially in women's narratives.
- 3Suggests policy and labor discussions should account for work's psychosocial value amid AI-driven displacement.
Scoring Rationale
Novel application of LLMs to a large historical corpus with clear societal relevance; limited by single-study reporting and unclear peer review.
Sources
Public references used for this report.
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