S3T Learning Path: Advanced Studies in Artificial Intelligence Governance.


Learning objectives

In this this 3 week advanced studies course course, participants will gain:

  • A deep understanding of the principles of AI Governance
  • A practical framework for setting up and managing an AI Governance function,
  • A set of sample AI Governance artifacts that they can use to accelerate the establishment and development of a mature AI Governance committee.

How the curriculum enables learning and skill acquisition

  • Sessions for learning key concepts,
  • Discussion forums to enhance engagement and provide a platform for deeper exploration of topics, and facilitate peer-to-peer learning.
  • Presentation days where participants and share their final deliverables and lessons learned.

Session schedule

This learning approach uses a 3 day per week cadence to introduce, activate and reinforce key lessons and skills:

  • Monday: Introduction to Learning Objective for the week, and Key Concepts to master.
  • Wednesday: Discussion & Clarification of Key Points, Initial Review of Draft Deliverables.
  • Friday: Presentation of Final Deliverables. Reinforce and celebrate what we learned.

Curriculum Outline

Week 1: Introduction to AI Governance

Main Class (Monday): Foundations of AI Governance

  • Overview of AI and its impact on society
  • Key principles of AI governance
  • Importance of ethical considerations in AI development and deployment
  • Assignment: Write a 1 page charter for an AI Governance Committee.

Discussion Forum (Wednesday): Open Discussion on AI Governance Principles

  • Interactive Q&A session on Monday's topics, and review of initial drafts of key deliverables for the week.
  • Sharing insights and perspectives on AI governance
  • Networking and collaborative discussion among participants

Follow-up (Friday): Case Studies in AI Governance

  • Discussion on real-world examples of AI governance challenges and successes
  • Analysis of current AI regulations and their effectiveness

Week 2: Policy and Regulatory Frameworks

Main Class (Monday): Global and Regional AI Policies

  • Examination of international AI policies and regulatory frameworks
  • Comparative analysis of AI regulations in different regions (e.g., EU, US, Asia)
  • The role of governmental and non-governmental organizations in AI governance
  • Assignment: Write a membership roster for an AI Governance Committee

Discussion Forum (Wednesday): Policy Debate and Discussion

  • Debating different AI policy approaches
  • Evaluating the effectiveness of existing regulations
  • Engaging in a policy development brainstorming session

Follow-up (Friday): Policy Development Workshop

  • Group activity: Drafting policy recommendations for AI governance
  • Discussion on the role of stakeholders in policy-making

Week 3: Implementing and Enforcing AI Governance

Main Class (Monday): Strategies for Effective AI Governance

  • Tools and methodologies for implementing AI governance
  • Risk management and mitigation strategies in AI
  • The role of transparency and accountability in AI systems
  • Assignment: Write the Voting Rules for an AI Governance Committee.

Discussion Forum (Wednesday): Practical Challenges and Solutions

  • Discussing practical challenges in implementing AI governance
  • Sharing experiences and solutions
  • Collaborative problem-solving session
  • Review of Draft Voting Rules.

Follow-up (Friday): Practical Applications and Future Trends

  • Exploring the future of AI governance: trends and predictions
  • Interactive session on the implementation of governance strategies in various sectors
  • Open discussion on the ethical implications of emerging AI technologies

Course Wrap-Up

  • Summary of key learnings and takeaways
  • Q&A session to address remaining questions and insights
  • Final thoughts and reflections on the future of AI governance