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UX Design Innovation: Challenges for Working with Machine Learning as a Design Material

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  • Graham Dove
  • ,
  • Kim Halskov
  • Jodi Forlizzi, Carnegie Mellon University, United States
  • John Zimmerman, Carnegie Mellon University, United States
Machine learning (ML) is now a fairly established technology, and user experience (UX) designers appear regularly to integrate ML services in new apps, devices, and systems. Interestingly, this technology has not experienced a wealth of design innovation that other technologies have, and this might be because it is a new and difficult design material. To better understand why we have witnessed little design innovation, we conducted a survey of current UX practitioners with regards to how new ML services are envisioned and developed in UX practice. Our survey probed on how ML may or may not have been a part of their UX design education, on how they work to create new things with developers, and on the challenges they have faced working with this material. We use the findings from this survey and our review of related literature to present a series of challenges for UX and interaction design research and education. Finally, we discuss areas where new research and new curriculum might help our community unlock the power of design thinking to re-imagine what ML might be and might do.
Original languageEnglish
Title of host publicationCHI '17 : Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
EditorsGloria Mark, Susan Fussell
Number of pages12
PublisherAssociation for Computing Machinery
Publication year2017
ISBN (print)978-1-4503-4655-9
Publication statusPublished - 2017
Event2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017 - Denver, United States
Duration: 6 May 201711 May 2017


Conference2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017
LandUnited States

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