mlsanityData to 14 Oct 2026

Bias and Fairness in Chatbots: An Overview

arXiv 2309.08836 ↗First posted 16 Sep 2023cs.CL cs.AI cs.CYcited by 20

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Abstract (arXiv)

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.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 81 of its 224 references that are in the map. First posted on arXiv 16 Sep 2023.

Builds on

81 of 224 references.

References · 81

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Citing papers per year: 2024: 7; 2025: 12; 2026: 1.

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