Three Lessons from Citizen-Centric Participatory AI Design

TL;DR

This paper discusses challenges and lessons from participatory design workshops involving the public and stakeholders to develop citizen-centric AI systems that reflect societal values and expectations.

Contribution

It introduces a participatory design approach with storytelling and prototyping to incorporate public input into AI development, emphasizing long-term engagement.

Findings

Public engagement is crucial for responsible AI design

Shared language between experts and citizens improves collaboration

Translating community input into systems remains a key challenge

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.