This course introduces the core ethical challenges in artificial intelligence and equips learners with the tools to evaluate and design responsible AI systems. Through twelve structured modules, students examine how bias, fairness, transparency, privacy, and accountability impact AI outcomes. Case studies and practical tools are used to explore real-world implications across domains such as hiring, lending, and policing. The course concludes with a capstone project where students conduct an ethical audit of an AI system.
Students will:
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Understand why ethics is essential in AI design and deployment
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Identify sources of bias in data, models, and decision processes
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Apply techniques for bias mitigation, transparency, and explainability
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Evaluate privacy and data ethics issues
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Understand global AI ethics frameworks (e.g., EU AI Act, UNESCO)
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Integrate ethics into the AI development lifecycle
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Conduct a structured ethical analysis of an AI application
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