Co-designing AI systems with value-sensitive citizen science
Bibliographic Data
| ID | 21110847 |
|---|---|
| Authors | Sachit Mahajan (0000-0001-9558-8895, ETH Zurich, corresponding author), D Helbing (0000-0002-9898-0101, ETH Zurich) |
| Year | 2026 |
| Volume | 41 |
| Issue | 8 |
| Pages | 7267-7282 |
| Publication date | 2026-07-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AI & Society (JOURNAL) |
| Journal identifiers | ISSN: 0951-5666 • E-ISSN: 1435-5655 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s00146-026-03174-8 |
| OpenAlex | W4410117633 |
| Language | EN |
| Citations received | 1 |
| References cited | 53 |
As AI systems increasingly influence everyday life, integrating diverse community values is both ethically essential and practically urgent. This paper presents Value-Sensitive Citizen Science (VSCS)—a systematic framework that combines Value-Sensitive Design (VSD) with citizen science to support meaningful public participation in AI development. VSCS addresses gaps in the existing approaches by integrating culturally grounded methods and cognitive scaffolding through the Participatory Value-Cognition Taxonomy (PVCT). Community members engage as co-researchers through iterative cycles guided by extended scenario reasoning (What-if, If-then, Then-what, What-now), translating local values into actionable technical requirements. The framework also embeds governance mechanisms to ensure adaptability, accountability, and ongoing oversight throughout the AI lifecycle. By bridging participatory design with algorithmic accountability, VSCS challenges monocultural and top–down approaches to AI. We discuss practical implications, including power asymmetries, scalability, and epistemic justice, and propose strategies for policymakers and practitioners seeking to advance inclusive, value-driven AI design across diverse sociotechnical contexts
Citizen science · Machine learning · Physics · Political science · Value (mathematics) · Big Data and Business Intelligence · Computer Science · Scientific Computing and Data Management · Species Distribution and Climate Change
Political Liberalism
Value Sensitive Design
Design Justice
Fairness and Abstraction in Sociotechnical Systems
A review of citizen science and community-based environmental monitoring
Globally networked risks and how to respond
Tokenism or Political Activism? Some Reflections on Participatory Planning
Citizen Science and Volunteered Geographic Information
From Conservation to Crowdsourcing
AI4People—An Ethical Framework for a Good AI Society
Democracy by Design
Creating Capabilities
The democratization dilemma
From Do-It-Yourself (DIY) to Do-It-Together (DIT)
Can citizen science enhance public understanding of science
Hybrid collective intelligence in a human–AI society
Glocalization
Ethical Community-Engaged Research
Leveraging the collaborative power of AI and citizen science for sustainable development
Infrastructuring and the formation of publics in participatory design
The making of AI society
Values Levers
Just good enough data
A Revision of Bloom's Taxonomy
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |