Can ChatGPT Assess Human Personalities? A General Evaluation Framework
- URL: http://arxiv.org/abs/2303.01248v3
- Date: Fri, 13 Oct 2023 15:53:00 GMT
- Title: Can ChatGPT Assess Human Personalities? A General Evaluation Framework
- Authors: Haocong Rao, Cyril Leung, Chunyan Miao
- Abstract summary: Large Language Models (LLMs) have produced impressive results in various areas, but their potential human-like psychology is still largely unexplored.
This paper presents a generic evaluation framework for LLMs to assess human personalities based on Myers Briggs Type Indicator (MBTI) tests.
- Score: 70.90142717649785
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Large Language Models (LLMs) especially ChatGPT have produced impressive
results in various areas, but their potential human-like psychology is still
largely unexplored. Existing works study the virtual personalities of LLMs but
rarely explore the possibility of analyzing human personalities via LLMs. This
paper presents a generic evaluation framework for LLMs to assess human
personalities based on Myers Briggs Type Indicator (MBTI) tests. Specifically,
we first devise unbiased prompts by randomly permuting options in MBTI
questions and adopt the average testing result to encourage more impartial
answer generation. Then, we propose to replace the subject in question
statements to enable flexible queries and assessments on different subjects
from LLMs. Finally, we re-formulate the question instructions in a manner of
correctness evaluation to facilitate LLMs to generate clearer responses. The
proposed framework enables LLMs to flexibly assess personalities of different
groups of people. We further propose three evaluation metrics to measure the
consistency, robustness, and fairness of assessment results from
state-of-the-art LLMs including ChatGPT and GPT-4. Our experiments reveal
ChatGPT's ability to assess human personalities, and the average results
demonstrate that it can achieve more consistent and fairer assessments in spite
of lower robustness against prompt biases compared with InstructGPT.
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