## 1. A Paradigm Shift in Analytic Epistemology



In the 1960s, a wide range of epistemologists were absorbed by the
question: what does it take for a belief to amount to
*knowledge*? It was generally agreed that for a person,
*S*, to *know* some proposition *p*, at least three
conditions must be met. First, *p* must be true. Second, *S*
must believe *p*. And third, *S* must be *justified*
in believing *p*. Thus, knowledge requires *justified true
belief.* But does the satisfaction of these three conditions
suffice to entail that *S* *knows* *p*?
Unfortunately, as Edmund Gettier (1963) showed with several convincing
cases, justified true belief doesn't guarantee knowledge.



Some subsequent attempts to explicate knowledge had broadly
"reliabilist" features, although they did not use this
terminology. According to "relevant alternatives
theories", a subject is said to know *p* provided that they
can "rule out" relevant alternatives where *p* does
not obtain (Dretske 1970; Goldman 1976; Stine 1976; Lewis 1996).
According to "truth-tracking theories", a subject knows
*p* provided their beliefs "track the truth" of
*p* across modal space. Truth-tracking theorists typically cash
this out in terms of subjunctive conditionals, such as
"Sensitivity": *If *p* had been false, *S*
wouldn't have believed p* (Nozick 1981), or
"Safety": If *S* were to believe *p*, *p*
would be true (Sosa 1999; Williamson 2000; Pritchard 2005). These
views are united by the idea that knowledge requires some form of
reliability. (See the entry on the
 analysis of knowledge.)



Meanwhile, many epistemologists have turned their attention to a
related epistemic concept: the concept of (epistemic)
*justification.* Justified belief is widely regarded as a
*necessary*--though insufficient--condition for
knowledge. Hence, justification must be regarded as a core concept for
epistemologists to explore and elucidate.



However, justification also proves to be a very elusive concept. In
1979 Alvin Goldman published a paper entitled "What Is Justified
Belief?", which departed from several well-entrenched positions
on the nature of epistemic justification. Years later, a number of
epistemologists recognized this paper as marking a significant turning
point, or "paradigm shift", in epistemology. Michael
Williams (2016: 3) called it "the Reliabilist Revolution".
This turning point has given rise to a lively debate about the kinds
of factors that determine the epistemic status of a person's
beliefs or credences.


### 1.1 The Basic Components: The Reliability of Mental Processes in Determining True vs. False Beliefs



The key idea behind Goldman's reliabilist approach is that the
justifiedness of a belief depends on the mental *history* of
the subject's belief. In particular, it depends on the
reliability of the process(es) which *cause* the belief in
question. Somewhat similar ideas (or segments thereof) have been
advanced by a number of predecessors, often focusing on knowledge
rather than justification. Frank Ramsey (1931) wrote that a belief
qualifies as *knowledge* if it is true, certain, and obtained
by a reliable process. He did not, however, provide a detailed defense
of this thesis. Peter Unger (1968) proposed that *S* knows that
*p* just in case "it is not at all accidental" that
*S* is right about its being the case that *p*. David
Armstrong (1973) offered an analysis of non-inferential knowledge that
explicitly used the term "reliable". He drew an analogy
between a thermometer that reliably indicates the temperature and a
belief that reliably *indicates* the truth. All of these
writers seemed to endorse some variant of *reliabilism*,
although typically there were minor or major differences from the
version we shall focus on here. For example, Armstrong promoted an
"indicator" variant of reliabilism rather than a
"psychological process" variant. And Unger presented
"non-accidentality" rather than
"truth-conduciveness" as the central determinant of
justifiedness. Clearly, however, there is a great deal of convergence
in these views. So, contemporary defenders of epistemic reliabilism
have grounds for optimism that they are laboring in promising terrain.
The nitty-gritty details, however, still need additional work, as we
shall see in the body of this entry. We turn now to some of the
principal details of Goldman's form of reliabilism for
justification (Goldman, 1979, 1986).



