Foundations of Responsible AI and Ethical System Design

As artificial intelligence becomes central to decision-making, ensuring these systems are fair, transparent, and accountable is more critical than ever. This course introduces you to the core principles of ethical AI, helping you understand how to identify risks and build trust with users. You will transition from a beginner to a practitioner who understands the societal impacts of AI, learning how to evaluate machine learning models for bias, implement governance frameworks, and address modern ethical challenges. What you'll learn: Understand foundational ethical principles including fairness, accountability, transparency, and privacy; Identify common sources of bias in training data and algorithms; Apply governance frameworks to evaluate and mitigate risks in real-world AI deployments; Explain the ethical implications of generative AI, including hallucinations and data privacy; Design transparent system workflows that respect user privacy and data rights. The course starts with essential terminology and historical context before moving into practical frameworks for analyzing and mitigating algorithmic bias. You will explore real-world scenarios through written case studies and conceptual exercises. This course is designed for beginners, including product managers, developers, and policy enthusiasts, with no prior technical or programming experience required. Start reading today to build a solid foundation in the ethical design of future technologies.