The effect of automation and workspace design on humans' ability to recognize patterns while fusing information

Abstract

Increasingly complex contested environments force analysts to combine many different types of intelligence data to form a more cohesive picture of the environment. Information fusion systems include computers that integrate and synthesize information from multiple sources and humans who combine that information with reasoning abilities and knowledge of past events to assess situations and predict future states. The intent of this paper is to highlight the importance of understanding human cognition and decision making by presenting the hypotheses of our current research. The purpose of the future study described in this paper is to investigate how the degree of information acquisition automation used affects the human's ability to detect patterns in data that may be needed to reach higher levels of information fusion. This study will use a 2 (task type: intuitive, analytic) × 3 (amount of automation: none, half, all), between subjects experimental design. We expect to find a significant interaction between task type and amount of automation. For tasks that induce the human's intuitive system, increasing automation is expected to disrupt the human's ability to recognize patterns. However, for tasks that induce the human's analytic system, increasing automation is expected to improve the human's ability to discern patterns. The results of this research can inform guidelines for the design of common workspaces to support human-machine teaming in future information fusion systems.