Emerging Practices in Participatory AI Design in Public Sector Innovation
Devansh Saxena, Zoe Kahn, Erina Seh-Young Moon, Lauren M. Chambers, Corey Jackson, Min Kyung Lee, Motahhare Eslami, Shion Guha, Sheena Erete, Lilly Irani, Deirdre Mulligan, John Zimmerman
TL;DR
The paper addresses how to advance participatory AI design in public sector innovation amid rapid government AI deployment across urban planning, security, and service delivery. It proposes a hybrid, day-long workshop to synthesize empirical PD methods, formalize core concepts, and develop practical guidance for equitable, transparent, and inclusive public-sector AI. The approach combines evaluation of existing participatory methods, definition of meaningful involvement elements and measurable outcomes, and strategies for embedding participation into procurement contracts, illustrated by case studies and design techniques from HCI and civic tech. The workshop plans include pre- and post-event activities, diverse recruitment, paper submissions via EasyChair, structured breakout sessions, and broad dissemination of findings to influence policy and practice in government AI projects.
Abstract
Local and federal agencies are rapidly adopting AI systems to augment or automate critical decisions, efficiently use resources, and improve public service delivery. AI systems are being used to support tasks associated with urban planning, security, surveillance, energy and critical infrastructure, and support decisions that directly affect citizens and their ability to access essential services. Local governments act as the governance tier closest to citizens and must play a critical role in upholding democratic values and building community trust especially as it relates to smart city initiatives that seek to transform public services through the adoption of AI. Community-centered and participatory approaches have been central for ensuring the appropriate adoption of technology; however, AI innovation introduces new challenges in this context because participatory AI design methods require more robust formulation and face higher standards for implementation in the public sector compared to the private sector. This requires us to reassess traditional methods used in this space as well as develop new resources and methods. This workshop will explore emerging practices in participatory algorithm design - or the use of public participation and community engagement - in the scoping, design, adoption, and implementation of public sector algorithms.
