Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities

TL;DR

This paper discusses the development and ethical considerations of LLM-based conversational agent personas, emphasizing responsible design, transparency, and societal impact in dynamic, human-like interactions.

Contribution

It introduces a framework for ethically designing and evaluating LLM-based personas, addressing bias, manipulation, and unpredictability in conversational agents.

Findings

Identifies key ethical challenges in LLM personas

Proposes best practices for responsible design

Highlights need for transparency and inclusivity

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.