Model blindness: A Framework for Understanding how Model-Based Decision Support Systems can Lead to Performance Degradation

Abstract

Model-Based Decision Support Systems (MDSS) are ubiquitous in many high-consequence domains like emergency management and military command and control. This paper proposes a framework of model-blindness imposed by MDSS via filtering relevant information and presenting irrelevant information to the decision-maker, causing performance degradation. The paper also defines novel categories of performance: model-limited, strategy-limited, and context-limited. We propose a theoretical confluence model of operator performance under model blindness and a framework to evaluate model blindness empirically. We report simulation results to demonstrate the impact of model blindness on performance and outline mitigation strategies for designers and developers of MDSS. The recommendations and insights can be used to evaluate the limitations associated with particular MDSS before implementation.