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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.20626 |
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| _version_ | 1866917355549884416 |
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| author | Wu, Yangyi Wang, Tianqi Liu, Xilin |
| author_facet | Wu, Yangyi Wang, Tianqi Liu, Xilin |
| contents | With the development of Large Language Models (LLMs) in consulting, their role in moral decision-making has become prominent. However, existing research predominantly consider AI as an independent "moral agent" adhering to the "Human-AI Alignment" paradigm. In this study, we propose that AI should serve as a "moral assistant", facilitating users' moral growth through the "Art of Midwifery" rather than substituting human judgment. We endow LLMs with distinct persona archetypes and conducted dialogues across six moral scenarios. Findings reveal that while the virtue exemplar excelled overall, optimal performance was context-dependent: the Guardian Angel excelled in bioethical crises for emotional support, whereas the Socratic persona better elicited reflection in existential dilemmas. We introduce "Constructive Divergence", arguing that AI should offer alternative perspectives at critical moment rather than blindly accommodate users, transcending traditional alignment paradigms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_20626 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | The Art of Midwifery in LLMs: Optimizing Role Personas for Large Language Models as Moral Assistants Wu, Yangyi Wang, Tianqi Liu, Xilin Social and Information Networks With the development of Large Language Models (LLMs) in consulting, their role in moral decision-making has become prominent. However, existing research predominantly consider AI as an independent "moral agent" adhering to the "Human-AI Alignment" paradigm. In this study, we propose that AI should serve as a "moral assistant", facilitating users' moral growth through the "Art of Midwifery" rather than substituting human judgment. We endow LLMs with distinct persona archetypes and conducted dialogues across six moral scenarios. Findings reveal that while the virtue exemplar excelled overall, optimal performance was context-dependent: the Guardian Angel excelled in bioethical crises for emotional support, whereas the Socratic persona better elicited reflection in existential dilemmas. We introduce "Constructive Divergence", arguing that AI should offer alternative perspectives at critical moment rather than blindly accommodate users, transcending traditional alignment paradigms. |
| title | The Art of Midwifery in LLMs: Optimizing Role Personas for Large Language Models as Moral Assistants |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2603.20626 |