Simulations of Science for Society (S3)
S3 is designed to transform how donors and global organizations understand, evaluate, and shape the future of science. With the use of advanced AI models and network-based simulations, S3 helps to reveal how medical, health, environmental, and biological research evolves—and how strategic investments can accelerate scientific and societal progress. The project is funded by the Novo Nordisk Foundation (NNF).
The project is carried out in collaboration with the University of Chicago and Indiana University. At the Center for Social Data Science (SODAS), University of Copenhagen and at the Pioneer Centre for Artificial Intelligence, the project is led by Professor Roberta Sinatra.

S3 aims to build an AI- and network-based system that will give a comprehensive, predictive view of the global scientific landscape.
This includes the ability to:
- assess the scientific and societal impacts of past and current scientific investments,
- simulate the consequences of potential future funding decisions, and
- create a dynamic “digital double” of global science, a living model that shows how scientific ideas, collaborations, and breakthroughs progress over time.
The aim is to gain the situational awareness needed to lead and shape scientific and technological progress, particularly in health, environmental, and biological sciences.
- How can we build an integrated, data-driven system that predicts the scientific and societal impacts of research investments across time?
- How does global science evolve, especially in health, environmental, and biological domains—and where are the emerging gaps, connections, and high-impact opportunities?
- How can AI- and network-based “digital doubles” map scientific content, context, and collaborations to identify prescient, disruptive, or transformative directions in science and technology?
- How can simulations of funding decisions help research organizations understand causal effects, trade-offs, and strategic opportunities for shaping future scientific and societal outcomes?
Within S3, the SODAS team focuses on bias in scientific data and evaluation. Scientific information like publications, collaborations, and research indicators, is never completely neutral. It often carries subtle biases related to gender, nationality, and other factors. These biases can shape who gets recognized, who receives funding, and who has access to opportunities in science.
Our goal is to identify, measure, and reduce these biases, ensuring that the project’s recommendations promote fairness, equity, and aligns with the values of the NNF.
- Professor James Evans: PI, University of Chicago
- Professor Roberta Sinatra: Co-PI, University of Copenhagen
- Professor Santos Fortunato: Co-PI, Indiana University
- Jacob Aarup Dalsgaard: PhD student, University of Copenhagen
