Scalable Information Fusion Trust

Key concerns for the deployment of information fusion systems is conformance to standards, methods for certifiability, and assessment of machine techniques to enhance human situation awareness. Two key elements of recent interest are methods to explore scalability and whether systems can be trusted. This paper explores the metrics from trust towards that of scalable information fusion systems designs. Building on experience from human testing with information fusion products, designing training material, providing checklists for fusion products, and feedback from operators; the paper explores methods of information fusion trust and scalability from extensible graphical information fusion techniques. The adapted results indicate a positive correlation between scalability (i.e., data prioritization) and trust (i.e., human attention) from data fusion support to user task analysis.