Integrating Machine Behavior into Human Subject Experiments: A User-Friendly Toolkit and Illustrations

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

No 302, ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany

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 oTreebased 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 humanmachine 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)
Pages: 46
Date: 2024-05
New Economics Papers: this item is included in nep-ain and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.econtribute.de/RePEc/ajk/ajkdps/ECONtribute_302_2024.pdf First version, 2024 (application/pdf)

Related works:
Working Paper: Integrating machine behavior into human subject experiments: A user-friendly toolkit and illustrations (2023)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ajk:ajkdps:302

Access Statistics for this paper

More papers in ECONtribute Discussion Papers Series from University of Bonn and University of Cologne, Germany Niebuhrstrasse 5, 53113 Bonn, Germany.
Bibliographic data for series maintained by ECONtribute Office ().