Cognitive Bias in Investigations

Professor Jennifer Serne of Central Washington University will present “We Think We know What Happened.” How cognitive bias can impact accident investigations.

Registration Closes 24-Hours in Advance.

All humans are prone to unconscious biases, whether they recognize them or not.  These biases are simply natural psychological processes which have evolved to help us cope with the inherent complexity of our world.  Most of the time these mental shortcuts help us navigate our day to day experiences without overtaxing our mental capacities. However, when a detailed, accurate picture of a set of circumstances is needed, such as during an accident investigation, these biases can prevent us from seeing the whole picture and thwart our efforts at determining the true causal factors in an accident scenario. This presentation will introduce the most commonly problematic cognitive biases for investigators and discuss ways to prevent them from hindering your investigations.

Jennifer Serne is an Assistant Professor in the Safety Health Management program at Central Washington University.  She teaches classes covering Hazardous Materials Management, Fire Safety, Incident Investigation, Emergency Response, Construction and Manufacturing Safety, Safety Analysis Systems, and Ergonomics and Human Factors. Previously, she worked for 20 years in the safety industry in research safety, pharmaceutical safety, radiation safety, and emergency response and was the lead inspector of medical and research facilities using radioactive materials in Washington State. She has also been an independent fatality investigator, serving various clients in 36 states and 6 countries. She has a Masters in Safety Science from Embry Riddle Aeronautical University and is working towards her Ph.D. in Industrial and Organizational Psychology and Human Factors. Her research interests include human punitive free reporting accident information sharing systems in industry and healthcare, human behavior in emergencies, automation dependency and mode confusion, the application of accident causation models in fatality investigations, cognitive bias in accident investigations, and the attribution of blame in fatal medical mistakes, assembly occupancy fire disasters, and serious aviation accidents.