This introductory course targets civil servants for national and regional administration, officials from international organisations, entrepreneurs, professionals in relevant sectors, representatives of civil society organisations, universities, research centres, think tanks, and the interested public.

The courses offered by UNU-MERIT are university-level training courses. We require participants to have a completed MSc (or equivalent) in Social Sciences (Public Policy, Economics, International Relations) or a related discipline (e.g. Law, Engineering, Political Science).

We are open to accepting participants with a BA degree (or equivalent) and work experience in the field, and well-developed analytical thinking (university level). In those cases, we require an entrance check based on a CV, including educational attainment and work experience.

Language: Fluency in English is required.
 

Upon completion of this course, participants will be able to:

• Define and classify the key constitutive dimensions of AI governance.
• Explain the ethical, normative and regulatory dilemmas in AI governance at international and national levels.
• Analyse the role of different stakeholders in AI governance.
• Evaluate the impact of AI governance on society, economy, and politics.

The course is divided into four units. The units have been carefully chosen in order to provide an overview of the most important aspects in the ethical, normative, regulatory and policy dimensions.

The four units are: 

Unit 1: Overview of AI and ethical principles

Unit 2: Global Governance of AI

Unit 3: Regulatory and normative frameworks

Unit 4: AI policies and stakeholders' engagement.

The course is offered online, with 10 weeks registration time of which 4 weeks course content offering. The course content includes:

• Weekly synchronous online lecture (Monday 14:00 CEST)
• Weekly synchronous online tutorial session (Thursday 14:00 CEST)
• Weekly Required (and optional) readings and toolkit materials (asynchronous)
• Individual Unit Exams
• Individual Final assignment and oral exam
• Optional weekly live (synchronous) Q&A sessions and Q&A discussion forums (asynchronous)
• Available deepening materials/policy applications and examples (asynchronous)

Readings: For each unit, a selection of compulsory readings is identified, complemented with a list of additional readings for the interested reader.  

Each unit contains an assignment, which participants have to complete for the course.

All materials can be accessed through the ITU Academy platform. 

Participants are required to submit one multiple-choice exam at the end of each module. Each assignment is graded individually on a 1-10 scale.

Upon completion of the course, participants need to submit an individual assignment.  Upon completion of all unit exams and submission of the assignment, there will be an individual oral exam.

The final grade for this module is the simple weighed average of all assignment grades.

• Unit 1 Exam: 10%
• Unit 2 Exam: 10%
• Unit 3 Exam: 10%
• Unit 4 Exam: 10%
• Individual final assignment: 30%
• Oral examination: 30%

You will pass the course if the average grade is 5.5 or higher (on a 10 point scale, with 1 being lowest and 10 being highest) and if the grade for at least three unit exams 5.5 or higher.

For each Unit exam there is one resit option. In case you take this option (which is open to all, irrespective the grade of exam one) the grade for the resit option will replace the initial grade (also in case the initial grade was higher). This resit option is available immediately after the completion of the exam.

For the individual assignment, there is one resit opportunity, linked to a resit oral exam. You are allowed to take the resit if your assignment grade is below 5.5 (on a 10 point scale, with 1 being lowest and 10 being highest) or if your final grade is below 5.5.

A total score of 5.5 or higher is required to pass the course and obtain the ITU certificate.

Overview of AI and ethical principles. The first module will provide a general overview of AI governance. It will introduce the fundamental ethical considerations and principles at the intersection of technology, ethics, law, and policy in AI governance. This introductory module will define the concept of AI governance and its significance for responsible, human-centred and ethical AI development. To understand the complexity of the AI challenges and dilemmas, participants will be acquainted with ethical challenges regarding bias, fairness, transparency, accountability, privacy, and accountability of the development of AI systems. During the tutorial session, the participants will focus on operationalising the UNESCO Ethical Recommendation on Artificial Intelligence to evaluate real-world case studies.

Global Governance of AI. The second module of the course will systematise the evolving process of developing global, regional and transnational frameworks for AI governance. This module will provide a landscape of different AI governance frameworks and their features, such as thematic scope, authority, institutional arrangements, and legal nature. It also includes the analysis of the interactions of the public authorities with different private actors (companies, experts, scientists, associations, etc.) in shaping the AI governance and regulations processes. The tutorial session will focus on explaining the mechanisms of the emergence of the AI regime complex in the context of the parallel expansion of new multi-stakeholder cooperation platforms and the fragmentation of existing cooperation frameworks.

Regulatory and normative frameworks. The third module of the course will introduce the landscape of developing regulatory and normative frameworks applicable to the field of AI. During this module, students will be acquainted with landmark existing regulations and laws governing AI at the international, national and industry levels. It will explore how authorities and organisations ensure compliance with the regulatory frameworks by distinguishing between soft and hard law regulation. The tutorial session will discuss the strategies, approaches and methodologies employed to ensure compliance with normative frameworks. It will explain the AI risk assessment approach to identifying and managing issues related to the deployment and operation of AI systems.
 

AI policies and stakeholders' engagement. The fourth module of the course will discuss the importance of the involvement of different stakeholders in the development of AI policies and strategies. This session will outline the relevance of stakeholders' involvement in designing and implementing AI policies in different jurisdictions. It will also explain the role of public authorities, industry, experts, activists, and affected communities in understanding the mechanisms of establishing accountability and transparency, including legally binding and voluntary codes of conduct. The tutorial session will focus on the strategies and challenges of implementing AI policy, comparing centralised and decentralised governance models and the methods for assessing the impact of AI policies on society, economy and politics.
.