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2020 | OriginalPaper | Buchkapitel

Gender Bias in Chatbot Design

verfasst von : Jasper Feine, Ulrich Gnewuch, Stefan Morana, Alexander Maedche

Erschienen in: Chatbot Research and Design

Verlag: Springer International Publishing

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Abstract

A recent UNESCO report reveals that most popular voice-based conversational agents are designed to be female. In addition, it outlines the potentially harmful effects this can have on society. However, the report focuses primarily on voice-based conversational agents and the analysis did not include chatbots (i.e., text-based conversational agents). Since chatbots can also be gendered in their design, we used an automated gender analysis approach to investigate three gender-specific cues in the design of 1,375 chatbots listed on the platform chatbots.org. We leveraged two gender APIs to identify the gender of the name, a face recognition API to identify the gender of the avatar, and a text mining approach to analyze gender-specific pronouns in the chatbot’s description. Our results suggest that gender-specific cues are commonly used in the design of chatbots and that most chatbots are – explicitly or implicitly – designed to convey a specific gender. More specifically, most of the chatbots have female names, female-looking avatars, and are described as female chatbots. This is particularly evident in three application domains (i.e., branded conversations, customer service, and sales). Therefore, we find evidence that there is a tendency to prefer one gender (i.e., female) over another (i.e., male). Thus, we argue that there is a gender bias in the design of chatbots in the wild. Based on these findings, we formulate propositions as a starting point for future discussions and research to mitigate the gender bias in the design of chatbots.

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Metadaten
Titel
Gender Bias in Chatbot Design
verfasst von
Jasper Feine
Ulrich Gnewuch
Stefan Morana
Alexander Maedche
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-39540-7_6

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