In my experience, the most sophisticated decision makers tend to be hypothesis-driven thinkers. They may be engineers solving a technical problem, product designers fulfilling a customer need, or entrepreneurs growing a business. They form a hypothesis about how to reach their goal and then work systematically to either validate or falsify it. Say you’re tuning a learning algorithm that estimates the health of corn stalks based on input from a tractor-mounted camera. (Many companies are developing products like this to help farmers make decisions about planting, weeding, or harvesting.) If your algorithm is doing poorly, how should you go about improving it? Some engineers tend to apply a one-size-fits-all rule. Someone who has experience improving algorithms by collecting more data may tend to gather more photos of corn stalks. When that doesn’t work, they may end up trying things more or less at random until they stumble on something ...