TL;DRWharton researchers found people accept wrong AI answers 80% of the time. Now apps like Moot are monetising the instinct to outsource decisions.
A pair of Wharton researchers have put a name to something that many AI users have quietly started doing: letting chatbots make their decisions for them. Steven Shaw and Gideon Nave published a study in January titled “Thinking, Fast, Slow, and Artificial,” in which they introduced the term “cognitive surrender” to describe the tendency of people to defer to AI outputs even when those outputs are wrong.
The study, conducted through the Wharton School at the University of Pennsylvania, asked participants to answer questions with and without AI assistance. Those who received AI help accepted correct answers 93% of the time, which is unsurprising. What caught the researchers’ attention was the error rate: participants accepted incorrect AI answers 80% of the time, and reported confidence levels 11.7% higher than those who worked without AI.
The results came from controlled experimental conditions, not real-world usage, but the pattern was consistent across the sample.
Shaw and Nave proposed what they call “Tri-System Theory,” adding a “System 3” to the framework made famous by Daniel Kahneman’s “Thinking, Fast and Slow.” In their model, System 1 is fast intuition, System 2 is slow deliberation, and System 3 is AI-assisted cognition, a mode in which the human mind effectively outsources the work of thinking to a machine. The risk, they argue, is that System 3 gradually weakens Systems 1 and 2 through disuse.
