Pretending Not to Know Reveals a Capacity for Model-Based Self-Simulation

Area of Science:

• Cognitive Science
• Psychology
• Behavioral Economics

Background:

• Pretending ignorance involves simulating decision-making under counterfactual conditions.
• Understanding this capacity sheds light on metacognitive processes and self-simulation.

Purpose of the Study:

• To investigate the human ability to simulate decision-making while pretending to lack specific knowledge.
• To analyze the accuracy and characteristics of such simulated decision-making.

Main Methods:

• Two game-based experiments were conducted with 1,001 English-speaking adults.
• Participants were shown game solutions but instructed to play as if they were unaware.
• Behavioral data (guesses, decision time) were collected and analyzed using statistical and computational modeling.

Main Results:

• Pretenders accurately mimicked general aspects of genuine play, including solution time and patterns related to uncertainty.
• Decision uncertainty influenced decision time similarly in both genuine and pretended ignorance conditions.
• While peers could not detect pretense, statistical analysis revealed subtle "overacting" in pretenders' decisions.

Conclusions:

• Individuals possess a capacity for simulating decision-making under counterfactual ignorance.
• This simulation involves a schematic, simplified internal model of cognition.
• The findings offer a novel approach to studying self-simulation and metacognitive knowledge.