Three Lessons from Citizen-Centric Participatory AI Design

Fuente: arXiv
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Main Authors: Schneiders, Eike, Kiden, Sarah, Zhang, Beining, Arcanjo, Bruno Rafael Queiros, Li, Zhaoxing, Periyathambi, Ezhilarasi, Yazdanpanah, Vahid, Stein, Sebastian
Format: Preprint
Published: 2026
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author Schneiders, Eike
Kiden, Sarah
Zhang, Beining
Arcanjo, Bruno Rafael Queiros
Li, Zhaoxing
Periyathambi, Ezhilarasi
Yazdanpanah, Vahid
Stein, Sebastian
author_facet Schneiders, Eike
Kiden, Sarah
Zhang, Beining
Arcanjo, Bruno Rafael Queiros
Li, Zhaoxing
Periyathambi, Ezhilarasi
Yazdanpanah, Vahid
Stein, Sebastian
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2602_08554
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Three Lessons from Citizen-Centric Participatory AI Design
Schneiders, Eike
Kiden, Sarah
Zhang, Beining
Arcanjo, Bruno Rafael Queiros
Li, Zhaoxing
Periyathambi, Ezhilarasi
Yazdanpanah, Vahid
Stein, Sebastian
Computers and Society
Human-Computer Interaction
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.
title Three Lessons from Citizen-Centric Participatory AI Design
topic Computers and Society
Human-Computer Interaction
url https://arxiv.org/abs/2602.08554