Can LLMs have personalities?
Evaluating Personality Traits in Large Language Models: Insights from Psychological Questionnaires
This paper explores whether large language models (LLMs) exhibit consistent personality traits by applying and adapting standard psychological questionnaires like the Big Five Inventory. Key findings reveal that LLMs demonstrate distinct and often dominant traits (e.g., high agreeableness, conscientiousness) but with variations across models and questionnaires. This is relevant to multi-agent systems because understanding LLM "personalities" can inform agent design, interaction dynamics, and potential biases in multi-agent communication. Modifying questionnaires and randomizing administration order were techniques used to minimize LLM response bias from prior exposure to the test materials during training. The variability in responses, particularly for neuroticism, highlights a need for improved consistency in assessing and interpreting these traits in LLMs.