SFI welcomes Omidyar Fellow Andrés Ortiz-Muñoz, who holds a BS in mathematics and physics from the University of Texas at El Paso and is completing a PhD in biology at CalTech.
SFI welcomes Program Postdoctoral Fellow George Cantwell, who is completing his PhD in physics at the University of Michigan and recently tackled one well-known flaw in network modeling that has persisted since the 1930s, and who will be working with SFI Professor Cris Moore.
The concept of the extended phenotype provides a way to circumvent Landauer’s bound.
Forecasting ambiguity is inevitable in exponential growth processes that underlie epidemics.
COVID-19 lockdowns provide a once-in-a-lifetime opportunity to study wildlife in empty cities.
Mechanism design can aid the market in meeting extraordinary needs under unusual circumstances.
Policies for responding to pandemics should be rooted in a scientific understanding of cities.
R0 is just an average: the transmission rate varies widely, and outbreaks can be surprisingly large even when the epidemic is subcritical.
Transmission T-023: David Tuckett, Lenny Smith, Gerd Gigerenzer, and Jürgen Jost on making good decisions under uncertainty
To make good decisions under uncertainty, decision-makers must act creatively to avoid paralysis, while recognizing the possibility of failure.
https://santafe.edu/people/profile/david-krakauerTest kits cannot exponentiate at the same rate as the virus. Unless we ramp up to 500K, the curve will flatten due to artifact.
The archaeological record can teach us much about cultural resilience and how to adapt to exogenous threats.
Exercise is a complex medicine that can make seniors less susceptible to frailty, and thus to COVID-19. To help the medicine go down, we need a systematic approach to improving the one technology that we know keeps people on task.
COVID-19 is changing fundamentally the way we talk about the economy, SFI's Wendy Carlin and Sam Bowles argue in an op-ed for the Financial Times.
What happens when the instruments we use to make rigorous scientific predictions operate in ways that we cannot comprehend with natural cognition? In a recent essay published in Aeon, SFI President David Krakauer takes a philosophical deep dive into this fascinating and pressing question.
The U.S. is likely to see a near-term 24% drop in employment, 17% percent drop in wages, and 22% drop in economic activity as a result of the COVID-19 crisis according to a new study co-authored by SFI External Professor Doyne Farmer at the University of Oxford. These impacts will be very unevenly distributed, with the bottom quarter of earners at risk of a 42% loss in employment and bearing a 30% share of total wage losses. In contrast, the study estimates the top quarter of earners only risk a 7% drop in employment and an 18% share of wage losses.
There’s no free lunch when it comes to making predictions about the COVID-19 pandemic.