Wrong-Side-of-Maybe Fallacy, Load Theory, Luxury Beliefs, & More
Alex Brogan
Most people misunderstand probability in a predictable way. When a weather forecast calls for a 70% chance of rain and it doesn't rain, they declare the forecast "wrong." When it rains, they call it "right." This is the wrong-side-of-maybe fallacy — judging probabilistic predictions based solely on which side of 50% they land, rather than their actual calibration over time.
Philip Tetlock identified this pattern in his research on forecasting accuracy. The fallacy reveals a fundamental confusion between confidence and correctness, between being directionally right and being precisely calibrated. A 70% forecast that fails to materialize wasn't wrong — it was telling you that 3 out of 10 times, it wouldn't rain.
The same logic applies to business decisions. Venture capitalists who back companies with a 30% success rate aren't failing when 7 out of 10 investments don't work. They're operating within expected parameters, assuming their 30% winners generate sufficient returns to compensate for the 70% that don't.