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Activity Number: 119 - Statistical Learning Applications for Autonomous Systems in Defense and National Security
Type: Topic Contributed
Date/Time: Monday, August 3, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Statistics in Defense and National Security
Abstract #313841
Title: Demystifying the Black Box: A Strategy for Testing AI-Enabled Systems
Author(s): Heather Wojton and Daniel Porter*
Companies: Institute for Defense Analyses and Institute for Defense Analyses
Keywords: AI-enabled systems; Autonomy; Test; Evaluation; Defense; National Security

The horizon of AI-enabled systems is near, but current test and evaluation practices within the Department of Defense are likely to mischaracterize performance, risk, and uncertainty. One of several key test and evaluation certification challenges will be interpolating between and extrapolating beyond our test points, especially in black-box systems. In this briefing, we present a conceptual framework to overcome these challenges, paying particular attention the role of experimental design and statistical analysis through the test and evaluation lifecycle.

Authors who are presenting talks have a * after their name.

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