Abstract

Local news sustains democratic life by connecting citizens to community issues and fostering public deliberation. Yet the global phenomenon of Local News Desertification—the decline of trustworthy local media—has weakened civic discourse, civic knowledge, and collective belonging in local areas. Citizen-participatory journalism enables citizens to report and interpret local issues; however, conventional newsroom hierarchies and insufficient support for community participants without formal journalistic training hinder its democratic potential. This study frames that tension as a Participatory Design (PD) problem concerning power and imbalanced agency in sociotechnical news systems. Through a PD process, the study develops a citizen–AI participatory journalism model that enables citizens to democratically produce, verify, and publish local news with AI-assisted support and humans' collaborative judgment. The findings contribute a framework for Community News Resilience and a value-sensitive design approach that democratizes local information ecosystems through citizen–AI collaboration for future participatory journalism.

Keywords

citizen-participatory journalism, participatory design, value-sensitive infrastructuring, human–AI collaboration

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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Democratizing the newsroom: A participatory design approach to empower citizen-participatory journalism and civic knowledge

Local news sustains democratic life by connecting citizens to community issues and fostering public deliberation. Yet the global phenomenon of Local News Desertification—the decline of trustworthy local media—has weakened civic discourse, civic knowledge, and collective belonging in local areas. Citizen-participatory journalism enables citizens to report and interpret local issues; however, conventional newsroom hierarchies and insufficient support for community participants without formal journalistic training hinder its democratic potential. This study frames that tension as a Participatory Design (PD) problem concerning power and imbalanced agency in sociotechnical news systems. Through a PD process, the study develops a citizen–AI participatory journalism model that enables citizens to democratically produce, verify, and publish local news with AI-assisted support and humans' collaborative judgment. The findings contribute a framework for Community News Resilience and a value-sensitive design approach that democratizes local information ecosystems through citizen–AI collaboration for future participatory journalism.

 

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