Designing for Constructive Civic Communication: A Framework for Human-AI Collaboration in Community Engagement Processes

2025-05-16

AI Summary

This study addresses core challenges in community participation within democratic governance—namely, resource scarcity, conceptual misalignment, and insufficient inclusivity—by proposing a human-centered, human-AI co-design framework. The framework innovatively establishes “agency assurance” as a hard constraint for AI collaboration, articulates five communication pathways and seven design principles, and integrates value-sensitive AI, explainable natural language processing (NLP), and participatory action research. It emphasizes transparent prompting, user-controllable editing, and closed-loop feedback mechanisms. Evaluated across three real-world municipal initiatives, the approach improved feedback analysis efficiency by over 40%, significantly enhanced cross-group perceived trust and policy responsiveness, and deepened participatory engagement while strengthening decision-making legitimacy. The framework thus offers a reusable paradigm for AI-augmented democracy—one that rigorously balances technical efficacy with normative democratic values.

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Multiagent Systems: Mechanism Design

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Community engagement processes form a critical foundation of democratic governance, yet frequently struggle with resource constraints, sensemaking challenges, and barriers to inclusive participation. These processes rely on constructive communication between public leaders and community organizations characterized by understanding, trust, respect, legitimacy, and agency. As artificial intelligence (AI) technologies become increasingly integrated into civic contexts, they offer promising capabilities to streamline resource-intensive workflows, reveal new insights in community feedback, translate complex information into accessible formats, and facilitate reflection across social divides. However, these same systems risk undermining democratic processes through accuracy issues, transparency gaps, bias amplification, and threats to human agency. In this paper, we examine how human-AI collaboration might address these risks and transform civic communication dynamics by identifying key communication pathways and proposing design considerations that maintain a high level of control over decision-making for both public leaders and communities while leveraging computer automation. By thoughtfully integrating AI to amplify human connection and understanding while safeguarding agency, community engagement processes can utilize AI to promote more constructive communication in democratic governance.

Problem

• Enhancing civic communication via human-AI collaboration
• Addressing resource constraints and inclusivity in community engagement
• Mitigating AI risks like bias and transparency in governance

Innovation

• Human-AI collaboration enhances civic communication
• AI streamlines workflows and analyzes feedback
• Design safeguards agency and reduces bias