Overview

Google, IBM & Meta Certificates – 40% Off

One Coursera Plus subscription covers most Professional Certificates on Coursera.

Welcome to our MOOC on how artificil intelligence is regulated and governed in practice. This course is aimed at professionals and students interested in the legal and societal implications of AI. It is particularly relevant for legal practitioners, policymakers, public sector officials, private sector actors, civil society representatives, academics, and students who want to better understand how existing legal frameworks apply to emerging technologies. Throughout the course, you will examine the EU AI Act and its risk-based approach, understand how AI-related risks are managed through legal and market tools, and analyse how responsibility is allocated across public and private actors. Drawing on theory and pracical examples, the course also considers AI’s impact on legal institutions, security, and migration, as well as the role of standards, sandboxes, soft-law frameworks, and corporate ethics in making AI governance operational. By the end of the course, you will be able to connect real-world AI systems to the rules, risks, and responsibility structures that govern them.

Syllabus

How AI Is Regulated
- This module introduces the idea of regulation: who makes the rules, why they exist, and how “risk-based” regulation determines the strictness of control. Learners explore how governments classify AI risks, why this matters for innovation and safety, and how new frameworks like the EU AI Act work in practice.
Responsibility in Practice - From Mistakes to Insurance
- When something goes wrong with an AI system - who pays? This module explains how the law allocates responsibility and manages risk through liability, contracts, and insurance. Learners discover how real examples like self-driving cars or hiring algorithms are handled when harm occurs.
AI Beyond Bordes - A Global View
- AI is reshaping legal systems and public authority across jurisdictions. This module examines how AI operates in cross-border contexts, focusing on its impact on the legal profession, judicial decision-making, and public administration. It then turns to high-stakes uses of AI in security, facial recognition, and migration control, where questions of human rights, surveillance, and state power become central.
Making Rules Work - Enforcement and Oversight
- AI is global, but laws differ. This module compares how the EU, US, and China regulate AI and how international coordination is emerging through organisations such as the UN, OECD, and UNESCO. Learners explore why global cooperation matters for both innovation and human rights.
Ethics, Standards and Industry Self-Regulation
- Not all governance comes from government. This module shows how companies and research communities create internal ethics codes, adopt technical standards, and use certification schemes to build trust in AI systems.
Peer Project - Create a Governance Plan
- In this final module, learners apply what they have learned about regulation, liability, and governance to design a simple governance plan for a fictional AI system. The activity consolidates the main course outcomes and demonstrates practical understanding of how to make AI law work.