Improving Predictive Accuracy with a Combination of Human Intuition and Mechanical Decision Aids.
This study examines the intuitive combination of human judgment and mechanical prediction under varied information conditions. As expected, mechanical prediction outperformed human intuition when based on the same information, but a combined approach was best when judges had access to relevant information not captured by the model (information asymmetry). The model was useful for differentiating between the event outcomes (improved slope), while eliminating the bias caused by base-rate neglect. Human intuition was useful for incorporating relevant information outside the scope of the model, resulting in improved slope and reduced judgment scatter. The addition of irrelevant information was detrimental to judgment accuracy, causing an increase in bias and a reduction in slope. These results provide insight into how and when combining mechanical prediction and human intuition is likely to result in improved accuracy. Copyright 1998 Academic Press.
Whitecotton
SM
School of Accountancy and Information Systems, Arizona State University
Sanders
DE
Norris
KB