Pretending Not to Know Reveals a Capacity for Model-Based Self-Simulation
Matan Mazor et al.
Abstract
Pretending not to know requires appreciating how one would behave without a given piece of knowledge and acting accordingly. Here, two game-based experiments reveal a capacity to simulate decision-making under such counterfactual ignorance. English-speaking adults (N = 1,001) saw the solution to a game (ship locations in Battleship, the hidden word in Hangman) but attempted to play as though they never had this information. Pretenders accurately mimicked broad aspects of genuine play, including the number of guesses required to reach a solution, as well as subtle patterns, such as the effects of decision uncertainty on decision time. Although peers were unable to detect pretense, statistical analysis and computational modeling uncovered traces of overacting in pretenders' decisions, suggesting a schematic simulation of their minds. Opening up a new approach to studying self-simulation, our results reveal intricate metacognitive knowledge about decision-making, drawn from a rich-but simplified-internal model of cognition.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.