Global MOOC on the Ethics of AI

UNESCO via Coursera

Go to class Write review

Details

Go to class

Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

10 weeks, 1 hour a week
Sessions

Self-Paced
Level

Intermediate
Subtitles

Arabic, Hindi, Russian, Korean, Portuguese, English, Italian, Indonesian, French, Chinese, Spanish

Found in

Overview

Google, IBM & Meta Certificates – 40% Off

One plan covers every Professional Certificate on Coursera.

Unlock All Certificates

AI is reshaping how the world works, and those who understand its ethical dimensions are better positioned to lead, design, and govern it in a way that helps everyone. This course, developed by UNESCO, in partnership with LG AI Research, gives you a comprehensive and practical foundation in AI ethics, built for professionals with basic knowledge of AI, who want to learn to make a real difference in how AI is created and used every day, and develop a foresight into embedding ethics in AI products and services. Across 10 modules, you will explore the full spectrum of AI ethics from the ‘why’ and ‘what’ of ethics, to how to operationalize the ethical AI principles, fairness, privacy, transparency, sustainability, proportionality, and meaningful work. Each module combines conceptual frameworks with real world and relatable examples, and simple tools and frameworks to immediately apply what you learn to your own professional context. What makes this course unique is its breadth and actionability. Drawing on UNESCO's Recommendation on the Ethics of AI, you'll move from understanding ethical principles to evaluating real-world trade-offs, values, and choices, and ultimately designing ethical, human-centered responses across the AI lifecycle using tools and frameworks. This is relevant, whether you work in technology, policy, law, research, or organizational leadership.

Syllabus

Module 1: Foundations of AI Ethics

This module explores the foundations of AI ethics, examining how ethical thinking applies throughout the AI lifecycle—from design and development to deployment and use. Learners will explore key ethical concepts, frameworks, and reasoning traditions while developing practical skills to identify, analyse, and address ethical challenges in AI systems.

Module 2: Human-AI Interaction

This module explores practical approaches to ethical AI design, using the Stanford AI Ethics Toolkit to connect ethical principles with real-world decision-making. Learners will examine how design choices influence human autonomy, dignity, and relationships, while applying practical frameworks to evaluate AI systems in diverse contexts.

Module 3: Safety & Security

This module examines how AI systems are tested, evaluated, and governed to ensure safe and responsible deployment. Learners will explore risk-based approaches to testing, understand the relationship between evaluation and regulation, and analyse how technical, human, and organisational factors influence AI performance in high-stakes contexts.

Module 4: Fairness, Non-Discrimination & Inclusion in AI

This module explores how fairness can be operationalised across the AI lifecycle, from defining affected groups and identifying risks to applying technical and governance tools. Learners will examine fairness trade-offs, safeguards, and corrective actions for AI-supported decisions.

Module 5: Privacy, Data Protection and Data Governance in AI

This module explores the principles of privacy, data protection, and data governance in AI, examining how responsible AI systems balance innovation with user rights, accountability, and trust. Learners will explore key governance concepts, practical tools, and real-world case studies to understand how privacy, transparency, human oversight, and responsible data practices support trustworthy AI throughout its lifecycle.

Module 6: Transparency, Explainability and Accountability (TEA)

This module explores the principles of Transparency, Explainability, and Accountability (TEA) in AI systems. Learners will examine how TEA supports trust, human oversight, and responsible AI governance while developing practical skills to assess, communicate, and improve transparency and accountability throughout the AI lifecycle.

Module 7: AI, Environment & Sustainability

This module explores the environmental sustainability of AI systems, examining their impacts across the entire AI lifecycle. Learners will develop practical skills to identify environmental hotspots, evaluate sustainability trade-offs, and apply frameworks that support responsible decision-making and organisational sustainability practices.

Module 8: Proportionality & Do No Harm

This module explores proportionality and risk-based governance in AI, focusing on how to assess, manage, and mitigate risks while protecting fundamental rights and enabling innovation. Learners will apply practical assessment frameworks and governance tools to support responsible AI decision-making.

Module 9: Human Autonomy, Meaningful Work, and the AI Economy

This module explores the impact of AI on human autonomy, meaningful work, and workplace wellbeing. Learners will learn how to design AI systems that support human agency, implement effective oversight, and promote ethical and responsible AI adoption in the workplace.

Module 10: Global AI Governance

This module explores the complexities of AI governance across different countries, organisations, and regulatory contexts. Learners will delve into governance frameworks, cross-border challenges, and practical approaches to balancing innovation, accountability, and trust in AI systems.