Cognitive biases in engineering decision making

Risk cubes, actually a 5×5 matrix, used in industry characterize particular risks in terms of the likelihood of occurrence, and the consequence of the actualized risk. Human cognitive bias research led by Daniel Kahneman and Amos Tversky exposed systematic translations of objective probability and value as judged by human subjects. An examination of industry-generated risk cube data reveals evidence of biases in the judgment of likelihood and consequence. In addition, other biases - including a `diagonal bias´ - are revealed in the risk cube data. The evidence presented could improve risk cube based risk analysis. This data has applications in other areas of engineering decisions including basic decision making under cognitive biases in decision making. Risk is used as an example due to the availability of data.