Goldman began by proposing some desiderata on any account of
justification. First, theories of justification should specify
conditions for justified belief that do not invoke the concept of
justification itself, or any other epistemically normative concepts
such as reasonability or rationality. The aim is to provide a
"reductive" account of justification that does not appeal
explicitly or implicitly to any notions that entail justification or
other members of that family. There is bite in this requirement. For
example, it might preclude an analysis of justified belief in terms of
"evidence", unless evidence can itself be characterized in
non-epistemic terms. What kinds of terms or properties, then, are
appropriate for constructing an account of justification? Permissible
concepts or properties would include doxastic ones, such as belief,
disbelief, suspension of judgment, and any other purely psychological
concepts, such as ones that refer to perceptual experience or memory.
Given the assumption that truth and falsity are non-epistemic notions,
they would also be perfectly legitimate for use in analyzing
justifiedness. Another admissible element in an account of
justifiedness is the causal relation.



Proceeding under these constraints, Goldman was led to the
"reliable process" theory as follows. (Note that the main
concept to be tackled here is *doxastic* justifiedness rather
than *propositional* justifiedness. That is, it focuses on what
it takes for a belief to *be* justified rather than what it
takes for someone to have *grounds* for forming such a belief.)
First, examples were adduced to show that the justifiedness of
particular beliefs depends on how those beliefs are *caused,*
or *causally sustained,* in the mind of the thinker. Suppose
Arthur justifiedly believes a conjunction of propositions, \(q \amp
r\), from which proposition \(p\) follows logically. Further suppose
that, soon after forming his belief in this conjunction, Arthur also
forms a belief in \(p\). Does it follow from this that Arthur's
belief in \(p\) is justified? No. Although Arthur believes \(q \amp
r\), this conjunction may not have played any causal role in his
coming to believe \(p\). He may have formed his belief in \(p\) purely
by wishful thinking. Perhaps he *hoped* \(p\) would be true,
and therefore (somehow) came to believe it. Alternatively, suppose
Arthur employed confused reasoning that began with \(q \amp r\), and
serendipitously led to \(p\). In neither case is his resulting belief
in \(p\) justified. This shows that a necessary condition for a belief
to be justified is that it be *produced* or *generated*
in a *suitable* way. Of course, this immediately raises the
question: which kinds of belief-forming processes are suitable and
which are defective or unsuitable?



One feature that is shared by wishful thinking and confused reasoning
is doxastic unreliability. These belief-forming methods commonly
generate beliefs that are false rather than true. By contrast, what
types of belief-forming processes commonly confer justification? They
include standard perceptual processes, remembering, good reasoning,
and introspection. What is shared by these processes? What they share
is reliability: most of the beliefs they produce are true. (This
formulation will be slightly refined later.) Thus, the central
proposal made in "What Is Justified Belief" is that the
justifiedness or unjustifiedness of a belief is determined by the
reliability or unreliability of the process or processes that cause
it. Reliability can here be understood either in a *frequency*
sense (pertaining to what occurs in the actual world) or in a
*propensity* sense (pertaining both to the actual-world and
other possible worlds.). A belief earns the status of
"justified" if it is produced by a process (or series of
processes) that has a high truth-ratio. Precisely how high a
truth-ratio must be in order to confer justifiedness is left vague,
just as the concept of justification itself is vague. The truth-ratio
threshold need not be as high as 1.0, but it must surely be greater
(presumably, quite a lot greater) than .50.



A number of conclusions were drawn from these main points, and
refinements were added. One consequence was that process reliabilism
is a historical type of theory. For example, a reliable inferential
process confers justification on a new belief only if the input
beliefs (premises) were themselves justified. How could the
justifiedness of these input beliefs have arisen? Presumably, their
justifiedness arose because they were produced by earlier applications
of reliable processes. Such a chain of processes must ultimately
originate from one or more reliable processes that themselves had no
doxastic inputs. Perceptual inputs are good candidates for such
processes. So, on this approach, justifiedness is often a product of a
history of personal cognitive processes. The historical framework of
such a process theory contrasts sharply with more traditional
epistemological frameworks, such as coherentism and (certain versions
of) evidentialism. According to these more traditional theories,
causal and historical relations play no role in determining
justifiedness. (Though see, e.g., Goldberg 2012 and Fleisher 2019 for
views that combine elements of coherentism and reliabilism; for views
that integrate evidentialism and reliabilism, see
 SS4.2
 below.) More generally, reliabilism marks an important break with
"current time-slice" approaches, according to which the
epistemic status of a belief at time *t* depends entirely on the
subject's mental states at *t*.



