According to the World Health Organization, more than one billion people worldwide have disabilities. The field of disability studies defines disability through a social lens, which considers people disabled to the extent that society creates accessibility barriers. AI technologies offer the possibility of removing many accessibility barriers. For example, computer vision might give people who are blind a better sense of the visual world, speech recognition and translation technologies might offer real-time captioning for people who are hard of hearing, and new robotic systems might augment the capabilities of people with mobility restrictions. Considering the needs of users with disabilities can help technologists identify high-impact challenges whose solutions can advance the state of AI for all users. At the same time, ethical challenges such as inclusion, bias, privacy, error, expectation setting, simulated data, and social acceptability must be considered. In this lecture, I will define these seven challenges, provide examples of how they relate to AI for Accessibility technologies, and discuss future considerations in this space.
Meredith Ringel Morris is a Sr. Principal Researcher and Research Manager at Microsoft Research; she is also an Affiliate Professor at the University of Washington in the School of Computer Science and Engineering and in the Information School. Dr. Morris leads MSR’s Ability team, which conducts research in HCI and AI with the goal of developing innovative technologies that extend the capabilities of and enhance quality of life for people with disabilities. She is an internationally-recognized expert in Human-Computer Interaction, and has conducted foundational research in several areas including gesture design, social search, and accessibility. She has served as the general chair for ACM’s CSCW conference, and has previously served as Technical Program Chair of the CHI, CSCW, ASSETS, and Interactive Tabletops & Surfaces conferences. Dr. Morris is a past member of the TOCHI editorial board and of the CSCW and CHI steering committees. She has been recognized as one of Technology Review’s “35 under 35” for her work on collaborative web search, and was named an ACM Distinguished Scientist for her contributions to HCI research. She is the author of more than 100 peer-reviewed research articles, many of which have been recognized with best paper awards; her publications are available at http://aka.ms/merrie. Dr. Morris earned her Sc.B. in computer science from Brown University, and her M.S. and Ph.D. in computer science from Stanford University.