Beyond Compliance: Participatory AI Governance Standards Co-Designed with Affected Communities

Many papers (e.g., Ericson et al., 2025; Williamson & Prybutok, 2024) critique current governance models for privileging expert or industry perspectives over those of the public, especially marginalized groups. Responding to this, and drawing on participatory design traditions, this project would co-create new standards for AI oversight with the “end users” of AI—patients, litigants, workers, or citizens—rather than just policymakers and technical experts. Through workshops, deliberative forums, and digital platforms, it would develop governance principles, audit criteria, and oversight procedures that reflect lived experience and local values, adapting methods from participatory technology assessment and citizen science (as advocated by the anti-capitalist and pluralistic approaches in Ericson et al., 2025 and Xing et al., 2024). The result would be a set of actionable, context-sensitive governance tools that not only boost legitimacy and trust, but may also surface new risks and solutions overlooked by conventional expert-driven approaches.

References:

1. Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in AI-Driven Healthcare. Steven M. Williamson, Victor R. Prybutok (2024). Applied Sciences.
2. AI Policy for Whom? Reclaiming Governance from Capitalist Capture. Petter Ericson, Rachele Carli, Jason Tucker, Virginia Dignum (2025). Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society.
3. Critical Theories Challenge the Normative Bases of Contemporary Global Economical Governance and Help to Imagine Progressive Alternatives. Yuecong Xing, Christopher Anderson, David Ho, Guillaume Lefevre, Michelle Lavoratori (2024). Journal of World Economy.