Bits of Confidence: Metacognition as Uncertainty Reduction
Description
The ability of humans to assess the correctness of their own decisions via confidence judgments is a form of metacognition. This self-reflective act is essential for learning, memory, consciousness, group decision, and many other aspects of cognition. Researchers evaluate the quality of metacognition according to bias, sensitivity and efficiency. These are often measured with such quantities as meta - d’, or M-ratio by inferring the potential accuracy of the primary task from the secondary confidence rating performance. In the present study, I offer a comprehensive account of confidence judgments and metacognition, in terms of a communication system between stimuli, actor, rater, and experimenter. Several information theory techniques are harnessed to uncover the underlying components of information transmission between stimuli, actor and rater. Within this framework, I advance three independent measures of metacognitive sensitivity: meta − U, meta − KL, and meta − J . These are based on multivariate uncertainty analysis, and applications of the Kullback-Leibler and Jeffrey’s divergences to confidence-accuracy distributions. I then demonstrate the various desirable characteristics of these information-theory measures, and provide considerable evidence for their construct validity. In addition, I outline the structural and individual sources of metacognitive inefficiency, according to an information-theory model of communication. Keywords: Metacognition, Confidence, Information-theory, meta-d’, M-ratio, meta - I