Probabilistic Knowledge and Cognitive Ability

Datos Bibliográficos

ID10696449
AutoresJason Konek (0000-0002-2658-9605, University of Kent, autor de correspondencia)
Año2016
Volumen125
Número4
Páginas509-587
Fecha de publicación2016-10-01
Peer ReviewedSí
Open AccessNo
TipoARTICLE
RevistaThe Philosophical Review (JOURNAL)
Identificadores de la revistaISSN: 0031-8108 • E-ISSN: 1558-1470
EditorialDuke University Press (PUBLISHER • US)
DOI10.1215/00318108-3624754
OpenAlexW2530570691
IdiomaEN
Citas recibidas14
Referencias citadas28

Sarah Moss (2013) argues that degrees of belief, or credences, can amount to knowledge in much the way that full beliefs can. This essay explores a new kind of objective Bayesianism designed to take us some way toward securing such knowledge-constituting credences, or “probabilistic knowledge.” Whatever else it takes for an agent's credences to amount to knowledge, their success, or accuracy, must be the product of cognitive ability or skill. The brand of Bayesianism developed here helps ensure this ability condition is satisfied. Cognitive ability, in turn, helps make credences valuable in other ways: it helps mitigate their dependence on epistemic luck, for example. What we end up with, at the end of the day, are credences that are particularly good candidates for constituting probabilistic knowledge. What's more, examining the character of these credences teaches us something important about what the pursuit of probabilistic knowledge demands from us. It does not demand that we give hypotheses equal treatment, by affording them equal credence. Rather, it demands that we give them equal consideration, by affording them an equal chance of being discovered

Character (mathematics) · Cognition · Credence · Epistemology · Luck · Machine learning · Probabilistic logic · Product (mathematics) · Artificial Intelligence · Bayesian Modeling and Causal Inference · Computer Science · Epistemology, Ethics, and Metaphysics · Mathematics · Philosophy · Philosophy and History of Science · Psychology