Join Lewis Elliott Abraham and Catherine Vu from Google Cloud as they share this presentation covering a robust risk assessment methodology for AI systems and applications, drawing upon established frameworks and standards. We will explore how to systematically identify, analyze, and mitigate potential risks across technical and operational dimensions.

At How to Assess Risk for AI with NIST and ISO Standards, our speakers will focus on the following Key Standards & Frameworks:

NIST AI Risk Management Framework (AI RMF): This framework provides a comprehensive structure for managing risks associated with AI systems, addressing trustworthiness, explainability, and fairness.
NIST Risk Management Framework (RMF): A broader framework for managing organizational risk, including security, privacy, and operational resilience. It offers guidance on risk identification, analysis, and mitigation strategies.
NIST Special Publication 800-53: This publication provides a catalog of security and privacy controls that can be applied to AI systems to address identified risks and ensure compliance with regulatory requirements.
ISO Standards: Relevant ISO standards, such as ISO 27001 (information security management) and ISO 22301 (business continuity management), offer best practices for managing risks in AI systems and ensuring their resilience against potential disruptions.

By integrating these frameworks and standards, organizations can establish a robust risk management program for AI systems, foster responsible development and deployment, and minimize potential negative impacts. This presentation will provide attendees with the knowledge and tools necessary to assess and manage risks associated with their AI initiatives effectively.

How to Assess Risk for AI with NIST and ISO Standards

Virtual

Speakers

Lewis Elliott Abraham

Catherine Vu