Monday, September 25, 2017 (All day)

Profs. Doshi and Goodie (Psychology) received a 1-year NSF grant for computationally modeling the decision making of individuals in impending disaster areas. 

The category 4 hurricane is approaching. Should a potentially affected individual follow the official orders and evacuate, or stay in place? Millions of individuals situated in vulnerable areas face this grave question as imminent disaster threatens. Many choose to leave, whereas some do not. Those individuals who choose to stay put have ostensibly made a sub-rational decision, with serious ramifications both for themselves and for first responders and other officials charged with serving them. Yet, numerous interviews with such persons clearly convey their conviction in having made the right choice. This project will identify the variables that significantly influence the decision making of individuals in impending disaster areas, and it will contribute to our understanding of how the variables are utilized differently by different individuals. These insights will help to build new computational models of the individual’s decision making under uncertainty, in extreme situations such as hurricanes and other natural disasters. The focus disasters will be the impacts of Hurricane Harvey on the Texas coast and Hurricane Irma on Florida and Georgia. The time-sensitive nature of potentially useful data makes its collection urgent. The insights and predictions generated by this systematic data-driven investigation could have significant impact on government and society. It could augment evacuation efforts with actions on the ground that target those most likely to ignore official recommendations. Furthermore, such modeling will likely help relief-and-rescue efforts to better coordinate and provide faster relief with better precision. Outcomes from this research will be integrated into the classroom instruction of courses taught by the PIs, which will provide students with exposure to how decision-making science can have real-world impact even under the most extreme circumstances.