Confidence biases and learning among intuitive Bayesians - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Theory and Decision Année : 2018

Confidence biases and learning among intuitive Bayesians

Résumé

We design a double-or-quits game to compare the speed of learning one’s specific ability with the speed of rising confidence as the task gets increasingly difficult. We find that people on average learn to be overconfident faster than they learn their true ability and we present an intuitive-Bayesian model of confidence which integrates confidence biases and learning. Uncertainty about one’s true ability to perform a task in isolation can be responsible for large and stable confidence biases, namely limited discrimination, the hard–easy effect, the Dunning–Kruger effect, conservative learning from experience and the overprecision phenomenon (without underprecision) if subjects act as Bayesian learners who rely only on sequentially perceived performance cues and contrarian illusory signals induced by doubt. Moreover, these biases are likely to persist since the Bayesian aggregation of past information consolidates the accumulation of errors and the perception of contrarian illusory signals generates conservatism and under-reaction to events. Taken together, these two features may explain why intuitive Bayesians make systematically wrong predictions of their own performance.
Fichier principal
Vignette du fichier
template.pdf (733.46 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01558394 , version 1 (07-07-2017)

Identifiants

Citer

Louis Lévy-Garboua, Muniza Askari, Marco Gazel. Confidence biases and learning among intuitive Bayesians. Theory and Decision, 2018, 54, pp.453-482. ⟨10.1007/s11238-017-9612-1⟩. ⟨hal-01558394⟩

Relations

337 Consultations
1845 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More