This web event will discuss how the DoD workforce could apply the use AI in System Safety Engineering (AI SS). Some topics include:
- AI SS I Course Objectives
- Relationships among the concepts and processes of Systems Engineering and System Safety Engineering, and Software Safety Engineering, and AI System Safety (AI-SS).
- How System of Systems and System Safety Engineering, including Software Safety, flow down to encompass AI SS.
- How System Safety Engineering and Software Safety Engineering concepts and processes will apply throughout all phases of the acquisition processes as described in the Adaptive Acquisition Framework
- Top three new activities in AI SS
- Current System Safety Hazard Analyses and new AI hazard analysis
- AI SS I Course follow on expectations
- Hazard Analysis for Machine Learning Data Sets
Who Should Attend:
DoD Acquisition and Engineering professionals
Mr. R. Chris DeLuca (U.S. Army Colonel, Ret.), Director of Specialty Engineering at the Office of Undersecretary of Defense (Research and Engineering), Systems Engineering and Architecture.
Mr. DeLuca has more than 35 years of experience in the Department of Defense as a U.S. Army Colonel (R) and DoD GS-15/NH-IV Civilian, Level III qualified in Program Management, Systems Engineering, and Test and Evaluation. As a U.S. Army commissioned officer, he was in combat arms and acquisition, holding multiple command, leadership, and staff positions including unit command, Army Program Acquisition Management Charters for Major (MDAP), and Non-Major (including rapid equipping and provisioning) Defense Acquisition Programs, and served on the Army Staff.
Proposing the Use of Hazard Analysis for Machine Learning Data Sets
Mr. Jason Rupert, Senior Airworthiness Engineer, Modern Technology Solutions, Inc.
Mr. Rupert began his career with Unmanned aircraft systems (UAS) over 20-yrs ago by performing flight test support at Fort Huachuca. That initial exposure was not enough so he carried on by providing UAS 6-DOF development and analysis, as well as supporting exploratory RDT&E efforts. In 2006 he was lucky enough to support an RDT&E effort that was examining the effectiveness of intelligent agents being applied to existing UAS. He had a small career detour in 2007 that allowed him to run 6-DOFs and perform statistical analysis on volumes of Hellfire Stockpile Reliability data to determine hit and kill effectiveness, but quickly return to UAS in 2011. His return to UAS was in an assurance role, where he served as a software airworthiness functional for a decade on Army UAS for the Army Airworthiness Authority. In 2021, Mr. Rupert began his work on AI/ML certification, especially the possibility of certifying/qualifying AI/ML for use on flight safety critical applications. In that role he has collaborated with colleagues from all branches and various communities of practice, e.g., SAE G-34 and Safety.
Moderator: Dr. Robert E. Raygan, DAU Professor of Engineering Management / NDIA Systems Engineering Division Education & Training Committee Chair
References for Deeper Learning:
· DAU Courses / Links
· Professional Organizations