Integrating machine behavior into human subject experiments: A user-friendly toolkit and illustrations

Christoph Engel, Max R. P. Grossmann and Axel Ockenfels

No 2024_01, Discussion Paper Series of the Max Planck Institute for Research on Collective Goods from Max Planck Institute for Research on Collective Goods

Abstract: Large Language Models (LLMs) have the potential to profoundly transform and enrich experimental economic research. We propose a new software framework, “alter_ego†, which makes it easy to design experiments between LLMs and to integrate LLMs into oTree-based experiments with human subjects. Our toolkit is freely available at github.com/mrpg/ego. To illustrate, we run differently framed prisoner’s dilemmas with interacting machines as well as with human machine interaction. Framing effects in machine-only treatments are strong and similar to those expected from previous human-only experiments, yet less pronounced and qualitatively different if machines interact with human participants.

Keywords: Software for experiments; large language models; humanmachine interaction; framing (search for similar items in EconPapers)
JEL-codes: C91 C92 D91 L86 O33 (search for similar items in EconPapers)
Date: 2023-12
New Economics Papers: this item is included in nep-ain, nep-big and nep-exp
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Related works:
Working Paper: Integrating Machine Behavior into Human Subject Experiments: A User-Friendly Toolkit and Illustrations (2024)
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