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

TY - GEN

T1 - UX Design Innovation

T2 - 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017

AU - Dove, Graham

AU - Halskov, Kim

AU - Forlizzi, Jodi

AU - Zimmerman, John

PY - 2017/5/2

Y1 - 2017/5/2

N2 - 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.

AB - 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.

KW - Design material

KW - Interaction design

KW - Machine learning

KW - UX practice

UR - http://www.scopus.com/inward/record.url?scp=85029144814&partnerID=8YFLogxK

U2 - 10.1145/3025453.3025739

DO - 10.1145/3025453.3025739

M3 - Article in proceedings

SN - 978-1-4503-4655-9

SP - 278

EP - 288

BT - CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems

A2 - Mark, Gloria

A2 - Fussell, Susan

PB - Association for Computing Machinery

Y2 - 6 May 2017 through 11 May 2017

ER -