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The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design

Authors:

Wesley H. Deng,

Ronald Velgersdijk,

Haiyi ZhuAuthors Info & Claims

FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency

Pages 440 - 451

https://doi.org/10.1145/3531146.3533110

Published: 20 June 2022 Publication History

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Abstract

There have been increasing calls for centering impacted communities – both online and offline – in the design of the AI systems that will be deployed in their communities. However, the complicated nature of a community’s goals and needs, as well as the complexity of AI’s development procedures, outputs, and potential impacts, often prevents effective participation. In this paper, we present the Model Card Authoring Toolkit, a toolkit that supports community members to understand, navigate and negotiate a spectrum of machine learning models via deliberation and pick the ones that best align with their collective values. Through a series of workshops, we conduct an empirical investigation of the initial effectiveness of our approach in two online communities – English and Dutch Wikipedia, and document how our participants collectively set the threshold for a machine learning based quality prediction system used in their communities’ content moderation applications. Our results suggest that the use of the Model Card Authoring Toolkit helps improve the understanding of the trade-offs across multiple community goals on AI design, engage community members to discuss and negotiate the trade-offs, and facilitate collective and informed decision-making in their own community contexts. Finally, we discuss the challenges for a community-centered, deliberation-driven approach for AI design as well as potential design implications.

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Cited By

Muralikumar MMcDonald D(2025)An Emerging Design Space of How Tools Support Collaborations in AI Design and DevelopmentProceedings of the ACM on Human-Computer Interaction10.1145/37011819:1(1-28)Online publication date: 10-Jan-2025
https://dl.acm.org/doi/10.1145/3701181
Kim SHo JLi YFan BYang WRamey JFox SZhu HZimmerman JEslami M(2024)Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved StakeholdersProceedings of the ACM on Human-Computer Interaction10.1145/36869058:CSCW2(1-39)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686905
Sarkar PLiem C(2024)"It's the most fair thing to do but it doesn't make any sense": Perceptions of Mathematical Fairness Notions by Hiring ProfessionalsProceedings of the ACM on Human-Computer Interaction10.1145/36373608:CSCW1(1-35)Online publication date: 26-Apr-2024
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Index Terms

The Model Card Authoring Toolkit: Toward Community-centered, Deliberation-driven AI Design
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
  2. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency

June 2022

2351 pages

ISBN:9781450393522

DOI:10.1145/3531146

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Published: 20 June 2022

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FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency

June 21 - 24, 2022

Seoul, Republic of Korea

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Cited By

Muralikumar MMcDonald D(2025)An Emerging Design Space of How Tools Support Collaborations in AI Design and DevelopmentProceedings of the ACM on Human-Computer Interaction10.1145/37011819:1(1-28)Online publication date: 10-Jan-2025
https://dl.acm.org/doi/10.1145/3701181
Kim SHo JLi YFan BYang WRamey JFox SZhu HZimmerman JEslami M(2024)Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved StakeholdersProceedings of the ACM on Human-Computer Interaction10.1145/36869058:CSCW2(1-39)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686905
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Eyuboglu SGoel KDesai AChen LMonfort MRé CZou J(2024)Model ChangeLists: Characterizing Updates to ML ModelsProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3659047(2432-2453)Online publication date: 3-Jun-2024
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