Algorithm and Parameters: Solving the Generality Problem for Reliabilism

Philosophical Review (forthcoming)
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Abstract
I offer a solution to the generality problem for a reliabilist epistemology, by developing an “algorithm and parameters” scheme for type-individuating cognitive processes. Algorithms are detailed procedures for mapping inputs to outputs. Parameters are psychological variables that systematically affect processing. The relevant process type for a given token is given by the complete algorithmic characterization of the token, along with the values of all the causally relevant parameters. The typing that results is far removed from the typings of folk psychology, and from much of the epistemology literature. But it is principled, empirically grounded, and shows good prospects for yielding the desired epistemological verdicts. I articulate and elaborate the theory, drawing out some of its consequences. Toward the end, I apply the fleshed-out theory to two important case studies: hallucination and cognitive penetration of perception.
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Archival date: 2019-03-09
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2019-03-09

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