A Skeptic's Guide to How Cognitive Biases and Reasoning Errors Fuel AI Hype

Separating hype from reality in AI has become more daunting than ever. More than cleantech in the aughts (we should know, we were there). Or previous AI waves (we were there too). While we've experienced tech hype cycles before, the current wave feels like a different beast altogether.

To shield yourself from the relentless enthusiasm of the #UnthinkingAIEnthusiast, it helps to understand the cognitive biases and reasoning errors that fuel the hype.

Benchmarks ≠ Intelligence

Kahneman's work exposed the substitution heuristic, where people answer a simpler (but not complete) question instead of the more complex (but correct) one. In AI, we often substitute "Can AI replace humans?" with "Has AI beaten a human on this benchmark?"

Benchmarks, while useful, shouldn't be seen as the be-all and end-all of measuring humans vs machines. Mapping artificial intelligence onto human intelligence by setting ever-harder benchmarks is like thinking you can reach the horizon by walking far enough. Properly evaluating AI's capabilities requires grasping its complexity, real-world problem-solving tasks, and the ill-defined context of human intelligence.