We address the generality problem for process reliabilism, i.e. the view that a subject knows the proposition p just in case p is true, the subject believes that p and, characteristically, the subject’s belief was acquired through a reliable process. The generality problem is that of classifying the type of process that was actually operative in belief acquisition. If no recipe for classification is given, reliabilism is an empty theory, or so the objectors claim. Our target is the account of the generality problem advanced in the influential work of Conee and Feldman. Specifically, we address their paradigm example of someone, Smith, seeing a maple tree from the window. We show that what we call basic level reliabilism, a reliabilism that relies on the basic level theory of (core) visual object recognition in cognitive psychology for fixing the process types in situations like that of Smith’s, satisfies Conee and Feldman’s own desiderata for an acceptable theory. We conclude that while Conee and Feldman may have succeeded in rebutting several other purported solutions to the generality problem in the paradigm case of visual object recognition, they have not produced anything that would present a challenge to basic level reliabilism.
Date: 19 September 2019
Time: 2pm to 4pm
Venue: Philosophy Meeting Room (AS3-05-23)
About the Speaker:
Erik J. Olsson is Professor and Chair in Theoretical Philosophy at Lund University, Sweden. His areas of research include epistemology, philosophical logic, pragmatism, and, more recently, epistemological aspects of social networks and search engines like Google. His books include Against Coherence: Truth, Probability, and Justification (Oxford University Press, 2005, paperback 2008), Knowledge and Inquiry: Essays on the Pragmatism of Isaac Levi (Cambridge University Press, 2006) and Belief Revision Meets Philosophy of Science (Springer, 2011). Olsson har written extensively on the reliabilist theory of knowledge, which he has defended against various objections. He is presently leading a research project funded by The Swedish Foundation for Humanities and Social Sciences investigating Google from the perspective of personalized search, filter bubbles and polarization.
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