Philosophy of Science and Engineering

Popper showed that the goal of testing is to find failures, not confirm success. This insight transforms how you write test plans, review designs, and evaluate evidence. If you have ever shipped a product that passed all tests and still failed in the field, you need Popper.

Kuhn explained why established communities resist new ideas, even when the evidence is overwhelming. Understanding this helps you navigate technology transitions (analog to digital, C to Rust, monolithic to microservices) without being caught on the wrong side.

Every simulation, every schematic, every equation is a model. George Box reminded us that all models are wrong, but some are useful. Knowing the difference between the map and the territory is the difference between a good engineer and a dangerous one.

Pseudoscience, cargo cult engineering, and vendor hype are everywhere. Feynman’s “Cargo Cult Science” essay is the best guide ever written for not fooling yourself. This course gives you the tools to spot nonsense.

What Makes Something Scientific?. The demarcation problem: how do you tell science from non-science? Popper’s falsifiability criterion, pseudoscience red flags, and the cold fusion debacle. Learn to evaluate engineering claims, datasheets, and research papers.

The Scientific Method in Engineering Practice. The textbook version vs the messy reality. Debugging is hypothesis testing, design reviews are peer review, test plans are experiments. Case study: Edison’s systematic filament testing.

Falsifiability: Testing to Fail. Popper’s key insight applied to engineering: the goal of testing is to find how your design fails, not to confirm it works. Confirmation bias, negative testing, and the Challenger disaster.

Paradigm Shifts. Kuhn’s model of scientific revolutions applied to engineering: vacuum tubes to transistors, CISC to RISC, bare metal to RTOS. The Rust vs C debate through Kuhn’s lens.

Models, Maps, and Reality. “All models are wrong, but some are useful.” When SPICE simulations succeed, when financial models catastrophically fail, and how to use engineering models wisely by knowing their assumptions and boundaries.

Uncertainty and the Limits of Knowledge. What we can know, what we cannot. Measurement uncertainty, chaos theory, complexity, observer effects, and why “more data” does not always help. The Mars Climate Orbiter and defense in depth.

Ethics and Responsibility in Engineering. Therac-25, Boeing 737 MAX, Volkswagen emissions. When engineering decisions have life-or-death consequences. Professional codes, whistleblowing, and a practical ethics checklist.

Technology, Society, and Unintended Consequences. Every technology has second-order effects. The automobile, social media, IoT surveillance, AI recommendation engines. The Collingridge dilemma and responsible innovation.

Thinking Like a Scientist-Engineer. Synthesis: combining scientific rigor with engineering pragmatism. When to be rigorous, when to ship. Feynman’s cargo cult science, engineering notebooks, and building a personal scientific practice.