How does human behavior change in the presence of AI systems that interact with large groups of people at scale? And how do algorithms change in return? From OpenClaw to the Instagram algorithm, technologists, policymakers, and courts continue to ask this question – with serious implications for society.
In 2026, CAT Lab is offering a set of micro-grants that will support scholars to work alongside communities to develop scientific understanding about collective human-algorithm behavior. This project, a partnership with Global Voices, is called the “HAB” Challenge – short for “human algorithm behavior.”
Each project we’re supporting will work with historical data about people’s interactions with an algorithm that shapes the community’s collective life – such as the popularity algorithms on Reddit, bots on Wikipedia, or other automated systems. In each case, scholars will collaborate with community partners to define outcome variables and questions that matter to them before undertaking a statistical forecasting challenge.
We are grateful to the Templeton World Charity Foundation for supporting this project, and to the Wikimedia Foundation for funding some of the summer schools and students who have worked with us on it.
You can read more about the project below.
CAT Lab Posts and Announcements:
- Matias, J.N. (2026) The HAB Challenge: Tending our Human Algorithm Ecosystems. Citizens and Technology Lab.
- Tzovaras, Bastian, G. (2025) Understanding Online Communities as Ecosystems. Citizens and Technology Lab.
- Platt, E. (2025) Visualizing the Algorithm. Citizens and Technology Lab.
- CAT Lab Team (ongoing) Working with Data at CAT Lab.
Academic Research:
- Matias, J. N., & Price, M. (2025). How public involvement can improve the science of AI. Proceedings of the National Academy of Sciences, 122(48), e2421111122.
- Matias, J.N. (2023) Humans and algorithms work together- so study them together. Nature.
- Matias, J. N. (2023). Influencing recommendation algorithms to reduce the spread of unreliable news by encouraging humans to fact-check articles, in a field experiment. Scientific Reports, 13(1), 11715.
