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SIGCHI Outstanding Dissertation Award: Profiling Artificial Intelligence as a Material for User Experience Design

Published: 08 May 2021 Publication History

Abstract

HCI has become especially interested in the promises and challenges of user experience of AI, such as user acceptance, human-agent teamwork, and accessibility. Less discussed, however, is that the field of HCI routinely grapples with such challenges; across the various technologies commonly referred to as AI (e.g., predictive modeling, computer vision, NLP), what shared characteristics made human-AI interaction appeared uniquely difficult to design in the first place? Synthesizing my hands-on design and research over the past six years, in my dissertation, I worked to articulate whether, why, and how human-AI interaction appears uniquely challenging to design with established HCI methods. In this extended abstract, I first describe a human-AI interaction design framework as an answer to this question. I then discuss one critical implication of this framework: Framing data-driven AI systems as living socio-technical systems that co-evolve with their users. I analogize this reframing to the shift from desktop computing to ubiquitous computing and outline the ethnographic, design, and technological research opportunities it reveals.

References

[1]
Graham Dove, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. UX Design Innovation: Challenges for Working with Machine Learning as a Design Material. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17. ACM Press, New York, New York, USA, 278–288. https://doi.org/10.1145/3025453.3025739
[2]
Aaron Steinfeld, Leslie Bloomfield, Sarah Amick, Yun Huang, Will Odom, Qian Yang, and John Zimmerman. 2019. Increasing access to transit: localized mobile information. Journal of urban technology 26, 3 (2019), 45–64.
[3]
Qian Yang. 2019. Two Case Studies of Experience Prototyping Machine Learning Systems in the Wild. In CHI’19. https://arxiv.org/abs/1910.09137
[4]
Qian Yang. 2020. Profiling Artificial Intelligence as a Material for User Experience Design. Doctoral Dissertation. Carnegie Mellon University.
[5]
Qian Yang, Alex Scuito, John Zimmerman, Jodi Forlizzi, and Aaron Steinfeld. 2018. Investigating How Experienced UX Designers Effectively Work with Machine Learning. In Proceedings of the 2018 Designing Interactive Systems Conference (Hong Kong, China) (DIS ’18). ACM, New York, NY, USA, 585–596. https://doi.org/10.1145/3196709.3196730
[6]
Qian Yang, Aaron Steinfeld, and John Zimmerman. 2019. Unremarkable AI : Fiting Intelligent Decision Support into Critical, Clinical Decision-Making Processes. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19.
[7]
Qian Yang, Aaron Steinfeld, and John Zimmerman. 2019. Unremarkable AI : Fitting Intelligent Decision Support into Critical, Clinical Decision-Making Processes. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19.
[8]
Qian Yang, Aaron Steinfeld, and John Zimmerman. 2020. Re-examining Whether, Why, and How the UX of AI Is Uniquely Difficult to Design. In Under review for the 2020 CHI Conference on Human Factors in Computing Systems - CHI ’20.
[9]
Qian Yang, Jina Suh, Nan-Chen Chen, and Gonzalo Ramos. 2018. Grounding Interactive Machine Learning Tool Design in How Non-Experts Actually Build Models. In Proceedings of the 2018 Designing Interactive Systems Conference (Hong Kong, China) (DIS ’18). ACM, New York, NY, USA, 573–584. https://doi.org/10.1145/3196709.3196729
[10]
Qian Yang, John Zimmerman, Aaron Steinfeld, Lisa Carey, and James F. Antaki. 2016. Investigating the Heart Pump Implant Decision Process: Opportunities for Decision Support Tools to Help. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI ’16). ACM, New York, NY, USA, 4477–4488. https://doi.org/10.1145/2858036.2858373
[11]
Qian Yang, John Zimmerman, Aaron Steinfeld, and Anthony Tomasic. 2016. Planning Adaptive Mobile Experiences When Wireframing. In Proceedings of the 2016 ACM Conference on Designing Interactive Systems - DIS ’16. ACM Press, Brisbane, QLD, Australia, 565–576. https://doi.org/10.1145/2901790.2901858

Cited By

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  • (2024)DeepThInkInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2023.103139181:COnline publication date: 1-Jan-2024
  • (2024)Importance Performance Matrix Analysis for Assessing User Experience with Intelligent Voice Assistants: A Strategic EvaluationSocial Indicators Research10.1007/s11205-024-03362-3Online publication date: 4-Jun-2024
  • (2024)Artificial Intelligence in UX/UI Design: A Research Framework for Exploring the Impact of Artificial Intelligence Tools on Design QualityProceedings of Ninth International Congress on Information and Communication Technology10.1007/978-981-97-5035-1_40(511-524)Online publication date: 23-Oct-2024
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cover image ACM Conferences
CHI EA '21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems
May 2021
2965 pages
ISBN:9781450380959
DOI:10.1145/3411763
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 08 May 2021

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Author Tags

  1. User experience
  2. artificial intelligence
  3. prototyping.
  4. sketching

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Cited By

View all
  • (2024)DeepThInkInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2023.103139181:COnline publication date: 1-Jan-2024
  • (2024)Importance Performance Matrix Analysis for Assessing User Experience with Intelligent Voice Assistants: A Strategic EvaluationSocial Indicators Research10.1007/s11205-024-03362-3Online publication date: 4-Jun-2024
  • (2024)Artificial Intelligence in UX/UI Design: A Research Framework for Exploring the Impact of Artificial Intelligence Tools on Design QualityProceedings of Ninth International Congress on Information and Communication Technology10.1007/978-981-97-5035-1_40(511-524)Online publication date: 23-Oct-2024
  • (2023)Context Connection: A Product Creative Design Method for Integrating Design Materials and Design ResourcesCreativity Research Journal10.1080/10400419.2023.2207304(1-21)Online publication date: 12-May-2023

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