Do LLMs Possess a Personality? Making the MBTI Test an Amazing Evaluation for Large Language Models

TL;DR

This paper explores whether large language models exhibit human-like personalities by using the MBTI as an evaluation tool, analyzing their personality types, modifiability through prompts, and dataset influence.

Contribution

It introduces the novel idea of applying MBTI to assess LLM personalities and systematically investigates the effects of prompts and training data on these personalities.

Findings

LLMs can be characterized by MBTI personality types.

Prompt engineering can alter the perceived personality of LLMs.

Training datasets influence the personality traits exhibited by LLMs.

Abstract

The field of large language models (LLMs) has made significant progress, and their knowledge storage capacity is approaching that of human beings. Furthermore, advanced techniques, such as prompt learning and reinforcement learning, are being employed to address ethical concerns and hallucination problems associated with LLMs, bringing them closer to aligning with human values. This situation naturally raises the question of whether LLMs with human-like abilities possess a human-like personality? In this paper, we aim to investigate the feasibility of using the Myers-Briggs Type Indicator (MBTI), a widespread human personality assessment tool, as an evaluation metric for LLMs. Specifically, extensive experiments will be conducted to explore: 1) the personality types of different LLMs, 2) the possibility of changing the personality types by prompt engineering, and 3) How does the training dataset affect the model's personality. Although the MBTI is not a rigorous assessment, it can still reflect the similarity between LLMs and human personality. In practice, the MBTI has the potential to serve as a rough indicator. Our codes are available at https://github.com/HarderThenHarder/transformers_tasks/tree/main/LLM/llms_mbti.