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%