Advances in information technology have provided many benefits for people with disabilities, including wide availability of textual content via text to speech, flexible control of motor wheelchairs, captioned video, and much more. People with cognitive disabilities benefit from easier communication, and better tools for scheduling and reminders. Will advances in machine learning enhance this impact? Progress in natural language processing, autonomous vehicles, and emotion detection, all driven by machine learning, may deliver important benefits soon. Further out, can we look for systems that can help people with cognitive challenges understand our complex world more easily, work more effectively, stay safe, and interact more comfortably in social situations? What are the technical barriers to overcome in pursuing these goals, and what are the theoretical developments in machine learning that may overcome them?

Clayton Lewis is Professor of Computer Science at the University of Colorado Boulder, and a visiting advisor to the DIAGRAM Center of Benetech, a Palo Alto based nonprofit organization that supports learners with disabilities. He is surveying the machine learning field for the Coleman Institute for Cognitive Disabilities, part of the University of Colorado System. Lewis has served previously as Scientist in Residence for the Coleman Institute, as Fellow of the Hanse-Wissenschaftskolleg (Delmenhorst, Germany) and as technology advisor to the director of the National Institute for Disability and Rehabilitation Research, US Department of Education. He has been honored by appointment to the ACM SIGCHI Academy, by the SIGCHI Social Impact Award, and by the Strache Leadership Award (CSUN Assistive Technology Conference).