Cited by 391Innovative Human-Technology InteractionUsability and User Interface DesignDesign Education and Practice

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

Dove, Graham, Halskov, Kim, Forlizzi, Jodi, Zimmerman, John·2017·Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

Abstract

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.

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Crossref · 10.1145/3025453.3025739

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References 56 · Cited by 391

Authors
Dove, G., Halskov, K., Forlizzi, J., & Zimmerman, J.
Affiliations
  • Aarhus University (DK)
  • Carnegie Mellon University (US)
Venue
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2017-05-02
Pages
278-288
OpenAlex
W2611748211
Cited by
391
References
56
Citations by year
2026: 35 · 2025: 40 · 2024: 57 · 2023: 53 · 2022: 44 · 2021: 64 · 2020: 38 · 2019: 30 · 2018: 29 · 2017: 1
FWCI
20.26
Type
conference paper
Language
en
Open access
closed
Locations
CHI Conference on Human Factors in Computing Systems (publishedVersion)
Funders
The Danish Innovation Foundation (1311-00001B)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
  • Physical Sciences › Engineering › Mechanical Engineering › Design Education and Practice
Keywords
machine learning, user experience design, design innovation, UX practitioners, human-machine collaboration, design challenges, design thinking, interaction design, curriculum development

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