Carl Bergstrom in Copenhagen: two talks in August

We are delighted to host Carl Bergstrom, Professor of Biology at the University of Washington and member of the External Faculty at the Santa Fe Institute, in Copenhagen this August.

Bergstrom’s work spans evolutionary biology, epidemiology, network science, the science of science, and the spread of misinformation. During his visit he will give two talks: one on recent research into the incentives that discourage risky science, and one on a new bachelor-level course — and accompanying book — on learning and thinking in a world of large language models.

Both talks are open to all colleagues in the area. Join us!

Talk 1 — The impediments to high-risk, high-return research

Wednesday 19 August, 14:00
Auditorium, Statens Naturhistoriske Museum
Øster Voldgade 5, Copenhagen
(a reception with refreshments will follow the talk)

Scientific researchers may be driven by curiosity, but they are constrained by the realities of the scientific ecosystems in which they operate and motivated by the incentives with which they are confronted. We can use mathematical models of the research enterprise to understand how scientific norms and institutions shape the questions we ask, the efficiency with which we work, and the discoveries we make about the world around us.

In this talk I present a trio of mathematical models aimed at revealing why scientists are reluctant to propose and conduct high-risk research. In the first vignette, we look at how peer review filters — ex ante review, as for grant proposals, and ex post review, as for completed manuscripts — shape the types of questions that researchers pursue. In the second, we develop an economic “hidden action” model to explore how the unobservability of risk and effort discourages risky research. In the third, we look at how competition for high-profile publications, prizes, and jobs can induce risk-taking behavior.

Scientific norms and institutions are not god-given; we create and maintain them. If we can understand their consequences, we have the potential to nudge them in directions better tailored to our contemporary research questions and technologies.

Talk 2 — Modern day oracles or bullshit machines: how to thrive in a ChatGPT world

Friday 21 August, 11:00
Copenhagen Center for Social Data Science (SODAS), conference room CSS 1-1-12
Øster Farimagsgade 5, Copenhagen

Large language models (LLMs) have upended education. Students and faculty alike are struggling with the pace of change. We have developed a general education course, Modern Day Oracles or Bullshit Machines, for every college freshman and high school student wanting to reflect on what it means to be human in an LLM-infused world. The course takes a collaborative learning approach to a fundamental question grounded in the humanities: how can we learn and thrive with LLMs?

In this talk, I provide an overview of the course, discuss what we have learned about teaching undergraduates to think about what it means to be a learner, scholar, and human being in a ChatGPT world, and reflect on the challenges of teaching about this rapidly evolving technology.

Course website: thebullshitmachines.com

About Carl Bergstrom

Carl Bergstrom is a Professor of Biology at the University of Washington. Broadly, his research contributions are many, ranging from how evolution encodes information in genomes to how it moves, and distorts, across online networks. Bergstrom’s many research contributions include the Eigenfactor metrics for measuring the influence of scholarly journals, foundational work on the science of science and the incentives that shape research, and models of how misinformation spreads through social media and, more recently, through generative AI. He is the co-author of the book Calling Bullshit: The Art of Skepticism in a Data-Driven World. Bergstrom is an eager science communicator and many will recognize Bergstrom from his communication effort during the COVID-19 pandemic when he gained a wide following. Trained in evolutionary biology and mathematical population genetics, he earned his B.A. from Harvard and his Ph.D. from Stanford, and his work continues to cross the boundaries between the natural and social sciences.