.png){kind=icon}
.png){kind=icon}
Return
Altruistic behavior in generative artificial intelligence: a comparative study using Dictator Game experiments
.png){kind=icon}
OA
AI
DOI：10.18845/tm.v39i5.8524.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper examines the growing integration of artificial intelligence (AI) in various social domains, with a focus on altruistic behavior exhibited by large language models (LLMs) such as GPT-3.5-turbo. As these models evolve and gain sophistication, there is a need to investigate whether they can replicate the complexity of human behavior in moral decision-making, particularly in situations involving altruism. The study uses the Dictator Game, a classical experiment in behavioral economics, to analyze how LLMs respond in scenarios where an agent decides how to divide a sum of money between themselves and an anonymous recipient without expecting any reward. The key research question is whether different versions of GPT-3.5-turbo exhibit variation in altruistic decision-making. The comparison of GPT-3.5-turbo's decisions with human behavior offers valuable insights into AI-human interaction in moral contexts.
Keywords:
Artificial Intelligence (AI)
GPT-3.5-turbo
altruistic behavior
moral decision-making
behavioral economics
AI-human interaction
altruism in AI
Journal
T
IF:
0.1
Papers:
86
Citations:
165