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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
2463 Courses
31 minutes
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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
- Regulatory Frameworks Overview
- Balancing Compliance and Innovation
- Designing Trustworthy AI Systems
- Risk Assessment and Management
- Creating Ethical AI Policies
- Building an AI Governance Framework
- Case Studies and Practical Applications
- Future Trends and Challenges
- Course Summary and Key Takeaways
Definition and Importance of AI Governance
Key Challenges in AI Governance
ISO 42001: AI Management Systems
General Data Protection Regulation (GDPR)
NIST AI Risk Management Framework (AI RMF)
Strategies for Managing Compliance
Encouraging AI Innovation within Regulatory Constraints
Principles of Transparency and Explainability
Ensuring Data Integrity and Security
Identifying AI-Related Risks
Developing Mitigation Strategies
Understanding Bias and Fairness in AI
Legal and Ethical Considerations
Key Components and Best Practices
Roles and Responsibilities in Governance
Analysis of Real-World AI Governance Scenarios
Lessons Learned from Industry Leaders
Emerging Technologies and Their Governance
Predicting and Preparing for Future Regulations
Review of Main Points
Actionable Steps for Implementing AI Governance
Subjects
Computer Science