用人类学提升AI对多元经济的理解能力
Economic Anthropology in the Era of Generative Artificial Intelligence
- 用人类学知识训练AI模型，增强其对多样经济系统的认知
- 新模型在理解非市场经济系统上表现更优，识别准确率显著提升
- 适合研究跨文化经济、可持续发展与伦理AI的学者
本文探讨经济人类学与生成式人工智能（GenAI）的交叉领域。研究分析大型语言模型（LLMs）模拟人类决策的能力及其内在归纳偏见。提出两个AI模型：C.A.L.L.O.N.（基于常规数据训练）和M.A.U.S.S.（融合人类学知识）。结果显示，融入经济人类学知识的M.A.U.S.S.在识别多元经济体系与概念方面表现更佳。研究证明，将经济人类学与AI结合，有助于形成更包容的经济学理解，提升非市场经济系统的可持续性。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。