A Turing test of whether AI chatbots are behaviorally similar to humans
成果类型：
Article
署名作者：
Mei, Qiaozhu; Xie, Yutong; Yuan, Walter; Jackson, Matthew O.
署名单位：
University of Michigan System; University of Michigan; Stanford University; The Santa Fe Institute
刊物名称：
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
ISSN/ISSBN：
0027-15420
DOI：
10.1073/pnas.2313925121
发表日期：
2024-02-27
关键词：
摘要：
We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts as if they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.