Social Sensemaking with AI: Designing an Open-ended AI Experience with a Blind Child
AI technologies are often used to aid people in performing discrete tasks with well-defined goals (e.g., recognising faces in images). Emerging technologies that provide continuous, real-time information enable more open-ended AI experiences. In partnership with a blind child, we explore the challenges and opportunities of designing human-AI interaction for a system intended to support social sensemaking. Adopting a research-through-design perspective, we reflect upon working with the uncertain capabilities of AI systems in the design of this experience. We contribute: (i) a concrete example of an open-ended AI system that enabled a blind child to extend his own capabilities; (ii) an illustration of the delta between imagined and actual use, highlighting how capabilities derive from the human-AI interaction and not the AI system alone; and (iii) a discussion of design choices to craft an ongoing human-AI interaction that addresses the challenge of uncertain outputs of AI systems.
Top- Morrison, Cecily
- Cutrell, Edward
- Grayson, Martin
- Thieme, Anja
- Taylor, Alex S.
- Roumen, Geert
- Longden, Camilla
- Tschiatschek, Sebastian
- Marques, Rita Faia
- Sellen, Abigail
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
Conference on Human Factors in Computing Systems (CHI 2021) |
Divisions |
Data Mining and Machine Learning |
Event Location |
Yokohama, Japan - virtual |
Event Type |
Conference |
Event Dates |
08.-13.05.2021 |
Series Name |
CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems |
ISSN/ISBN |
978-1-4503-8096-6 |
Publisher |
ACM |
Page Range |
396:1-396:14 |
Date |
8 May 2021 |
Official URL |
https://doi.org/10.1145/3411764.3445290 |
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