Collective intelligence as infrastructure for reducing broad global catastrophic risks

Abstract

Academic and philanthropic communities have grown increasingly concerned with global catastrophic risks (GCRs), including artificial intelligence safety, pandemics, biosecurity, and nuclear war. Outcomes of many risk situations hinge on the performance of human groups, such as whether democratic governments and scientific communities can work effectively. We propose to think about these issues as Collective Intelligence (CI) problems — of how to process distributed information effectively. CI is a transdisciplinary perspective, whose application involves humans and animal groups, markets, robotic swarms, collections of neurons, and other distributed systems. In this article, we argue that improving CI can improve general resilience against a wide variety of risks. Given the priority of GCR mitigation, CI research can benefit from developing concrete, practical applications to global risks. GCR researchers can benefit from engaging more with behavioral sciences. Behavioral researchers can benefit from recognizing an opportunity to impact critical social issues by engaging with these transdisciplinary efforts.