What You Need to Know Before
You Start

Starts 7 June 2025 00:24

Ends 7 June 2025

00 days
00 hours
00 minutes
00 seconds
course image

Strategies for Effective AI Governance

Discover key principles of AI governance, regulatory standards like NIST AI Risk Management Framework, and practical steps to implement oversight processes for organizational AI initiatives.
via Pluralsight

659 Courses


22 minutes

Optional upgrade avallable

Not Specified

Progress at your own speed

Free Trial Available

Optional upgrade avallable

Overview

Organizations are increasingly adopting AI without proper oversight, leading to scattered implementation and potential risks. In this course, Strategies for Effective AI Governance, you'll learn the basics of developing an AI governance approach for your organization.

First, you'll explore the key principles of AI governance and why they matter. Next, you'll discover an overview of current regulatory standards, including the NIST AI Risk Management Framework.

Finally, you'll learn about practical first steps for implementing basic governance structures. When you're finished with this course, you'll have a foundational understanding of AI governance needed to begin developing oversight processes for AI initiatives in your organization.

Syllabus

  • Introduction to AI Governance
  • Definition and Importance of AI Governance
    Objectives of AI Governance in an Organization
    Challenges in AI Governance
  • Key Principles of AI Governance
  • Fairness and Non-Discrimination
    Transparency and Explainability
    Accountability and Responsibility
    Privacy and Data Protection
    Robustness and Security
  • Overview of Current Regulatory Standards
  • NIST AI Risk Management Framework
    GDPR and AI Considerations
    Other Relevant National and International Standards
  • Practical Steps for Implementing AI Governance
  • Assessing Organizational Readiness
    Establishing Governance Roles and Responsibilities
    Developing an AI Risk Management Plan
    Ensuring Compliance with Legal and Ethical Standards
  • Developing Oversight Processes for AI Initiatives
  • Monitoring and Auditing AI Systems
    Creating Feedback Loops for Continuous Improvement
    Engaging Stakeholders and Promoting Awareness
  • Conclusion and Future Trends
  • Emerging Trends in AI Governance
    Preparing for Evolving Regulatory Landscapes
    The Role of AI Governance in Promoting Innovation and Trust
  • Case Studies and Real-World Examples
  • Analysis of Successful AI Governance Models
    Lessons Learned from Governance Failures

Taught by

Doru Catana


Subjects

Computer Science