Gradual Voluntary Participation: A Framework for Participatory AI Governance in Journalism
2026-04-23 • Human-Computer Interaction
Human-Computer Interaction
AI summaryⓘ
The authors studied how journalists feel about using AI in their work and found that trust in AI depends on how much control people think they have in using it. They note that traditional ways of letting users shape technology don’t work well with AI, since AI is often hard to understand and change. To fix this, the authors propose a new method called Gradual Voluntary Participation (GVP), which encourages small, optional steps for people to get involved with AI over time, rather than one-time sessions. This approach aims to balance how AI changes work with giving people more say in how it’s used in newsrooms.
Participatory DesignAI in JournalismTrust in AIWorkplace DynamicsGradual Voluntary ParticipationStakeholder EngagementHuman-AI InteractionEpistemic BurdenOrganizational Change
Authors
Matilde Barbini, Stefano Sorrentino, Daniel Gatica-Perez
Abstract
The integration of AI into journalism challenges participatory design (PD), particularly with respect to stakeholder influence, workplace perceptions, and organizational dynamics. Traditional PD assumes that users can shape technologies, yet AI systems resist influence due to opaque data, fixed architectures, and inaccessible objectives. Through interviews with 10 journalists, we identify the perception gap, showing that trust in AI depends on perceived agency within workplace participatory workflows. Informed by these findings, we introduce the Gradual Voluntary Participation (GVP) framework in journalism and its five core principles, reconceptualizing participation as a gradual and voluntary process that can be operationalized at the newsroom level, beyond fixed workshops or one-time preference-elicitation campaigns. Addressing epistemic burdens, participatory ceilings, and performative consultations, GVP treats gradualism and voluntariness as design dimensions that shape perception, legitimacy, and ownership. Moving beyond unidimensional ladder metaphors and adopting a bidimensional matrix structure, the framework maps stakeholders across depth and scope, offering a new model for local participatory AI governance that balances technological transformation with stakeholder empowerment in rapidly evolving hybrid workplaces.