 CCC Blog In a new workshop report published by the Computing Community Consortium (CCC), Grand Challenges for the Convergence of Computational and Citizen Science Research, experts across disciplines examine the ways in which computational science — including artificial intelligence (AI) — and citizen science can mutually enrich each other, fostering increased opportunity for advancement in numerous scientific fields.
The report presents a roadmap for maximizing the potential of citizen science through the contributions of AI — and vice versa — while also demonstrating the broader applications of this union for challenges across ecological, infrastructural, clinical, and other domains. “We are entering a brave new world where we are renegotiating the relationship between humans and machines,” says Lucy Fortson (University of Minnesota), one of the report’s co-chairs. “Investing in human-machine teaming research for citizen science is investing in … accelerating scientific output.”
The report, also co-chaired by Lea Shanley (International Computer Science Institute and GNIES, University of Wisconsin-Madison) and with contributions from lead authors Tanya Berger-Wolf (The Ohio State University), Kevin Crowston (Syracuse University), Corey Jackson (University of Wisconsin-Madison), Saiph Savage (Northeastern University), and Haley Griffin (Computing Research Association), is the culmination of extensive visioning. The findings are most notably informed by discussions at the CCC Grand Challenges for the Convergence of Computational and Citizen Science Research workshop on April 8-9, 2025 in Washington, D.C., as well as two virtual roundtables on the topic. In total, 46 experts across computing research, NGOs, philanthropy, industry, and federal agencies came together to envision “how humans and machines may team up to solve some of the world’s most pressing scientific problems,” articulating specific next steps for making that future a reality.
Key Priorities and Opportunities for Growth
This report centers the immense opportunity that arises when human talent is at the core of emerging technologies. Volunteer citizen scientists are capable of data labeling, analysis, and creativity that machines are simply currently incapable of or may not have the resources to perform. Scaling these citizen science efforts would help close the gap between the sheer volume of data that computational technologies are able to produce and the data-based interpretations scientists can then apply to solving complex questions.
Five strategic priorities are identified for increasing this convergence of computational technology and citizen science:
- Create novel ways for humans and machine learning/AI to interact, enabling multi-agent teams to accelerate scientific discovery while balancing productivity, accuracy, engagement, and the education of participants.
- Craft better, more responsive feedback loops that connect volunteers, scientists, project teams, and other stakeholders in meaningful ways in order to sustain participation and ensure data reliability.
- Establish trustworthy, transparent, and reliable systems that make volunteers feel respected and included.
- Ensure the security and privacy of data, safeguarded against threats in order to strengthen credibility, improve societal uptake of results, and empower more people to contribute to research.
- Design and implement an infrastructure that can support large-scale participation and both the human and technological needs that underpin it.
Future Recommendations
These strategic priorities guide detailed recommendations for the future research directions and other actions that support the goal of large-scale convergence. They call on researchers, federal agencies, and industry professionals
- Creating a national infrastructure for convergence that establishes sustained platforms, governance systems, and the physical/cyber architecture required to support scalable, trustworthy, and nationwide convergence efforts.
- Focusing on the foundational scientific and socio-technical investigations required to advance convergence, focusing on developing new models, metrics, and frameworks for human-AI interaction, trust, and accountability.
- Developing the necessary human capital, including the skills, knowledge, and organizational structures, to create, manage, and participate in convergence projects across all sectors.
Read the Full Report
The Grand Challenges for the Convergence of Computational and Citizen Science Research report is available now on the CCC website. It provides a detailed roadmap of not only the full benefits of convergence and human-centered computing, but clear, actionable steps for making it possible.
We encourage all members of the computing community to read the full report here.
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