ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2026, Vol. 58 ›› Issue (7): 1237-1253.doi: 10.3724/SP.J.1041.2026.1237

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Personalized alignment of large language models and its impact on moral judgment

LI Chang-Jin1,2,3, JIAO Liying4, CHEN Zhen1,2,3, XU Hengbin1,2,3, WU Michael Shengtao5, XU Yan1,2,3()   

  1. 1 Faculty of Psychology, Beijing Normal University
    2 Beijing Key Laboratory of Applied Experimental Psychology
    3 National Demonstration Center for Experimental Psychology Education [Beijing Normal University], Beijing 100875, China
    4 Department of Psychology, School of Humanities and Social Sciences, Beijing Forestry University, Beijing 100083, China
    5 Department of Philosophy, School of Philosophy and Sociology, Jilin University, Changchun 130012, China
  • Published:2026-07-25 Online:2026-05-15
  • Contact: XU Yan E-mail:xuyan@bnu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(31671160);Ministry of Education of the People’s Republic of China(24YJC190012);“14th Five-Year Plan” of Beijing Education Science(BCHA25157)

Abstract:

With the advent of the era of human?machine symbiosis, the ethical dilemmas and algorithmic biases of large language models (LLMs) have sparked widespread societal concern. Consequently, guiding artificial intelligence technology toward beneficial development has emerged as a urgent and challenging imperative. This research explores the impact of personalized alignment based on the HEXACO personality model on the moral judgment of LLMs. Specifically, Study 1 examined and verified that LLMs can effectively manifest HEXACO personality traits by adhering to prompts. Study 2 explored the influence of personalized alignment on the utilitarian tendencies of LLMs, as well as the similarities and differences compared to human participants. The results indicate that personality prompts characterized by high Honesty?Humility, Agreeableness, and Conscientiousness significantly reduce the propensity of GPT-3.5, GPT-4, and ERNIE 3.5 to make utilitarian choices. Accordingly, we propose an LLM personalized alignment framework based on both the HEXACO personality model and the personality metatrait, highlighting the moral salience effect of personality dimensions within the Stability metatrait—namely, Honesty?Humility, Agreeableness, and Conscientiousness—in the personalized alignment of LLMs. This research provides a psychological foundation for the theoretical construction and technological pathways of LLM personalized alignment.

Key words: large language models, personalized alignment, moral judgment, HEXACO personality, metatrait