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Social sensemaking with AI: Designing an open-ended AI experience with a blind child

Morrison, C., Cutrell, E., Grayson, M. , Thieme, A., Taylor, A. ORCID: 0000-0001-6311-3967, Roumen, G., Longden, C., Tschiatschek, S., Marques, R. F. & Sellen, A. (2021). Social sensemaking with AI: Designing an open-ended AI experience with a blind child. In: CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 2021 CHI Conference on Human Factors in Computing Systems, 8-13 May 2021, Online. doi: 10.1145/3411764.3445290


AI technologies are often used to aid people in performing discrete tasks with well-defned 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 refect 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.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © the authors | ACM 2021. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record is to be published in ACM Conference on ACM CHI Conference on Human Factors in Computing Systems (, DOI:
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine
Departments: School of Science & Technology > Computer Science
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