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Whose Values Matter in Persuasive Writing Tools?

Elmimouni, Houda; Sharma, Anasuya; Manayra, Vidushi; Chan, Man Iao; Feng, Yifan; Kyrölä, Kata; Rode, Jennifer A; (2024) Whose Values Matter in Persuasive Writing Tools? In: HttF '24: Proceedings of the Halfway to the Future Symposium. (pp. pp. 1-9). Association for Computing Machinery (ACM): New York, NY, USA. Green open access

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Abstract

We examine Microsoft’s Inclusivity Suggestions (MSIS) tool in promoting inclusive persuasive writing. In doing so, we tackle the question of how best to adapt to the plurality of humanness in technology design. Following the naturalistic use of the tool in an educational context, we conducted a qualitative investigation with nine diverse students to evaluate the tool’s capabilities and limitations. Our findings reveal that while MSIS effectively identifies explicit gender biases, it struggles with implicit biases, code-switching, and multilingual inclusivity. Participants perceived the tool as useful in raising awareness but highlighted notable differences between performative use and genuine engagement with inclusive language. Based on these insights, we argue the tool has strong biases towards an American-centered conception of diversity. Drawing on earlier work on value-sensitive design, we propose design recommendations, and more broadly we critique whether designing for universal values is entirely realistic. We call for a more international perspective on the value tensions regarding diversity embedded into technology. Content warning: racist and sexist data.

Type: Proceedings paper
Title: Whose Values Matter in Persuasive Writing Tools?
Event: HTTF '24: Halfway to the Future
ISBN-13: 9798400710421
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3686169.3686171
Publisher version: http://dx.doi.org/10.1145/3686169.3686171
Language: English
Additional information: Copyright © 2024 Owner/Author. This work is licensed under a Creative Commons Attribution International 4.0 License, https://creativecommons.org/licenses/by/4.0/.
Keywords: AI; Bias; Gender; Inclusivity; Persuasive Technology; Race; Value Sensitive Design
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Education
UCL > Provost and Vice Provost Offices > UCL SLASH
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education
UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities
UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of Arts and Humanities > Arts and Sciences (BASc)
URI: https://discovery.ucl.ac.uk/id/eprint/10199018
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