Anja Thieme, Cynthia L. Bennett, Cecily Morrison, Edward Cutrell and Alex Taylor (2018) “I can do everything but see!” – How People with Vision Impairments Negotiate their Abilities in Social Contexts. In Proceedings CHI ’18. ACM Press.
Ari Schlesinger, Kenton O’Hara and Alex Taylor (2018) Lets Talk about Race: Identity, Chatbots, and AI. In Proceedings CHI ’18. ACM Press.
Very happy to have contributed to two papers being presented at the upcoming CHI conference this year. One reports on work with the blind and vision impaired a few of us have been involved in different ways (see here). Broadly, we’ve used the piece to reflect on the relations between vision impairment and artificial intelligence, and set out directions for a possible design space.
The second paper picks up on a new theme for me, but one closely related to past reflections and design work around machine intelligence. With the fantastic Ari Schlesinger (GA Tech) leading the research, we examine the challenges faced in handling race talk (and racism) in human-bot interactions. Taking both Tai AI and the blacklist as starting points, we take seriously the computational underpinnings of chat bots and conversational agents, to underscore the role they have in sustaining troubling racial categories and the conditions they make possible for more just and equitable ways forward.
Abstract — This research takes an orientation to visual impairment (VI) that does not regard it as fixed or determined alone in or through the body. Instead, we consider (dis)ability as produced through interactions with the environment and configured by the people and technology within it. Specifically, we explore how abilities become negotiated through video ethnography with six VI athletes and spectators during the Rio 2016 Paralympics. We use generated in-depth examples to identify how technology can be a meaningful part of ability negotiations, emphasizing how these embed into the social interactions and lives of people with VI. In contrast to treating technology as a solution to a ‘sensory deficit’, we understand it to support the triangulation process of sense-making through provision of appropriate additional information. Further, we suggest that technology should not try and replace human assistance, but instead enable people with VI to better identify and interact with other people in-situ.
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?