Grand Challenges for the Convergence of Computational and Citizen Science Research Workshop Report

This report is an outcome of a Computing Community Consortium (CCC) visioning workshop on Grand Challenges for the Convergence of Computational and Citizen Science Research conducted on April 8-9, 2025, in Washington, D.C. as well as through several precursor virtual input-gathering sessions. These events brought together experts across relevant disciplines to develop a research agenda that brings to fruition the above vision on how humans and machines may team up to solve some of the world's most pressing scientific problems. Citizen science delivers measurable economic and national value. Public participation in scientific research generates millions of dollars in volunteer labor value, extends government agency capacity, and directly supports federal priorities in areas such as disaster management, public health, water, energy, workforce development, and many more. At the same time, 21st-century scientific infrastructure requirements for citizen science (from hardware and cyberinfrastructure to data and computational frameworks) mirror those for computational science more generally. The distributed, collaborative, long-term, and contextual nature of citizen science makes it a demanding real-world use case for a novel robust research infrastructure that accounts for security, privacy, resource adaptability, and transparency. In this report, we outline the key findings, future research directions, and recommendations that emerged from the April 2025 CCC Grand Challenges for the Convergence of Computational and Citizen Science Research Workshop.

New Studies: How Commercial Forces Make Science Less Reliable

Computational social science has been distorted by commercial forces, and AI is making it worse.

Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Request PDF

Request PDF | On Jan 1, 2013, Jessica McCallum Breen and others published Civic, Citizen and Grassroots Science: Towards a Transformative Scientific Research Model | Find, read and cite all the research you need on ResearchGate

LIMITS 2025 -- Workshop on Computing within Limits

The LIMITS workshop concerns the role of computing in human societies situated in a world of limits, such as limits of extractive logics, limits to a biosphere’s ability to recover, limits to our knowledge, or limits to technological solutions to societal issues. As an interdisciplinary group of researchers, practitioners, and scholars, we seek to reshape the computing research agenda, grounded by an awareness that contemporary computing research is intertwined with ecological limits in general, and climate- and climate justice-related limits in particular. LIMITS 2025 solicits submissions that move us closer towards computing that supports diverse human and non-human lifeforms and thriving biospheres.

LIMITS 2026 -- Workshop on Computing within Limits

LIMITS concerns the role of computing in human societies situated in a world of planetary boundaries and limits, such as limits of extractive logics, limits to a biosphere’s ability to recover, limits to our knowledge, or limits of technological solutions to societal issues. As an interdisciplinary group of researchers, practitioners, and scholars, we seek to reshape and orient the broader computing research agenda, grounded by an awareness that contemporary computing research is embedded in finite socio-ecological conditions and must reckon with with ecological limits in general, and climate- and climate justice-related limits in particular. LIMITS 2026 solicits submissions that move us closer towards computing that supports ecological and just futures for diverse human and non-human lifeforms and thriving biospheres.

Field Theory: AI as Social Science Question, Object & Tool

Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.

AI is turning research into a scientific monoculture

Generative AI deserves scientific attention. But the rush to study it is producing a feedback loop of topical and methodological convergence, flattening scientific imagination and crowding out the pluralism needed to keep research adaptive, resilient, and intellectually generative.

The Citizen Lab - The Citizen Lab

The Citizen Lab is an interdisciplinary research unit at the Munk School of Global Affairs & Public Policy, University of Toronto. We apply our collective expertise in the fields of law, computer science, cybersecurity, political science, and social sciences to investigate complex issues of the 21st century. Explore focus areas Get the latest research in […]

An epistemology for democratic citizen science

Abstract. More than ever, humanity relies on robust scientific knowledge of the world and our place within it. Unfortunately, our contemporary view of scie

No. 010: AutoScientists governance, AI-agent monoculture, nonsense-term retractions - The Hallway Track

The Hallway Track No. 010 - How AI is affecting the practice of science

Charting AI’s Role in Scientific Discovery — Renaissance Philanthropy – A brighter future for all through science, technology, and innovation

Renaissance Philanthropy, with support from Google.org , is conducting a landscape study of AI integration in scientific research — and we want your perspective.

SimPolitics

For more than six decades, the public has been promised that computers will revolutionize politics, both nationally and internationally. In SimPolitics, Fenw...

Governing the scholarly AI Commons – Open Future

New report explores how academic communities can shape AI governance in research and publishing, from regulation to community-led approaches.

AI as the Catalyst of the New Paradigm of Science? | Cadmus Journal

The rapid advancement of Artificial Intelligence (AI) is reshaping the landscape of scientific inquiry. This article examines the challenges confronting modern science, including knowledge fragmentation, diminishing returns of current paradigms, and the disconnect between science and society. It explores how AI offers solutions enhancing collaboration and integrating knowledge—as well as considers the possible “darker side” of using AI in research. However, the advent of AI in science not only enhances scientific research but also redefines the role of human researchers and fosters a new paradigm of human understanding. By embracing these transformations, a more cohesive and responsive scientific enterprise can emerge.