City Research Online

Abstract

Why is it so hard for chatbots to talk about race? This work explores how the biased contents of databases, the syntactic focus of natural language processing, and the opaque nature of deep learning algorithms cause chatbots difficulty in handling race-talk. In each of these areas, the tensions between race and chatbots create new opportunities for people and machines. By making the abstract and disparate qualities of this problem space tangible, we can develop chatbots that are more capable of handling race-talk in its many forms. Our goal is to provide the HCI community with ways to begin addressing the question, how can chatbots handle race-talk in new and improved ways?

Publication Type:	Conference or Workshop Item (Paper)
Additional Information:	© Schlesinger, Ari, O Hara, Kenton P & Taylor, Alex S.| ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record is published in Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, New York, NY: ACM Press. http://dx.doi.org/10.1145/10.1145/3173574.3173889.
Publisher Keywords:	chatbots; race; artificial intelligence
Departments:	School of Science & Technology > Computer Science > Human Computer Interaction Design

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