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Large Language Models (LLMs) especially ChatGPT have produced impressiveresults in various areas, but their potential human-like psychology is stilllargely unexplored. Existing works study the virtual personalities of LLMs butrarely explore the possibility of analyzing human personalities via LLMs. Thispaper presents a generic evaluation framework for LLMs to assess humanpersonalities based on Myers Briggs Type Indicator (MBTI) tests. Specifically,we first devise unbiased prompts by randomly permuting options in MBTIquestions and adopt the average testing result to encourage more impartialanswer generation. Then, we propose to replace the subject in questionstatements to enable flexible queries and assessments on different subjectsfrom LLMs. Finally, we re-formulate the question instructions in a manner ofcorrectness evaluation to facilitate LLMs to generate clearer responses. Theproposed framework enables LLMs to flexibly assess personalities of differentgroups of people. We further propose three evaluation metrics to measure theconsistency, robustness, and fairness of assessment results fromstate-of-the-art LLMs including ChatGPT and GPT-4. Our experiments revealChatGPT's ability to assess human personalities, and the average resultsdemonstrate that it can achieve more consistent and fairer assessments in spiteof lower robustness against prompt biases compared with InstructGPT.

Can ChatGPT Assess Human Personalities? A General Evaluation Framework