Kim Halskov

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

Research output: Research - peer-reviewConference article

  • Graham Dove
    Graham Dove
  • Kim Halskov
  • Jodi Forlizzi
    Jodi ForlizziCarnegie Mellon UniversityUnited States
  • John Zimmerman
    John ZimmermanCarnegie Mellon UniversityUnited 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
JournalCHI - conference for Human-Computer Interaction
StatePublished - 2017

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