Participatory Design of AI Systems: Opportunities and Challenges Across Diverse Users, Relationships, and Application Domains
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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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.”
From “It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism (2026) · cites this paper as [183]
Cites
Engaging older people using participatory design
Lindsay, S., Jackson, D., Schofield, G., & Olivier, P. (2012) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208570 · Cited by 323 · see citing works
Zhang, A., Boltz, A., Wang, C. W., & Lee, M. K. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501866 · Cited by 166 · see citing works
Self-citationConducting Participatory Design to Improve Algorithms in Public Services: Lessons and Challenges
Saxena, D., & Guha, S. (2020) · Companion Publication of the 2020 Conference on Computer Supported Cooperative Work and Social Computing · doi:10.1145/3406865.3418331 · Cited by 30 · see citing works
Self-citationRethinking Dating Apps as Sexual Consent Apps: A New Use Case for AI-Mediated Communication
Furlo, N., Gleason, J., Feun, K., & Zytko, D. (2021) · Companion Publication of the 2021 Conference on Computer Supported Cooperative Work and Social Computing · doi:10.1145/3462204.3481770 · Cited by 26 · see citing works
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“It’s Just a Wild, Wild West”: Harnessing Public Procurement as an AI Governance Mechanism
Hudig, A. I., Kallina, E., & Singh, J. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791968 · Cited by 3 · see citing works
- 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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