  This report prepared by the Montreal AI Ethics Institute provides
recommendations in response to the National Security Commission on Artificial
Intelligence (NSCAI) Key Considerations for Responsible Development and
Fielding of Artificial Intelligence document. The report centres on the idea
that Responsible AI should be made the Norm rather than an Exception. It does
so by utilizing the guiding principles of: (1) alleviating friction in existing
workflows, (2) empowering stakeholders to get buy-in, and (3) conducting an
effective translation of abstract standards into actionable engineering
practices. After providing some overarching comments on the document from the
NSCAI, the report dives into the primary contribution of an actionable
framework to help operationalize the ideas presented in the document from the
NSCAI. The framework consists of: (1) a learning, knowledge, and information
exchange (LKIE), (2) the Three Ways of Responsible AI, (3) an
empirically-driven risk-prioritization matrix, and (4) achieving the right
level of complexity. All components reinforce each other to move from
principles to practice in service of making Responsible AI the norm rather than
the exception.
