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AI, Ethics & Justice: Fairness, Accountability, Rights

Lund University via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

6 weeks, 2 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Overview

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Welcome to our MOOC on how artificial intelligence affects democracy, power, and justice. 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 explore how bias and discrimination emerge in AI systems, how transparency operates across different areas of law, and who gets to shape AI governance. The course also analyses access to justice when automated decisions cause harm and frames ethical dilemmas through EU and constitutional law perspectives, including applied challenges in healthcare AI. By the end of the course, you will understand how AI reshapes participation, accountability, and fundamental rights in contemporary legal systems.

Syllabus

Bias and Fairness - Why AI Can Discriminate
- AI systems can unintentionally reproduce bias from the data they learn from. This module introduces the concept of bias, explains why fairness matters, and shows simple ways to spot and mitigate discrimination in automated decision-making.
Transparency Across the Legal Field
- Transparency is key to trust. This module explains why it matters to understand how an algorithm reaches a decision and what “explainability” means in practice. Learners explore the tension between complexity, trade secrets, and the human right to information.
People and Power - Who Gets a Say in AI
- Who participates in shaping AI? This module introduces democratic and participatory approaches to AI governance. Learners examine how communities, civil-society groups, and citizens can influence how AI systems are designed and used.
Access to Justice - Fighting Back Against Bad AI Decisions
- This module focuses on what happens when AI decisions harm people. Learners explore real examples - denied benefits, biased hiring, automated policing - and learn how complaints, appeals, and oversight mechanisms can restore justice.
Turning Ethics into Action
- Ethics becomes meaningful only when applied. This module introduces key ethical principles -beneficence, non-maleficence, autonomy, and justice - and shows how to turn them into everyday practice when designing or deploying AI systems.
Peer Project: Ethics in Action
- In the final module, learners apply ethical principles to a realistic AI scenario. They identify ethical challenges, link them to fairness, transparency, and accountability, and design a simple ethics checklist or intervention plan. The goal is to turn abstract values into practical guidance.