The Better Angels of Machine Personality: How Personality Relates to LLM Safety

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Zhang, Jie, Liu, Dongrui, Qian, Chen, Gan, Ziyue, Liu, Yong, Qiao, Yu, Shao, Jing
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866916328199159808
author Zhang, Jie
Liu, Dongrui
Qian, Chen
Gan, Ziyue
Liu, Yong
Qiao, Yu
Shao, Jing
author_facet Zhang, Jie
Liu, Dongrui
Qian, Chen
Gan, Ziyue
Liu, Yong
Qiao, Yu
Shao, Jing
contents Personality psychologists have analyzed the relationship between personality and safety behaviors in human society. Although Large Language Models (LLMs) demonstrate personality traits, the relationship between personality traits and safety abilities in LLMs still remains a mystery. In this paper, we discover that LLMs' personality traits are closely related to their safety abilities, i.e., toxicity, privacy, and fairness, based on the reliable MBTI-M scale. Meanwhile, the safety alignment generally increases various LLMs' Extraversion, Sensing, and Judging traits. According to such findings, we can edit LLMs' personality traits and improve their safety performance, e.g., inducing personality from ISTJ to ISTP resulted in a relative improvement of approximately 43% and 10% in privacy and fairness performance, respectively. Additionally, we find that LLMs with different personality traits are differentially susceptible to jailbreak. This study pioneers the investigation of LLM safety from a personality perspective, providing new insights into LLM safety enhancement.
format Preprint
id arxiv_https___arxiv_org_abs_2407_12344
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The Better Angels of Machine Personality: How Personality Relates to LLM Safety
Zhang, Jie
Liu, Dongrui
Qian, Chen
Gan, Ziyue
Liu, Yong
Qiao, Yu
Shao, Jing
Computation and Language
Computers and Society
Personality psychologists have analyzed the relationship between personality and safety behaviors in human society. Although Large Language Models (LLMs) demonstrate personality traits, the relationship between personality traits and safety abilities in LLMs still remains a mystery. In this paper, we discover that LLMs' personality traits are closely related to their safety abilities, i.e., toxicity, privacy, and fairness, based on the reliable MBTI-M scale. Meanwhile, the safety alignment generally increases various LLMs' Extraversion, Sensing, and Judging traits. According to such findings, we can edit LLMs' personality traits and improve their safety performance, e.g., inducing personality from ISTJ to ISTP resulted in a relative improvement of approximately 43% and 10% in privacy and fairness performance, respectively. Additionally, we find that LLMs with different personality traits are differentially susceptible to jailbreak. This study pioneers the investigation of LLM safety from a personality perspective, providing new insights into LLM safety enhancement.
title The Better Angels of Machine Personality: How Personality Relates to LLM Safety
topic Computation and Language
Computers and Society
url https://arxiv.org/abs/2407.12344