Decision Aiding to Overcome Biases in Object Identification

Abstract

Human decision makers typically use heuristics under time-pressured situations. These heuristics can potentially degrade task performance through the impact of their associated biases. Using object identification in image analysis as the context, this paper identifies cognitive biases that play a role in decision making. We propose a decision support system to help overcome these biases in this context. Results show that the decision support system improved human decision making in object identification, including metrics such as time taken to identify targets in an image set, accuracy of target identification, accuracy of target classification, and quantity of false positive identification.

Improving Anomaly Detection Through Identification of Physiological Signatures of Unconscious Awareness

“…Due to the increase in the amount of data availability, the cognitive limit of IAs is continuously pushed to its limits, and the identification of anomalies within the military image analysis task is becoming increasingly time-critical (Fendley & Narayanan, 2012;Muller & Narayanan, 2009;Duvall, 2005;Maule, 1997). Additionally, the random and unexpected nature of certain anomalies provides an increased difficulty of timely anomaly detection (Warren, Smith, & Cybenko, 2011).…”

Development and Application of an Analyst Process Model for a Search Task Scenario

“…A DSS should be integrated with the decision process of the operator to enhance cognitive decision making capabilities (Fendley & Narayanan, 2012). The decision process model will allow identification of areas where GOST can impact and potentially improve decision making and analyst performance.…”

Utilizing functional near-infrared spectroscopy for prediction of cognitive workload in noisy work environments

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