Cited by 88Innovative Human-Technology InteractionUsability and User Interface DesignEthics and Social Impacts of AI

Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains

Zytko, Douglas, J. Wisniewski, Pamela, Guha, Shion, P. S. Baumer, Eric, Lee, Min Kyung·2022·CHI Conference on Human Factors in Computing Systems Extended Abstracts

Abstract

Participatory design (PD) for Artificially Intelligent (AI) systems has gained in popularity in recent years across multiple application domains, both within the private and public sectors. PD methods broadly enable stakeholders of diverse backgrounds to inform new use cases for AI and the design of AI-based technologies that directly impact people's lives. Such participation can be vital for mitigating adverse implications of AI on society that are becoming increasingly apparent and pursuing more positive impact, especially to vulnerable populations. This panel brings together researchers who have, or are, conducting participatory design of AI systems across diverse subject areas. The goal of the panel is to elucidate similarities and differences, as well as successes and challenges, in how PD methods can be applied to Artificially Intelligent systems in practical and meaningful ways. The panel serves as an opportunity for the HCI research community to collectively reflect on opportunities for PD of AI to facilitate collaboration amongst stakeholders, as well as persistent challenges to participatory AI design.

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Registry

Crossref · 10.1145/3491101.3516506

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  • HCI scholarship has a distinctive role in translating abstract principles into concrete, citizen-centred practices by offering insights into participatory design methods for AI systems and policy, tools to facilitate stakeholder engagement, and socio-technical evaluation.

    “HCI scholarship has a distinctive role here: by offering established insights into participatory design methods for AI systems and policy [87, 103, 183], tools to facilitate stakeholder engagement [97], and socio-technical evaluation [12, 110, 131], it helps translate abstract principles into concrete, citizen-centred practices.”

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Authors
Zytko, D., J. Wisniewski, P., Guha, S., P. S. Baumer, E., & Lee, M. K.
Affiliations
  • Oakland University (US)
  • Department of Computer Science, University of Central Florida, United States
  • University of Toronto (CA)
  • Computer Science & Engineering, Lehigh University, United States
  • The University of Texas at Austin (US)
Venue
CHI Conference on Human Factors in Computing Systems Extended Abstracts
Publisher
ACM
Published
2022-04-27
Pages
1-4
OpenAlex
W4225134894
Cited by
88
References
4
Citations by year
2026: 31 · 2025: 15 · 2024: 28 · 2023: 11 · 2022: 3
FWCI
11.40
Type
conference paper
Language
en
Open access
closed
Locations
CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
  • Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
participatory design, artificial intelligence systems, stakeholder engagement, vulnerable populations, societal impact of AI, stakeholder collaboration, design challenges, human-AI interaction

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