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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

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Researching AI Legibility Through Design. / Lindley, Joseph; Akmal, Haider Ali; Pilling, Franziska; Coulton, Paul.

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York : ACM, 2020.

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

Harvard

Lindley, J, Akmal, HA, Pilling, F & Coulton, P 2020, Researching AI Legibility Through Design. in CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. ACM, New York, CHI 2020, 25/04/20. https://doi.org/10.1145/3313831.3376792

APA

Lindley, J., Akmal, H. A., Pilling, F., & Coulton, P. (2020). Researching AI Legibility Through Design. In CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems ACM. https://doi.org/10.1145/3313831.3376792

Vancouver

Lindley J, Akmal HA, Pilling F, Coulton P. Researching AI Legibility Through Design. In CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York: ACM. 2020 https://doi.org/10.1145/3313831.3376792

Author

Lindley, Joseph ; Akmal, Haider Ali ; Pilling, Franziska ; Coulton, Paul. / Researching AI Legibility Through Design. CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. New York : ACM, 2020.

Bibtex

@inproceedings{f98c446d9ec442149e42d2697df778f9,
title = "Researching AI Legibility Through Design",
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{\textquoteright}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.",
author = "Joseph Lindley and Akmal, {Haider Ali} and Franziska Pilling and Paul Coulton",
note = "{\textcopyright} 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 ; CHI 2020 ; Conference date: 25-04-2020 Through 30-04-2020",
year = "2020",
month = apr,
day = "25",
doi = "10.1145/3313831.3376792",
language = "English",
isbn = "9781450367080",
booktitle = "CHI '20",
publisher = "ACM",
url = "https://chi2020.acm.org/",

}

RIS

TY - GEN

T1 - Researching AI Legibility Through Design

AU - Lindley, Joseph

AU - Akmal, Haider Ali

AU - Pilling, Franziska

AU - Coulton, Paul

N1 - © 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

PY - 2020/4/25

Y1 - 2020/4/25

N2 - 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.

AB - 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.

U2 - 10.1145/3313831.3376792

DO - 10.1145/3313831.3376792

M3 - Conference contribution/Paper

SN - 9781450367080

BT - CHI '20

PB - ACM

CY - New York

T2 - CHI 2020

Y2 - 25 April 2020 through 30 April 2020

ER -