Three Lessons from Citizen-Centric Participatory AI Design

TL;DR

This workshop paper investigates challenges in citizen-centric AI design using three 2025 participatory workshops with diverse publics. It employs constructive design methods—storytelling and lo-fi prototyping—to surface visions and potential community impacts, followed by a third workshop that assesses feasibility with cross-sector experts. The authors identify three core challenges: sustaining long-term public engagement, achieving a shared language between experts and lay participants, and translating speculative input into implementable systems, proposing iterative, reflexive pathways to bridge ideas with technical and ethical constraints. The work advocates long-term, participatory practices as essential for responsible and actionable citizen-centric AI development, with practical implications for governance, literacy, and design pipelines.

Abstract

This workshop paper examines challenges in designing agentic AI systems from a citizen-centric perspective. Drawing on three participatory workshops conducted in 2025 with members of the general public and cross-sector stakeholders, we explore how societal values and expectations shape visions of future AI agents. Using constructive design research methods, participants engaged in storytelling and lo-fi prototyping to reflect on potential community impacts. We identify three key challenges: enabling meaningful and sustained public engagement, establishing a shared language between experts and lay participants, and translating speculative participant input into implementable systems. We argue that reflexive, long-term participation is essential for responsible and actionable citizen-centric AI development.