AI Ethics for Engineers: Moral Decisions in Autonomous Vehicles

As autonomous vehicles transition from research labs to public roads, programming them to navigate split-second decisions in critical situations has become one of the greatest engineering challenges of our time. How do we translate complex human ethics into logical machine code? This text-only course guides you through the foundational ethical theories and practical engineering frameworks required to navigate moral dilemmas in artificial intelligence. You will transition from understanding basic philosophical principles to analyzing complex algorithmic decision-making models used in modern self-driving systems. What you will learn: Understand the classical ethical frameworks, including utilitarianism and deontology, as they apply to machine learning; Analyze the famous Trolley Problem and its modern variations in autonomous driving scenarios; Explore how algorithmic bias and safety-critical engineering standards shape autonomous vehicle software; Evaluate modern AI alignment techniques and regulatory guidelines for autonomous systems; Practice resolving moral dilemmas through structured, written engineering case studies. You will begin with core ethical terminology and philosophical foundations before moving into real-world engineering trade-offs, algorithmic safety, and policy implications. Designed for aspiring engineers, computer science students, and tech enthusiasts, this course requires no prior background in philosophy or programming. Start reading today to shape the future of responsible autonomous technology.