Artificial Intelligence
Responsible AI and AI Risk Management Frameworks
Overview
This training introduces attendees to the many Responsible AI governance frameworks, risk management frameworks, and related resources that are available to organizations as they plan the safe and secure development, deployment, and use of AI systems.
Duration
8 class hours (1 day)
Why You Should Take This Course
In the duration of this course, students will:
- Explore the “promise and peril” of artificial intelligence (AI) systems and the resulting need for organizations to develop governance processes/mechanisms that ensure the safe, trustworthy, and secure development, deployment, and use of these systems.
- Explore ethical considerations in the development, deployment, and use of AI systems.
- Review the current landscape of Responsible AI governance frameworks and risk management frameworks including a comparison of taxonomies.
- Review risk repositories, incident databases, and similar resources.
- Review the NIST AI Risk Management Framework (RMF) and related resources (e.g., the NIST Playbook, profiles, etc.).
- Apply the NIST AI RMF to participant scenarios.
- Provide the spark needed to get people moving forward on governance initiatives.
Course Outline
Responsible AI and AI Risk Management Frameworks
A high level outline of the course is as follows:
- Promise and peril.
- Ethical considerations.
- Frameworks review.
- Related resources.
- NIST deep dive.
- NIST real world exercise.
- Exercise review, discussion, and ideation.