  Recent advances in artificial intelligence (AI) have lead to an explosion of
multimedia applications (e.g., computer vision (CV) and natural language
processing (NLP)) for different domains such as commercial, industrial, and
intelligence. In particular, the use of AI applications in a national security
environment is often problematic because the opaque nature of the systems leads
to an inability for a human to understand how the results came about. A
reliance on 'black boxes' to generate predictions and inform decisions is
potentially disastrous. This paper explores how the application of standards
during each stage of the development of an AI system deployed and used in a
national security environment would help enable trust. Specifically, we focus
on the standards outlined in Intelligence Community Directive 203 (Analytic
Standards) to subject machine outputs to the same rigorous standards as
analysis performed by humans.
