Collective responses to time-critical threats

Abstract: This seminar explores network and crowds' physical, behavioral, and computational limits for solving time-critical problems. I describe several real-world episodes in which we used social networks to mobilize the masses to deter threats of unprecedented complexity. From finding red weather balloons hidden across the United States, to tracking down thieves in a global hunt, to reconstructing shredded classified documents, to disabling a harmful Artificial Intelligence, the potential of crowdsourcing is real, but so are the exploitation, sabotage, and polarization dynamics that undermine the power of crowds. Keeping our communities, organizations, and institutions safe depends on harnessing the networks and crowds' power and talent while defending themselves from their aggressors.

Bio: Dr. Manuel Cebrian is a Distinguished Researcher with the Department of Statistics at the Universidad Carlos III de Madrid, and a Fellow of the UC3M-Santander Big Data Institute. Previously, he held Principal Investigator positions with the Max Planck Society, the Massachusetts Institute of Technology, CSIRO, and the University of California at San Diego.  Cebrian’s research examines computational methods to create incentives that mobilize large groups of people to collaborate in solving major social challenges under time pressure. His current focus is on the study of collective cooperative responses to threats such as natural disasters, biological hazards, and risks from Artificial Intelligence.