Systems Engineering Processes to Test AI Right (SEPTAR)

The Department of Defense (DoD) is making sizable investments (14.7 billion dollars) in Artificial Intelligence (AI) Research and Development and acquiring AI through programs [1]. Ensuring proper process execution enables these investments to be realized, especially the processes that ensure effect...

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Bibliographic Details
Main Authors: Lockett, Jim, Reeder, Florence, Chen, Ivy, Pomales, Carol, Balhana, Carlos, Moore, Danny, Ferguson, Ronald
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Best practices
Investment
Planning
Research and development
Systems Engineering
Systems engineering and theory
Test and Evaluation
US Department of Defense
Online Access:Request full text
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Summary:The Department of Defense (DoD) is making sizable investments (14.7 billion dollars) in Artificial Intelligence (AI) Research and Development and acquiring AI through programs [1]. Ensuring proper process execution enables these investments to be realized, especially the processes that ensure effective evaluation of AI-enabled systems (AIES). SEPTAR (Systems Engineering Processes to Test AI Right) presents benefits and best practices for proactive planning for Test and Evaluation (T&E) activities for AIES. By following the best practices, AIESs are more likely to be delivered on time, to meet budgetary goals, and to perform effectively for mission expectations. The three major themes of this paper are: a) Broadening the T&E continuum; b) Defining data needs for AIES up-front; and c) Evaluating the Systems Engineering Life Cycle (SELC) to inform AIES trustworthiness 1 .
ISSN:1558-4550
DOI:10.1109/AUTOTESTCON47465.2024.10697513