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有半个多世纪的历史。近年来，随着自然语言处理（NLP）技术的迅速发展，基于大型语言模型（LLMs）的聊天机器人备受关注。与传统聊天机器人相比，现代聊天机器人的能力更为强大，已被广泛应用于实际场景。然而，现代聊天机器人设计中存在偏见与公平性问题。由于海量训练数据、庞大的模型规模以及缺乏可解释性，缓解偏见并维护公平性面临挑战。因此，本文对聊天机器人系统中的偏见与公平性进行了全面综述。首先回顾了聊天机器人的发展历史及其分类，继而分析了偏见的来源及其在应用中的潜在危害，探讨了设计公平无偏聊天机器人系统的考量因素，最后讨论了未来的研究方向。