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
This paper explores emerging participatory AI design practices in the public sector, emphasizing community engagement to ensure democratic values and trust in smart city initiatives involving AI systems.
Contribution
It identifies new challenges and develops resources for participatory AI design methods tailored to the public sector's unique requirements.
Findings
Participatory AI design faces higher standards in public sector implementation.
New methods are needed for effective community engagement in AI projects.
Challenges include formulating robust participatory approaches for public sector AI.
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…
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Taxonomy
TopicsInnovative Approaches in Technology and Social Development · Smart Cities and Technologies · Innovative Human-Technology Interaction
