Effect of Shared Information on Trust and Reliance in a Demand Forecasting Task

Abstract

People have difficulty relying on forecasting systems appropriately, which can lead to huge business losses. Sharing information regarding the performance of forecasting systems may lead to more appropriate trust and reliance. This study considered imperfect forecasting systems and investigated how sharing such information influences people's trust and reliance. A simulated demand forecasting task required participants to provide an initial forecast, select and view a model forecast, and then determine their final forecast. Results showed that participants' reliance on a forecasting model strongly depended on their trust in the model, which was often inappropriate. With shared information, participants' reliance was more sensitive to changes of their trust in the model. However, when the shared information exposed instances of poor performance of the model, it diminished compliance with the selected model forecast, which undermined the accuracy of the final forecasts. These results suggest that sharing information may promote more appropriate reliance in situations in which people over trust automation, but not in situations in which people tend to under trust automation.