Three Lessons from Citizen-Centric Participatory AI Design

2026-02-09

AI Summary

This study addresses the design of agentic AI systems from a citizen-centered perspective, aiming to align such systems with societal values and ensure responsible development. Through three participatory workshops conducted in 2025, the research engaged diverse stakeholders using constructive design research methods, inviting the public to explore the potential community impacts of AI agency via narrative scenarios and low-fidelity prototypes. The work identifies three core design challenges: establishing sustained public engagement mechanisms, developing a shared language between experts and citizens, and translating speculative visions into implementable systems. The findings offer both actionable pathways and theoretical grounding for advancing reflective, long-term-oriented citizen-centered AI development.

Technology Category

• Multiagent Systems: Agent/AI Theories and Architectures
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Philosophy and Ethics of AI: Artificial General Intelligence

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Search and Retrieval-Augmented AI: Agentic search

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.

Problem

• citizen-centric AI
• participatory design
• public engagement
• agentic AI systems
• constructive design research

Innovation

• participatory AI design
• citizen-centric AI
• constructive design research
• public engagement
• speculative prototyping