Economic Anthropology in the Era of Generative Artificial Intelligence

Zachary Sheldon and Peeyush Kumar

Papers from arXiv.org

Abstract: This paper explores the intersection of economic anthropology and generative artificial intelligence (GenAI). It examines how large language models (LLMs) can simulate human decision-making and the inductive biases present in AI research. The study introduces two AI models: C.A.L.L.O.N. (Conventionally Average Late Liberal ONtology) and M.A.U.S.S. (More Accurate Understanding of Society and its Symbols). The former is trained on standard data, while the latter is adapted with anthropological knowledge. The research highlights how anthropological training can enhance LLMs' ability to recognize diverse economic systems and concepts. The findings suggest that integrating economic anthropology with AI can provide a more pluralistic understanding of economics and improve the sustainability of non-market economic systems.

Date: 2024-10
New Economics Papers: this item is included in nep-cmp and nep-hme
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Published in Annual Joint Meeting of Society of Economic Anthropology and Society for the Anthropology of Work 2024

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2410.15238

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