Date Thesis Awarded

4-2024

Access Type

Honors Thesis -- Access Restricted On-Campus Only

Degree Name

Bachelors of Arts (BA)

Department

Economics

Advisor

Robert Hicks

Committee Members

Lisa Anderson

Daniel Vasiliu

Abstract

Our research explores how knowledge of an AI opponent impacts investment behavior in a public goods game, with the aim of shedding light on the dynamics of human-AI trust. We had three treatments of human subjects play the same VCM with varying levels of information about their opponents. While we did not find varying levels of knowledge to significantly impact investment, consistent with existing studies, we found ChatGPT to exhibit greater prosocial behavior than its human counterparts. Regardless of the opponent, human participants were likely to exploit players who exhibited high levels of prosocial behavior, leading to the paradoxical outcome of humans freeriding off AI. We also found the AI to be sensitive to prompting and system role content, suggesting that the desired level of cooperation can be fostered through parameterization. This paper provides a commentary on the current state of human-AI trust through a strategic game’s framework.

Available for download on Saturday, April 24, 2027

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