Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities

TL;DR

Addresses ethical and practical challenges of LLM-based personas in CUIs, including bias, manipulation, and unpredictable behavior. Proposes a cross-disciplinary workshop to synthesize literature, share best practices, and develop ethical guidelines and a common vocabulary for terms such as persona, agent, and character. Describes a concrete plan with pre-workshop submissions, hands-on prototyping sessions, a keynote by an AI policy expert, and post-workshop reporting and community-building efforts. The outcome aims to produce actionable guidelines and foster ongoing collaboration to ensure transparent, inclusive, and user-centered LLM-driven CUIs aligned with societal values.

Abstract

The emergence of Large Language Models (LLMs) has revolutionized Conversational User Interfaces (CUIs), enabling more dynamic, context-aware, and human-like interactions across diverse domains, from social sciences to healthcare. However, the rapid adoption of LLM-based personas raises critical ethical and practical concerns, including bias, manipulation, and unforeseen social consequences. Unlike traditional CUIs, where personas are carefully designed with clear intent, LLM-based personas generate responses dynamically from vast datasets, making their behavior less predictable and harder to govern. This workshop aims to bridge the gap between CUI and broader AI communities by fostering a cross-disciplinary dialogue on the responsible design and evaluation of LLM-based personas. Bringing together researchers, designers, and practitioners, we will explore best practices, develop ethical guidelines, and promote frameworks that ensure transparency, inclusivity, and user-centered interactions. By addressing these challenges collaboratively, we seek to shape the future of LLM-driven CUIs in ways that align with societal values and expectations.