Ensuring the Safety and Security of AI Systems
• Webcast
Publisher
Software Engineering Institute
Topic or Tag
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Abstract
Artificial intelligence (AI) systems offer tremendous potential, but compared to traditional software, they introduce novel safety and security risks. System theory provides a powerful lens for understanding these risks and developing effective mitigations. In this webcast, we’ll introduce System Theoretic Process Analysis (STPA), a system-theory-based approach to safety analysis. We’ll explain how STPA helps organizations build stronger assurances about the safety and security of complex systems, including those that incorporate AI.
What Will Attendees Learn?
- How complex systems fail due to design flaws and unsafe interactions—not just component failures
- How these types of accidents can occur in AI-enabled systems
- How to apply a system-theoretic perspective, including System Theoretic Process Analysis (STPA), to analyzing AI systems
- Practical insights into improving the design, testing, and operational use of AI systems to strengthen safety and security
About the Speaker
David Schulker
David Schulker is a senior data scientist at the SEI. His current work includes projects for DoD clients focused on Large Language Model test and evaluation, statistical modeling to support zero trust implementation, and data architecture design. His past research has focused on using econometric and statistical techniques to analyze …
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