Scrofani, James W.

Multi-INT is an emerging, interdisciplinary field seeking to understand how integrating intelligence can vastly improve sensemaking, situation awareness and decision making. In an era where collection of data has outpaced the ability of technology and humans to make sense of all available information, the orthodox notion of working in, or specializing in, independent, single intelligence domains (e.g. HUMINT, SIGINT, etc.) is undergoing significant reconsideration. In fact, Multi-INT approaches employed across the intelligence process must be examined, and integrated notions of requirements generation, tasking, collection and processing must be considered. Additionally, increasing volumes and sources of information are an inescapable feature of modern intelligence and national security enterprises. Virtually all Department of Defense (DoD) and Intelligence Community (IC) organizations use data sets from disparate sources to extract information about targets such as, identity, geolocation, behavior, and patterns. In their unprocessed forms this data is simply information (e.g. measurements, sensor readings, documents, addresses, longitude and latitudes, etc.). Translating information into knowledge requires understanding macro and micro relationships between the data. Converting that knowledge into effective, actionable, intelligence necessitates drawing conclusions about these relationships in as close to real-time as possible. Over the last decade, techniques for multi-sensor data fusion have been developed using advances in fields including artificial intelligence, applied mathematics, statistical estimation, signal and image processing, and behavioral sciences. Organizations working in these arenas have gradually and independently developed a corpus of Multi-INT capabilities and expertise. However, because the work of these entities is driven by individual customers, and there is no single professional organization through which to promulgate their results, their research and development products are often difficult to compile as a cohesive body of knowledge. Thus the scope, breadth, and depth of the national Multi-INT capacity is not readily known and, therefore, not readily available to the sponsor community looking to understand where needs exist and how to prioritize investment. Multi-INT training, education, and workforce development efforts have undergone a similar evolution. Seeking to address immediate requirements, individuals and organizations have pieced together expertise through a combination of on-the-job training and enrollment in single topic courses and workshops offered in disciplines such as electrical engineering, computer science, mathematics, operations research, and physics. While these efforts help meet specific near-term demands, they do not afford development of a Multi-INT workforce that shares common insights, lexicons, and best practices. There is currently no curriculum that focuses specifically on understanding the Multi-INT problem space and/or provides a holistic approach to addressing enterprise-wide questions in this arena.
Electrical & Computer Engineering
Department of Defense Space
DoD
2016