These fundamental ideas were spelled out by Goldman in "What Is
Justified Belief?" (1979), in a series of principles including
base-clause principles and recursive-clause principles. The initial
one was (1):



(1)
If *S*'s belief in *p* at *t* is a product of
a reliable cognitive belief-forming process (or set of processes),
then *S*'s belief in *p* at *t* is
justified.


This principle would fit cases of perceptually caused beliefs and
other beliefs that make no use of prior doxastic states (as inputs).
But inference-generated beliefs require a different principle. When a
new belief results from an inference, its justificational status
depends not only on the properties of the inferential
*process,* but also on whether the input beliefs themselves
were justified. To accommodate this, a slightly more complex principle
was introduced:



(2)
If *S*'s belief in *p* results from a
*conditionally* reliable belief-dependent process, and if the
beliefs on which this process operated in generating *S*'s
belief in **P* are themselves justified, then*
*S*'s new *belief in *P** is also
*justified.*


By philosophical standards, these are not terribly complex principles.
Thus, process reliabilism is a comparatively simple and
straightforward theory. Such simplicity has usually been viewed as a
virtue of the approach. Of course, matters are more complicated than
the foregoing principles convey. We will survey some potential
complications and refinements of this theory below.


### 1.2 Justified vs. Unjustified Beliefs: Some Examples



Is it true, as process reliabilism claims, that beliefs formed by
reliable processes are (intuitively) considered justified and that
beliefs formed by unreliable processes are (intuitively) considered
unjustified? Here are some examples of processes that frequently lead
to false beliefs: wishful thinking, reliance on emotional attachment,
mere hunch or guesswork, and hasty generalization. Beliefs produced by
such processes would all be considered, intuitively, unjustified. So
there is a high correlation between process-unreliability and
unjustifiedness. Similarly, here are some examples of processes that
commonly lead to true beliefs: standard perceptual processes, good
reasoning, and introspection. Here again there is a strong correlation
between process-reliability and justified belief.



We should notice, of course, that justifiedness is not a purely
categorial concept. We can and do regard certain beliefs as more
certain and more justified than others. Furthermore, our intuitions of
comparative justifiedness go along with our beliefs about the
comparative reliability of the belief-causing processes (Goldman 1979;
1986: 103-4; 1992; 2008). This comports well with process
reliabilism.


## 2. Challenges and Replies



By now, a number of problems have been raised for process reliabilism.
Here we review some of the main challenges, focusing on the three that
have received the most attention in the literature: the clairvoyance
problem
 (SS2.1),
 the new evil demon problem
 (SS2.2),
 and the generality problem
 (SS2.3).
 Afterwards, we will briefly survey some challenges of a more recent
vintage
 (SS2.4).


### 2.1 The Clairvoyance Problem



One early challenge to reliabilist theories of justification was
advanced by Laurence BonJour (1980), concerning a hypothetical
clairvoyant named "Norman". Norman has a perfectly
reliable clairvoyance faculty. But he has no evidence or reasons for
or against the general possibility of a clairvoyant power or for or
against *his* possessing such a power. One day Norman's
clairvoyance faculty generates in him a belief that the President is
currently in New York City, but with no accompanying perception-like
experience, just the bare belief itself. Intuitively, says BonJour,
Norman isn't justified in holding this belief. Yet process
reliabilism seems to imply otherwise. Since Norman's clairvoyant
power has a high truth ratio, Norman's belief about the
President must be justified. So reliabilism seems to get this wrong.
(Similar examples were offered by Keith Lehrer (1990) and Alvin
Plantinga (1993).)



Reliabilists have offered various responses to this challenge,
including:


#### Approved List Reliabilism



One response is to opt for a variant of simple process reliabilism,
which goes by the names of "two-stage reliabilism"
(Goldman 1992) or "approved-list reliabilism" (Fricker
2016). Rather than directly giving an account of what justification
is, this approach seeks to give a theory of how ordinary people make
justification attributions. Approved-list reliabilists offer the
following conjecture about how this works. In a preliminary stage,
attributors form opinions about the reliability or unreliability of
assorted belief-forming processes, using observation and/or inference
to draw conclusions about the track-records of these processes in the
actual world. They thereby construct mental lists of reliable and
unreliable processes: lists of approved and disapproved processes
(respectively). In the second stage, they deploy these lists to make
judgments about particular beliefs (actual or hypothetical). If
somebody's belief was caused by a process that is on their
approved list--or strongly resembles one on their approved
list--they consider it justified. If it is caused by a process on
their disapproved list, it is classed as unjustified.



