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Risk assessment is an essential part of responsible AI (RAI) development and is an increasingly common requirement in AI standards and laws such as ISO 42001 and the EU AI Act. This chalk talk provides an introduction to best practices for RAI risk assessment for generative AI applications, covering controllability, veracity, fairness, robustness, explainability, privacy and security, transparency, and governance. Explore examples to estimate the severity and likelihood of potential events that could be harmful. Learn about Amazon SageMaker tooling for model governance, bias, explainability, and monitoring, and about transparency in the form of service cards as potential risk mitigation strategies.