Mohammed Abukalam

LLMs and Personalities: Inconsistencies Across Scales

Tosato Tommaso

Mahmood Hegazy

This study investigates the application of human psychometric assessments to large language models (LLMs) to examine their consistency and m… (see more)alleability in exhibiting personality traits. We administered the Big Five Inventory (BFI) and the Eysenck Personality Questionnaire-Revised (EPQ-R) to various LLMs across different model sizes and persona prompts. Our results reveal substantial variability in responses due to question order shuffling, challenging the notion of a stable LLM "personality." Larger models demonstrated more consistent responses, while persona prompts significantly influenced trait scores. Notably, the assistant persona led to more predictable scaling, with larger models exhibiting more socially desirable and less variable traits. In contrast, non-conventional personas displayed unpredictable behaviors, sometimes extending personality trait scores beyond the typical human range. These findings have important implications for understanding LLM behavior under different conditions and reflect on the consequences of scaling.

2024-10-09

NeurIPS.cc/2024/Workshop/Behavioral_ML (oral)

openreview.net

LLMs and Personalities: Inconsistencies Across Scales

Tosato Tommaso

Mahmood Hegazy

This study investigates the application of human psychometric assessments to large language models (LLMs) to examine their consistency and m… (see more)alleability in exhibiting personality traits. We administered the Big Five Inventory (BFI) and the Eysenck Personality Questionnaire-Revised (EPQ-R) to various LLMs across different model sizes and persona prompts. Our results reveal substantial variability in responses due to question order shuffling, challenging the notion of a stable LLM "personality." Larger models demonstrated more consistent responses, while persona prompts significantly influenced trait scores. Notably, the assistant persona led to more predictable scaling, with larger models exhibiting more socially desirable and less variable traits. In contrast, non-conventional personas displayed unpredictable behaviors, sometimes extending personality trait scores beyond the typical human range. These findings have important implications for understanding LLM behavior under different conditions and reflect on the consequences of scaling.

2024-10-09

NeurIPS.cc/2024/Workshop/Behavioral_ML (oral)

openreview.net