Dr Hayley Dorfman - Harvard University

Dr. Dorfman's research investigates how people decide to approach or avoid threatening information under conditions of uncertainty, and why this tendency varies across individuals and contexts. In high-threat environments, these decisions can become systematically biased, causing personnel to miss critical risk information or over-rely on prior assumptions. Her theoretical model proposes that decisions to seek or avoid threatening information reflect a trade-off between two competing drives: reducing uncertainty by gathering more information, versus reducing exposure to negative outcomes by avoiding it. A novel behavioural task tests this model, in which participants make real-time decisions about whether to seek or avoid information in threatening versus safe contexts. Using pupillometry as a physiological readout of emotional arousal, eye gaze to assess attentional dynamics, and a computational model to predict decision-making, we can precisely quantify individual differences in how people weight uncertainty against potential threat.