AI Ethics for Engineers: Designing Decisions for Autonomous Systems

As autonomous vehicles and AI systems take over real-world decision-making, engineers face unprecedented ethical responsibilities. How do we program a machine to make life-or-death decisions when accidents are unavoidable? This text-based course guides you through the foundational ethics of artificial intelligence, helping you analyze safety-critical scenarios and implement responsible engineering frameworks. You will transition from understanding classic philosophical dilemmas to applying concrete ethical design principles in modern software development. What you'll learn: 1. Understand foundational ethical theories and how they apply to modern machine learning models. 2. Analyze the classic trolley problem and its real-world implications for autonomous vehicle programming. 3. Evaluate algorithmic bias, fairness, and accountability in automated decision-making systems. 4. Apply risk-assessment frameworks to safety-critical AI and robotics applications. 5. Explore modern AI alignment principles and current regulatory standards for autonomous systems. The course begins with essential terminology and the core philosophical foundations of engineering ethics. From there, you will read through real-world case studies, analyze algorithmic trade-offs, and complete written exercises designed to challenge and refine your technical decision-making. This course is designed for aspiring engineers, computer science students, and tech enthusiasts who want to understand the moral dimensions of technology. No prior programming or philosophy background is required. Reflect on the ethical dimensions of tomorrow's technology and start building safer, more responsible systems today.