Algorithm and Parameters: Solving the Generality Problem for Reliabilism

Philosophical Review 128 (4):463-509 (2019)
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Abstract

The paper offers 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 and empirically grounded, and shows good prospects for yielding the desired epistemological verdicts. The paper articulates and elaborates the theory, drawing out some of its consequences. Toward the end, the fleshed-out theory is applied to two important case studies: hallucination and cognitive penetration of perception.

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Author's Profile

Jack Lyons
University of Glasgow

Citations of this work

Reliabilist Epistemology.Alvin Goldman & Bob Beddor - 2021 - Stanford Encyclopedia of Philosophy.
Knowledge, practical knowledge, and intentional action.Joshua Shepherd & J. Adam Carter - 2023 - Ergo: An Open Access Journal of Philosophy 9:556-583.
Why is Warrant Normative?Peter J. Graham - 2019 - Philosophical Issues 29 (1):110-128.

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References found in this work

Thinking, Fast and Slow.Daniel Kahneman - 2011 - New York: New York: Farrar, Straus and Giroux.
The Predictive Mind.Jakob Hohwy - 2013 - Oxford, GB: Oxford University Press UK.
Philosophical explanations.Robert Nozick - 1981 - Cambridge, Mass.: Harvard University Press.

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