The Art of Midwifery in LLMs: Optimizing Role Personas for Large Language Models as Moral Assistants

TL;DR

This paper explores how large language models can serve as moral assistants by adopting specific personas to facilitate moral growth, emphasizing context-dependent roles and introducing the concept of 'Constructive Divergence' for better moral support.

Contribution

It proposes a novel role for LLMs as moral assistants with distinct personas, and introduces 'Constructive Divergence' to enhance moral dialogue beyond traditional alignment.

Findings

Virtue exemplar performed best overall

Guardian Angel excelled in bioethical crises for emotional support

Socratic persona elicited reflection in existential dilemmas

Abstract

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.