Research Needs for Trusted Analytics in National Security Settings

Technical Report · Tue Sep 01 04:00:00 EDT 2020

DOI:https://doi.org/10.2172/1662023· OSTI ID:1662023

Speed, Ann ^[1]; Stracuzzi, David John ^[1]

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1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

As artificial intelligence, machine learning, and statistical modeling methods become commonplace in national security applications, the drive to create trusted analytics becomes increasingly important. The goal of this report is to identify areas of research that can provide the foundational understanding and technical prerequisites for the development and deployment of trusted analytics in national security settings. Our review of the literature covered several disjoint research communities, including computer science, statistics, human factors, and several branches of psychology and cognitive science, which tend not to interact with one another or cite each other's literatures. As a result, there exists no agreed-upon theoretical framework for understanding how various factors influence trust and no well-established empirical paradigm for studying these effects. This report therefore takes three steps. First, we define several key terms in an effort to provide a unifying language for trusted analytics and to manage the scope of the problem. Second, we outline an empirical perspective that identifies key independent, moderating, and dependent variables in assessing trusted analytics. Though not a substitute for a theoretical framework, the empirical perspective does support research and development of trusted analytics in the national security domain. Finally, we discuss several research gaps relevant to developing trusted analytics for the national security mission space.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000; NA0003525
• OSTI ID: 1662023
• Report Number(s): SAND--2020-9709R; 690597
• Country of Publication: United States
• Language: English

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