Extrapolating from past data points is not an explanation. Building your confidence that something that will happenβlike Bayes Theoremβis useful for descrete, observable problems, but fails to reveal the truth. It’s the equivalent of saying “because it’s always been that way” which is a flawed way of reasoning about the world.
For example, let’s say you are trying to predict the temperature of a beaker water. You start to turn up the heat on a burner and, based on previous data points, you expect the temperature to rise. It correlates wellβheat goes up, water temperature goes up. Until it hits the boiling point and the water temperature remains constant. Trends are not sufficient to explain what’s going on here because it doesn’t explain the idea what is truly happening.
Listen to The Beginning of Infinity part 1 on Naval Ravikant’s podcast.
See also:
- More specifically, updating your priors is not an epistemology. It’s useful, but there are downsides to inductive reasoning.
- Creativity is required to offer good explanations.
- The Beginning of Infinity