Stanford Seminar – Exploring the implications of machine learning for cognitive disabilities
EE380: Computer Systems Colloquium Seminar
Exploring the implications of machine learning for people with cognitive disabilities
Speaker: Clayton Lewis, Benetech and University of Colorado Boulder
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?
About the Speaker:
Clayton Lewis is Professor of Computer Science and Fellow of the Institute of Cognitive Science, University of Colorado Boulder. He is visiting Palo Alto as an advisor to the DIAGRAM Center of Benetech, a Palo Alto based nonprofit organization that supports learners with disabilities, and as a consultant to the Coleman Institute for Cognitive Disabilities. This work was supported by a fellowship at the Hanse-Wissenschaftskolleg, Delmenhorst, Germany.
For more information about this seminar and its speaker, you can visit https://ee380.stanford.edu/Abstracts/…
Support for the Stanford Colloquium on Computer Systems Seminar Series provided by the Stanford Computer Forum.
Colloquium on Computer Systems Seminar Series (EE380) presents the current research in design, implementation, analysis, and use of computer systems. Topics range from integrated circuits to operating systems and programming languages.