- Angel Draev
- Ghazi Mabrouk
Introductory
Event Organizer(s)
Funded by
Description
This online self-paced course is part of the broader master course AI governance: fundamentals, which introduces learners to key concepts, challenges, and frameworks shaping the governance of Artificial Intelligence (AI).
While this course can be taken as a standalone module, it also forms one of five building blocks of the full learning journey. Participants may choose to focus on this specific topic or complete the master course to gain a comprehensive understanding of AI governance. Designed for non-technical audiences, the course equips policymakers, professionals, and civil society actors with the knowledge needed to critically assess AI systems and engage in governance discussions.
Upon successful completion of this course, participants will receive an ITU Academy badge. Learners who complete all five courses and pass the final assessment in the master course will earn an additional ITU Academy badge.
Designed for non-technical participants, this course is ideal for policymakers, regulators, business professionals, civil society organizations, international organizations’ staff, and students looking to understand how AI is shaping societies and economies worldwide. It breaks down complex AI concepts into clear, accessible language, making it easy for participants to grasp the implications of AI without requiring a technical background.
By the end of this module, participants will be able to:
- Compare risk-based and rights-based approaches to AI regulation.
- Identify national, regional, and global AI governance frameworks.
- Explain innovative models of governance, including sandboxes and algorithm audits.
- Assess the role of public–private partnerships (PPPs) in shaping AI regulation.
The course applies an interactive, learner-centered approach tailored to an online, self-paced format. Participants will progress through a mix of learning tools designed to build knowledge, encourage reflection, and link theory with practice.
- Structured Learning: Engaging video lectures, interactive readings, and factsheets introduce and explain core concepts.
- Case-Based Scenarios: Story-driven examples ground abstract principles in real-world dilemmas, helping learners analyze governance challenges.
- Knowledge Checks: Quizzes and quick assessments reinforce understanding, provide instant feedback, and guide learners toward mastery.
- Wrap-Up and Resources: The course concludes with a synthesis of key lessons and curated references for continued learning on AI governance.
This self-paced course employs a balanced and flexible assessment strategy designed to measure both participants’ comprehension of fundamental AI governance concepts and participants’ ability to apply this knowledge in real-world and professional contexts.
Passing Criteria
- A total score of 80% or higher is required to obtain the ITU badge attesting completion.
- Participants must complete all required assignments and quizzes.
This module explores different approaches to AI regulation, examining how governments and international bodies develop frameworks to manage risks, protect rights, and foster innovation.
- Uses a learner-friendly, scenario-based approach tailored for non-technical audiences
- Introduces key regulatory approaches (risk-based and rights-based) through clear, practical explanations
- Explores global, regional, and national AI frameworks (e.g., EU, U.S., China, and international organizations) to highlight diverse governance models
- Examines real-world challenges of AI governance, including differences in national policies and the complexity of international coordination
- Introduces innovative governance tools such as regulatory sandboxes and public–private partnerships (PPPs)
Registration information
Unless specified otherwise, all ITU Academy training courses are open to all interested professionals, irrespective of their race, ethnicity, age, gender, religion, economic status and other diverse backgrounds. We strongly encourage registrations from female participants, and participants from developing countries. This includes least developed countries, small island developing states and landlocked developing countries.
