Engineering Ethics in the Age of Artificial Intelligence

As artificial intelligence increasingly automates decision-making, engineers face unprecedented ethical responsibilities. Understanding how these technologies reshape human reason, accountability, and societal structures is a core engineering requirement. This text-based course guides you through the philosophical foundations and practical frameworks needed to build responsible, ethical AI systems. You will transition from simply writing code to critically evaluating the societal impact of your technical choices, aligning your engineering practices with modern safety and fairness standards. What you'll learn: 1. Understand foundational ethical theories and how AI challenges traditional Enlightenment values of human agency. 2. Identify and mitigate algorithmic bias, ensuring fairness and equity in machine learning models. 3. Apply modern framework concepts for transparency, explainability, and accountability in automated systems. 4. Navigate the complexities of data privacy, consent, and intellectual property in generative AI. 5. Evaluate safety risks, alignment problems, and the long-term societal implications of autonomous technologies. 6. Implement practical ethical checklists and impact assessments within your engineering workflow. You will begin by exploring core ethical terminology and historical philosophical shifts before moving into practical case studies, code-ethics analysis, and structural frameworks for responsible system design. This course is designed for beginner software developers, data scientists, and engineering students, requiring no prior background in philosophy or ethics. Start reading today to build technology that respects human values and advances society responsibly.