Preprints

Together with Rani and Clare, we propose a new way to model perceptual detection decisions (decisions about whether something is present or absent). Our model has only one sensor that is sensitive to the presence of a target image, and participants are assumed to observe this sensor and make decisions based on its output. This model exemplifies two principles. First, deciding that something is not there based on the sensor not activating is what philosophers call “an argument from ignorance”. And second, this makes decisions about absence strongly dependent on beliefs about the probability that the sensor would activate when the target image is present. The model fits well data from three detection experiments, and reveals that people vary in how much they take into account the properties of the sensor when making decisions about absence.

In order to pretend that I don’t know something, I need to mentally simulate what I would do if my knowledge were different than what it is. To do this, I rely on knowledge that I have about my own mind: metacognitive knowledge. Together with Chaz and Ian, we quantified people’s metacognition by measuring their ability to pretend they don’t know something. Specifically, we had them play rounds of Hangman (“reveal the hidden word with as few letter guesses as possible”) and Battleship (“reveal the hidden ships in the grid with as few cell guesses as possible”). We then compared their behaviour in real games against their behaviour in pretend games, in which we told them what the word was, or where the ships were hidden, but asked them to behave as they would if they didn’t have this information. We found a remarkable capacity for self-simulation, but also identified important limitations: pretenders had a tendency to over-act, and were sub-optimal in their taking-in of new information.