Contemporary epistemologists assume a view I call ‘comparabilism.’ They do not, however, argue for this view. I claim that noncomparabilism is a viable alternative. I further argue that noncomparabilism has advantages over comparabilism.

Proper functionalism claims that a belief has epistemic warrant only if it’s formed according to the subject’s truth-aimed cognitive design plan. The most popular putative counter-examples to proper functionalism all involve agents who form beliefs in seemingly warrant-enabling ways that don’t appear to proceed according to any sort of design. The Swampman case is arguably the most famous scenario of this sort. However, some proper functionalists accept that subjects like Swampman have warrant, opting instead to adopt a non-standard account of (...) design. But critics of proper functionalism hold that this strategy comes at a high cost: the design-plan condition now seems explanatorily superfluous. James Taylor construes cases like Swampman as posing a dilemma for the proper functionalist: either deny warrant in these cases and concede that proper functionalism doesn’t capture our intuitions, or affirm warrant and undermine the explanatory power of the design-plan condition. Proper functionalists have replied to both horns of this dilemma. Recently, Kenny Boyce and Andrew Moon have argued that warrant-affirming intuitions on cases like Swampman are motivated by a principle that has a clear counter-example. Also, Alvin Plantinga presents a set of cases that supposedly cause problems for any analysis of warrant that lacks a design-plan condition. In this essay, I present a counter-argument to Boyce and Moon’s argument, and show that a more robust reliability condition can accommodate Plantinga’s problem cases. I conclude that we’re left with no good reason to doubt that cases like Swampman raise a troubling dilemma for the proper functionalist. (shrink)

The generality problem is one of the most pressing challenges for reliabilism. The problem begins with this question: of all the process types exemplified by a given process token, which types are the relevant ones for determining whether the resultant belief counts as knowledge? As philosophers like Earl Conee and Richard Feldman have argued, extant responses to the generality problem have failed, and it looks as if no solution is forthcoming. In this paper, I present a new response to the (...) generality problem that illuminates the nature of knowledge-enabling reliability. My response builds upon the insights of Juan Comesaña’s well-founded solution to the generality problem, according to which relevant types are content–evidence pairs, i.e., descriptions of both the target belief’s content and the evidence on which the belief was based. While most responses to the generality problem, including Comesaña’s, only posit one relevant type for any given process token, I argue that knowledge-enabling reliability requires a process token to be reliable with respect to multiple content–evidence pairs, each with varying degrees of descriptive specificity. I call this solution multi-type evidential reliabilism. After offering a clear formulation of MTE, I conclude by arguing that MTE is sufficiently informative to rebut Conee and Feldman’s generality problem objection to a reliability condition on knowledge. (shrink)

The generality problem is commonly considered to be a critical difficulty for reliabilism. In this paper, we present a dynamical perspective on the problem in the spirit of naturalized epistemology. According to this outlook, it is worth investigating how token belief-forming processes instantiate specific types in the biological agent’s cognitive architecture and background experience, consisting in the process of attractor-guided neural activation. While our discussion of the generality problem assigns “scientific types” to token processes, it represents a unified account in (...) the sense that it incorporates contextual and common sense features emphasized by other authors. (shrink)

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. (shrink)

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. (shrink)

According to Intellectualism knowing how to V is a matter of knowing a suitable proposition about a way of V-ing. In this paper, I consider the question of which ways of acting might figure in the propositions which Intellectualists claim constitute the object of knowledge-how. I argue that Intellectualists face a version of the Generality Problem – familiar from discussions of Reliabilism – since not all ways of V-ing are such that knowledge about them suffices for knowledge-how. I consider various (...) responses to this problem, and argue that none are satisfactory. (shrink)

This article is concerned with a statistical proposal due to James R. Beebe for how to solve the generality problem for process reliabilism. The proposal is highlighted by Alvin I. Goldman as an interesting candidate solution. However, Goldman raises the worry that the proposal may not always yield a determinate result. We address this worry by proving a dilemma: either the statistical approach does not yield a determinate result or it leads to trivialization, i.e. reliability collapses into truth (and anti-reliability (...) into falsehood). Various strategies for avoiding this predicament are considered, including revising the statistical rule or restricting its application to natural kinds. All amendments are seen to have serious problems of their own. We conclude that reliabilists need to look elsewhere for a convincing solution to the generality problem. (shrink)