The distinction between true belief and knowledge is one of the most fundamental in philosophy, and a remarkable effort has been dedicated to formulating the conditions on which true belief constitutes knowledge. For decades, much of this epistemological undertaking has been dominated by a single strategy, referred to here as the modal approach. Shared by many of the most widely influential constraints on knowledge, including the sensitivity, safety, and anti-luck/risk conditions, this approach rests on a key underlying assumption — the (...) modal profiles available to known and unknown beliefs are in some way asymmetrical. The first aim of this paper is to deconstruct this assumption, identifying its plausibility with the way in which epistemologists frequently conceptualize human perceptual systems as excluding certain varieties of close error under conditions conducive to knowledge acquisition. The second aim of this paper is to then argue that a neural phase phenomenon indicates that this conceptualization is quite likely mistaken. This argument builds on the previous introduction of this neural phase to the context of epistemology, expanding the use of neural phase cases beyond relatively narrow questions about epistemic luck to a much more expansive critique of the modal approach as a whole. (shrink)

Suppose Ted is in an ordinary house in good viewing conditions and believes red, his table is red, entirely because he sees his table and its color; he also believes not-white, it is false that his table is white and illuminated by a red light, because not-white is entailed by red. The following three claims about this table case clash, but each seems plausible: 1. Ted’s epistemic position is strong enough for him to know red. 2. Ted cannot know not-white (...) on the basis of red. 3. The epistemic closure principle, suitably restricted, is true. Stewart Cohen has called this three-way clash of intuitions the problem of easy knowledge. If we wish to resolve the clash without accepting skepticism, we seem to have two options. According to the hard argument, the best response is to reject 3. The easy argument rejects 2. But there may be a third alternative, the reverse argument, which rejects 1 without ceding a substantial amount of ground to the skeptic. In this essay I criticize recent versions of the reverse argument and the hard argument, thereby lending support to the easy argument. (shrink)

In this paper, I develop a serious new dilemma involving necessary truths for safety-based theories of knowledge, a dilemma that I argue safety theorists cannot resolve or avoid by relativizing safety to either the subject’s basis or method of belief formation in close worlds or to a set of related or sufficiently similar propositions. I develop this dilemma primarily in conversation with Duncan Pritchard’s well-known, oft-modeled safety-based theories of knowledge. I show that Pritchard’s well-regarded anti-luck virtue theory of knowledge and (...) his recently proposed (allegedly superior) anti-risk virtue theory of knowledge clearly succumb to the dilemma, and so they are inadequate as they stand. If Pritchard’s safety-based theories of knowledge are shown to be inadequate by the dilemma that is developed in this paper, then a number of other safety-based theories of knowledge (e.g., Beddor and Pavese’s, Luper’s, Dutant’s, early Pritchard’s, and others) look to be in jeopardy in this connection as well. (shrink)

Philosophical Papers 36.1 (2007): 151-161.

Typical Gettieresque scenarios involve a subject, S, using a method, M, of believing something, p, where, normally, M is a reliable indicator of the truth of p, yet, in S’s circumstances, M is not reliable: M is deleteriously rigged. A different sort of scenario involves rigging that restores the reliability of a method M that is deleteriously rigged: M is restoratively rigged. Some theorists criticize the safe indication account of knowledge defended by Luper, Sosa, and Williamson on the grounds that (...) it treats such cases as knowledge. But other theorists also criticize the safe indication account because it treats the cases as examples of ignorance when they are really examples of knowledge. I answer both groups of critics by arguing that restorative rigging can enable us to know things, and restoratively rigged cases can meet the relevant conditions of the safe indication account. (shrink)