Exploring Persona-dependent LLM Alignment for the Moral Machine Experiment

• URL: http://arxiv.org/abs/2504.10886v1
• Date: Tue, 15 Apr 2025 05:29:51 GMT
• Title: Exploring Persona-dependent LLM Alignment for the Moral Machine Experiment
• Authors: Jiseon Kim, Jea Kwon, Luiz Felipe Vecchietti, Alice Oh, Meeyoung Cha,
• Abstract summary: This study examines the alignment between socio-driven decisions and human judgment in various contexts of the moral machine experiment.<n>We find that the moral decisions of LLMs vary substantially by persona, showing greater shifts in moral decisions for critical tasks than humans.<n>We discuss the ethical implications and risks associated with deploying these models in applications that involve moral decisions.
• Score: 23.7081830844157
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Deploying large language models (LLMs) with agency in real-world applications raises critical questions about how these models will behave. In particular, how will their decisions align with humans when faced with moral dilemmas? This study examines the alignment between LLM-driven decisions and human judgment in various contexts of the moral machine experiment, including personas reflecting different sociodemographics. We find that the moral decisions of LLMs vary substantially by persona, showing greater shifts in moral decisions for critical tasks than humans. Our data also indicate an interesting partisan sorting phenomenon, where political persona predominates the direction and degree of LLM decisions. We discuss the ethical implications and risks associated with deploying these models in applications that involve moral decisions.

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