探讨大模型对话人格的伦理设计，防止偏见与操纵
Personas Evolved: Designing Ethical LLM-Based Conversational Agent Personalities
- 提出跨学科协作框架，规范大模型对话人格的设计
- 强调透明性与用户中心，避免不可控的社会影响
- 适合关注AI伦理与人机交互的研究者和开发者
大型语言模型（LLMs）的兴起彻底改变了对话式用户界面（CUIs），使其在社会科学、医疗健康等多个领域实现更动态、上下文感知且类人的交互。然而，大模型驱动的人格化角色快速普及，也带来了偏见、操纵及不可预见的社会后果等关键伦理与实践问题。与传统CUI中明确意图设计的人格不同，大模型生成的角色行为源于海量数据，难以预测且难于管控。本研讨会旨在弥合CUI与更广泛人工智能社区之间的差距，推动跨学科对话，探讨大模型人格负责任的设计与评估方法。通过汇聚研究者、设计师与实践者，我们将探索最佳实践，制定伦理准则，并建立确保透明性、包容性与用户中心交互的框架。通过协同应对这些挑战，我们希望塑造符合社会价值观与期望的大模型驱动型CUI未来。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。