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Starts 5 June 2025 10:48

Ends 5 June 2025

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AI Governance Explained: Ensuring Compliance While Driving Innovation

Discover how to implement AI governance strategies that balance regulatory compliance with innovation, covering frameworks like ISO 42001, GDPR, and NIST AI RMF while building trustworthy, transparent AI systems.
INFOSEC TRAIN via YouTube

INFOSEC TRAIN

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Overview

Discover how to implement AI governance strategies that balance regulatory compliance with innovation, covering frameworks like ISO 42001, GDPR, and NIST AI RMF while building trustworthy, transparent AI systems.

Syllabus

  • Introduction to AI Governance
  • Definition and Importance of AI Governance
    Key Challenges in AI Governance
  • Regulatory Frameworks Overview
  • ISO 42001: AI Management Systems
    General Data Protection Regulation (GDPR)
    NIST AI Risk Management Framework (AI RMF)
  • Balancing Compliance and Innovation
  • Strategies for Managing Compliance
    Encouraging AI Innovation within Regulatory Constraints
  • Designing Trustworthy AI Systems
  • Principles of Transparency and Explainability
    Ensuring Data Integrity and Security
  • Risk Assessment and Management
  • Identifying AI-Related Risks
    Developing Mitigation Strategies
  • Creating Ethical AI Policies
  • Understanding Bias and Fairness in AI
    Legal and Ethical Considerations
  • Building an AI Governance Framework
  • Key Components and Best Practices
    Roles and Responsibilities in Governance
  • Case Studies and Practical Applications
  • Analysis of Real-World AI Governance Scenarios
    Lessons Learned from Industry Leaders
  • Future Trends and Challenges
  • Emerging Technologies and Their Governance
    Predicting and Preparing for Future Regulations
  • Course Summary and Key Takeaways
  • Review of Main Points
    Actionable Steps for Implementing AI Governance

Subjects

Computer Science