Summary of Economic Anthropology in the Era Of Generative Artificial Intelligence, by Zachary Sheldon et al.
Economic Anthropology in the Era of Generative Artificial Intelligence
by Zachary Sheldon, Peeyush Kumar
First submitted to arxiv on: 20 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: General Economics (econ.GN)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel intersection between economic anthropology and generative artificial intelligence (GenAI) is explored in this study, which examines how large language models (LLMs) simulate human decision-making and the inductive biases present in AI research. The paper introduces two AI models: C.A.L.L.O.N. and M.A.U.S.S., each trained on different data sets. 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. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study combines artificial intelligence with economic anthropology to better understand how humans make decisions about money and resources. Researchers created two special computer models, C.A.L.L.O.N. and M.A.U.S.S., that can think like humans do when it comes to economics. They found that by teaching these AI models about different ways people live and work, they can become more fair and good at understanding how societies use money. |
