Building Trustworthy AI Systems: Transparency, Explainability, and Control with ISO/IEC TR 24028

Building Trustworthy AI Systems: Transparency, Explainability, and Control with ISO/IEC TR 24028
Instructor: Lyron Andrews

Learning objectives

Analyze approaches to establishing trust in AI systems through transparency, explainability, and controllability.
Evaluate engineering pitfalls, threats, and risks associated with AI systems, along with potential mitigation techniques.
Apply methods to assess and improve the availability, resiliency, reliability, accuracy, safety, security, and privacy of AI systems.
Explain the concepts of trustworthiness in AI, including explainability, transparency, and controllability, in the context of evolving global regulatory and legal environments.
Design AI systems with careful consideration of explainability, transparency, and controllability to enhance their trustworthiness.