Chatbots have been studied for more than half a century. With the rapid development of natural language processing (NLP) technologies in recent years, chatbots using large language models (LLMs) have received much attention nowadays. Compared with traditional ones, modern chatbots are more powerful and have been used in real-world applications. There are however, bias and fairness concerns in modern chatbot design. Due to the huge amounts of training data, extremely large model sizes, and lack of interpretability, bias mitigation and fairness preservation of modern chatbots are challenging. Thus, a comprehensive overview on bias and fairness in chatbot systems is given in this paper. The history of chatbots and their categories are first reviewed. Then, bias sources and potential harms in applications are analyzed. Considerations in designing fair and unbiased chatbot systems are examined. Finally, future research directions are discussed.

翻译：聊天机器人的研究已持续半个多世纪。近年来，随着自然语言处理技术的快速发展，基于大型语言模型的聊天机器人受到了广泛关注。与传统聊天机器人相比，现代聊天机器人功能更强大，并已应用于实际场景。然而，现代聊天机器人在设计过程中存在偏见与公平性问题。由于训练数据规模庞大、模型参数量惊人且缺乏可解释性，缓解偏见和保障公平性成为现代聊天机器人的巨大挑战。为此，本文对聊天机器人系统中的偏见与公平性问题进行了全面综述。首先回顾了聊天机器人的发展历史及其分类，随后分析了应用场景中的偏见来源与潜在危害，进一步探讨了设计公平且无偏的聊天机器人系统所需考量的要素，最后讨论了未来研究方向。