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    Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems http://doi.acm.org/10.1145/3313831.3376792

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Researching AI Legibility Through Design

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date25/04/2020
Host publicationCHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Place of PublicationNew York
PublisherACM
Number of pages13
ISBN (print)9781450367080
<mark>Original language</mark>English
EventCHI 2020 - Honololu, Hawaii
Duration: 25/04/202030/04/2020
https://chi2020.acm.org/

Conference

ConferenceCHI 2020
Period25/04/2030/04/20
Internet address

Conference

ConferenceCHI 2020
Period25/04/2030/04/20
Internet address

Abstract

Everyday interactions with computers are increasingly likely to involve elements of Artificial Intelligence (AI). Encompassing a broad spectrum of technologies and applications, AI poses many challenges for HCI and design.
One such challenge is the need to make AI’s role in a given system legible to the user in a meaningful way. In this paper we employ a Research through Design (RtD) approach to explore how this might be achieved. Building on contemporary concerns and a thorough exploration of related research, our RtD process reflects on designing imagery intended to help increase AI legibility for users.
The paper makes three contributions. First, we thoroughly explore prior research in order to critically unpack the AI legibility problem space. Second, we respond with design proposals whose aim is to enhance the legibility, to users, of systems using AI. Third, we explore the role of design-led enquiry as a tool for critically exploring the intersection between HCI and AI research.

Bibliographic note

© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems http://doi.acm.org/10.1145/3313831.3376792