Workshops and working groups are among the defining features of science at SFI, but the dividends sometimes follow months or years down the line.
SFI External Professor Ross Hammond and collaborators have developed a new agent-based computer model that helps policy-makers simulate multiple variations for re-opening. It can incorporate critical factors in determining how to contain COVID-19, such as variations in age, contact networks, activity patterns, and likelihood of infection.
InterPlanetary Transmissions: Stardust, a record of the proceedings of the second annual InterPlanetary Festival, has launched from the SFI Press.
Transmission T-035: Amos Golan on info-metrics for modeling and inference with complex and uncertain pandemic information
We must use a modeling approach to COVID-19 data that will yield the least biased inference and prediction.
When thinking about reopening schools, an important factor to consider is the rate of community transmission.
Human cognition and cultural norms have changed the composition of human portraits, according to a new analysis of European paintings from the 15th to the 20th century. The study, led by SFI Omidyar Fellow Helena Miton, examined "bias" in 1831 paintings by 582 unique European painters.
Our thoughts are with the many victims of disease, abuse, injustice, and exclusion. Black lives and Native lives matter. Our community of complexity researchers are aligned with all who are committed to freedom, justice, diversity, opportunity, and empiricism. We stand with those who strive to provide the most powerful ideas, methods, and tools pursuant to a civil and equitable society. We add our voice to the moment, defend freedom of expression, and offer all that we can in pursuit of a safer and fairer world.
Launched in early April, the online “Complexity of COVID-19” course is a resource for families and communities to think through the broad-reaching consequences of this pandemic in real time.
When disease modelers map the spread of viruses like the novel coronavirus, Ebola, or the flu, they traditionally treat them as isolated pathogens. Under these so-called “simple” dynamics, it’s generally accepted that the forecasted size of the affected population will be proportional to the rate of transmission. But according to former SFI postdoc Laurent Hébert-Dufresne at the University of Vermont and his co-authors Samuel Scarpino at Northeastern University, a former Omidyar Fellow, and Jean-Gabriel Young at the University of Michigan, the presence of even one more contagion in the population can dramatically shift the dynamics from simple to complex.
In the field of computer science, recent advances in machine learning have begun to produce tools that could be used to mine the vast trove of communiqués in cyberspace that hold patterns that can provide rich insights into how our minds work. An SFI working group, which met online in April, brought together psychologists and computer scientists to explore how the two fields can collaborate.
SFI Trustee Katherine Collins and ACtioN member Putnam Investments are co-hosting a Virtual Topical Meeting May 27-28 to explore how complexity science can inform sustainable investing. The meeting will bring investors together with leading climate and complexity scientists to discuss “The Complexity of Sustainability and Investing.”
On April 15, SFI hosted a flash discussion that focused on human behavior, incentives, and beliefs. The overarching message was that the financial and social fallout of the pandemic, while difficult to predict, will largely depend on actions at individual, community, and institutional levels.