Mastering AI Ethics & Governance

Programme Outline

Learning Objectives

By the end of the course, participants should be able to:

  • Understand current and developing definitions of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Bias, etc.
  •  Determine the need for strong ethics and governance in AI.
  • Develop efficient internal governance structures for AI development and deployment.
  • Determine the level of human involvement in AI-augmented decision-making.
  •  Identify the operational issues of AI governance and management.
  • Provide an overview of international AI ethics frameworks across the world.
  • Identify stakeholder interaction and communications.
Day 1
  • Introduction+ Definitions + Case Study 1
  • Bias + Human Centricity + Case Study 2
  • Generative AI Pros & Cons + Case Study 3
  • Explainability + Case Study 4
Day 2
  • Accountability + Frameworks + Case Study 5
  • Auditability + Stakeholder Management + Case Study 6
  • Governance + Global Views + Case Study 7 + 6 solutions
  • Assessment
Assessment
  • Online quiz – 60%
  • Oral Assessment (class participation) – 40%
What’s next

Find out more

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