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.

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.

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.

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.

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.