Carl Bergstrom

About

Carl Bergstrom is a Professor of Biology at the University of Washington and a member of the External Faculty at the Santa Fe Institute. His training is in evolutionary biology and mathematical population genetics, and he enjoys working across disciplines to integrate ideas from the natural and social sciences. His unifying research theme is the concept of information, focusing on how communication evolves and how evolution encodes information in genomes. Bergstrom uses mathematical models and computer simulations to study a wide range of problems in population biology, animal behavior, and evolutionary theory. His research efforts are concentrated in several areas, including the science of science, where he investigates how norms and institutions shape scientific knowledge and research strategies; the flow of information in biological systems, exploring how living organisms acquire, store, and use information, and the strategic aspects of communication; and the field of evolution and medicine, which seeks evolutionary explanations for human vulnerability to disease and the rapid evolution of pathogens and parasites. Bergstrom's work emphasizes the importance of information in understanding biological processes and the influence of social and scientific norms on knowledge production.

Research topics

• Computer Science
• Environmental health
• Data science
• Virology
• Medicine
• Political Science
• Artificial Intelligence
• Social Science
• Sociology
• Psychology

Selected publications

• Misinformation in and about science

  Proceedings of the National Academy of Sciences · 2021 · 370 citations

  Senior authorCorresponding

  Humans learn about the world by collectively acquiring information, filtering it, and sharing what we know. Misinformation undermines this process. The repercussions are extensive. Without reliable and accurate sources of information, we cannot hope to halt climate change, make reasoned democratic decisions, or control a global pandemic. Most analyses of misinformation focus on popular and social media, but the scientific enterprise faces a parallel set of problems-from hype and hyperbole to pub…

  DOI

• Stewardship of global collective behavior

  Proceedings of the National Academy of Sciences · 2021 · 287 citations

  Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our so…

  DOI

• Model-driven mitigation measures for reopening schools during the COVID-19 pandemic

  Proceedings of the National Academy of Sciences · 2021 · 89 citations

  Reopening schools is an urgent priority as the COVID-19 pandemic drags on. To explore the risks associated with returning to in-person learning and the value of mitigation measures, we developed stochastic, network-based models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in primary and secondary schools. We find that a number of mitigation measures, alone or in concert, may reduce risk to acceptable levels. Student cohorting, in which students are divided into tw…

  DOI

• How should the advancement of large language models affect the practice of science?

  Proceedings of the National Academy of Sciences · 2025-01-27 · 47 citations

  articleOpen access

  Large language models (LLMs) are being increasingly incorporated into scientific workflows. However, we have yet to fully grasp the implications of this integration. How should the advancement of large language models affect the practice of science? For this opinion piece, we have invited four diverse groups of scientists to reflect on this query, sharing their perspectives and engaging in debate. Schulz et al. make the argument that working with LLMs is not fundamentally different from working…

  PublisherOA PDFDOI

• Frequency and accuracy of proactive testing for COVID-19

  medRxiv (Cold Spring Harbor Laboratory) · 2020 · 36 citations

  Abstract September 5, 2020 The SARS-CoV-2 coronavirus has proven difficult to control not only because of its high transmissibility, but because those who are infected readily spread the virus before symptoms appear, and because some infected individuals, though contagious, never exhibit symptoms. Proactive testing of asymptomatic individuals is therefore a powerful, and probably necessary, tool for preventing widespread infection in many settings. This paper explores the effectiveness of altern…

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: How do publication and funding filters shape the science that we do, and how we learn from it?

  NSF · $75k · 2020–2022

• TLS: COLLABORATIVE RESEARCH: Tracking Scientific Innovation from Usage Data: Models and Tools to Support a Science of Science

  NSF · $217k · 2009–2013

• Collaborative Research: Dynamic Perspectives on Costs and Conflict in Signaling Interactions

  NSF · $230k · 2010–2015

Frequent coauthors

• Michael Lachmann

  Santa Fe Institute

  46 shared

• Jevin D. West

  44 shared

• Martin Rosvall

  27 shared

• Rustom Antia

  Emory University

  23 shared

• Théodore C. Bergstrom

  20 shared

• Kevin Gross

  North Carolina State University

  18 shared

• Tali Magidson

  University of Washington

  16 shared

• Marc Lipsitch

  13 shared

Education

• Ph.D., Evolutionary Biology

  University of California, Berkeley

  1996

• M.S., Evolutionary Biology

  University of California, Berkeley

  1992

• B.A., Zoology

  University of California, Santa Barbara

  1989

Similar researchers at University of Washington

• Julie Therioth-89
• Daniel E. Schindlerh-78
• Cecilia B. Moensh-76