A Naturalistic Approach to the Generality Problem

Olsson, Erik J

doi:10.1002/9781118609378.ch8

Cited by 11 publications

(8 citation statements)

References 35 publications

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“…Note that not every solution to the generality problem that looks different from A&P is a competitor to A&P. A&P is a theory about which processes determine the epistemic status of a belief. Some solutions to the generality problem (e.g., Jönsson 2013, Olsson 2016 are aimed at something quite different: a theory about what drives ordinary intuitive judgments of justifiedness. These two-actual epistemic status and intuitive judgment about epistemic status-needn't have too much to do with each other, especially on an externalist theory that denies that first-order justification depends on a reflective metajustification.…”

Section: Some Related Solutions To the Generality Problemmentioning

confidence: 99%

Algorithm and Parameters: Solving the Generality Problem for Reliabilism

Lyons

2019

The Philosophical Review

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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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Section: Some Related Solutions To the Generality Problemmentioning

confidence: 99%

Algorithm and Parameters: Solving the Generality Problem for Reliabilism

Lyons

2019

The Philosophical Review

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“…9 e.g., Becker (2008), Comesaña (2006) 10 e.g., Olsson (2016) 11 e.g., Wunderlich (2003) 12 e.g., Comesaña (2006), Schmitt (1992). See also Conee and Feldman (1998, pp.…”

Section: Beebe's Statistical Solutionmentioning

confidence: 99%

“…1360. 21 It is worth nothing that Olsson (2016) indeed looks elsewhere, namely, to experimental philosophy. While I think that there are significant disadvantages to Olsson's approach, I do not have the space to discuss them here.…”

Section: New Statistical Answer: For Any Process Token T T Is the Rementioning

confidence: 99%

“…Solutions have been proposed by Goldman (1986, pp. 49-51), Schmitt (1992), Alston (1995), Wunderlich (2003), Beebe (2004), Becker (2008), and Olsson (2016). But as Dutant and Olsson (2013) note: "although much work has gone into solving the Generality Problem, none of the proposals that have emerged so far has gained widespread acceptance" (p. 1351).…”

Section: Introductionmentioning

confidence: 99%

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A New Statistical Solution to the Generality Problem

Kampa¹

2017

Episteme

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The Generality Problem is widely recognized to be a serious problem for reliabilist theories of justification. James R. Beebe's Statistical Solution is one of only a handful of attempted solutions that has garnered serious attention in the literature. In their recent response to Beebe, Julien Dutant and Erik J. Olsson successfully refute Beebe's Statistical Solution. This paper presents a New Statistical Solution that countenances Dutant and Olsson's objections, dodges the serious problems that trouble rival solutions, and retains the theoretical virtues that made Beebe's solution so attractive in the first place. There indeed exists a principled, rigorous, conceptually sparse, and plausible solution to the Generality Problem: it is the New Statistical Solution.

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“…The empirical study in Jönsson (2013) concluded, by contrast, that people often converge on judgements of reliability in normal cases. See also Olsson (2016) for a discussion of this aspect of the so-called generality problem for reliabilism.…”

Section: Principle E4 (Data Prioritymentioning

confidence: 99%

Explicationist Epistemology and Epistemic Pluralism

Olsson

2017

Epistemic Pluralism

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I discuss Carnap's method of explication with special emphasis on its application to epistemology. I observe that explication has the advantage over conceptual analysis of not being vulnerable to the so-called paradox of analysis. Moreover, explicationist epistemology is intrinsically immune to the Gettier problem. I proceed to identify three senses in which the former is inherently pluralistic. For example, it allows for a plurality of legitimate and potentially interesting epistemological projects. Finally, I argue that while there are salient affinities with Alston's theory of epistemic desiderata, beyond a far-reaching commitment to pluralism, there are also important differences. Above all, Carnap's methodological outlook is reconstructive in ways in which Alston's is not.

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A Naturalistic Approach to the Generality Problem

Cited by 11 publications

References 35 publications

Algorithm and Parameters: Solving the Generality Problem for Reliabilism

Algorithm and Parameters: Solving the Generality Problem for Reliabilism

A New Statistical Solution to the Generality Problem

Explicationist Epistemology and Epistemic Pluralism

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