How would approved-list reliabilism explain intuitive judgments in the
clairvoyance case? Presumably, an ordinary attributor would not have a
clairvoyance process on either of her lists. But she might well have
processes like *extra-sensory-perception* or
*telekinesis* on her list, especially her disapproved list. The
process or faculty that Norman uses to arrive at his belief about the
President sounds very similar to one of those obscure and suspect
powers. Hence, Norman's belief is intuitively classified as
unjustified. This is despite the fact that--as potential
attributors are told--Norman's clairvoyance process is
thoroughly reliable.



Approved list reliabilism is a theory of the factors that influence
our *attributions* of epistemic justification. It is thus
naturally construed as an *attributor theory*--a theory of
the conditions under which a justification attribution (that is, a
sentence of the form, "*S* is justified in believing
*p*") is judged to be true or false. In this regard, it
parallels attributor theories of knowledge (e.g., DeRose 1992). There
are different ways of developing an approved list attributor theory
more precisely. For instance, a contextualist implementation might
hold that a justification attribution is true if and only if the
subject's belief-forming process belongs to the speaker's
approved list. Alternatively, one could adopt an assessor-relativist
implementation, according to which the truth-conditions of
justification attributions are relativized to contexts of assessment
(cf. MacFarlane 2005). An assessor-relativist version of the approved
list might hold that a justification attribution is true at a context
of assessment if and only if the subject's belief-forming
process belongs to the assessor's approved list.


#### Appealing to Primal Systems



A different response to the clairvoyance problem is to concede that
being the result of a reliable process is not sufficient for a belief
to be *prima facie* justified. Rather, some further condition
must be met. One version of this approach has been developed by Jack
Lyons (2009, 2011) who argues that in order for a non-inferential
belief to be justified, it must be the result of a "primal
system". Drawing on research in cognitive science, Lyons
proposes that a primal system is any cognitive system that meets two
conditions: (i) it is "inferentially opaque"--that
is, its outputs are not the result of an introspectively accessible
train of reasoning, (ii) it develops as a result of a combination of
learning and innate constraints (2009: 144). For Lyons, our perceptual
systems are paradigmatic examples of such primal systems.



How does this help with the clairvoyance objection? According to
Lyons, BonJour's presentation of the Norman example invites the
assumption that Norman's clairvoyance was the result of some
recent development--e.g., "a recent encounter with
radioactive waste" or a "neurosurgical
prank"--not the result of some combination of learning and
innate constraints (2009: 118-119). Given this assumption,
Norman's clairvoyance-based belief is not the result of a primal
system, hence it is not *prima facie* justified.



A third possible response to the clairvoyance objection--which
involves combining reliabilism with evidentialist elements--will
be discussed in
 SS4.2
 below.


### 2.2 The New Evil Demon Problem



A second problem for process reliabilism is the "new evil-demon
problem" (Cohen 1984; Pollock 1984; Feldman 1985; Foley 1985).
Imagine a world where an evil demon creates non-veridical perceptions
of physical objects in everybody's minds. All of these
perceptions are qualitatively identical to ours, but are false in the
world in question. Hence, their perceptual belief-forming processes
(as judged by the facts in that world) are unreliable; and their
beliefs so caused are unjustified. But since their perceptual
experiences--hence evidence--are qualitatively identical to
ours, shouldn't those beliefs in the demon world be
justified?


#### Approved List Reliabilism



As with the clairvoyance objection, one response is to move from
simple reliabilism to approved list reliabilism (see
 SS2.1
 above). As before, approved-list reliabilists will maintain that a
potential attributor constructs lists of belief-forming processes, one
for approved process types and one for disapproved types. Perceptual
processes (of various sorts) would be on the approved list. Since the
people in the evil-demon case use perceptual processes that would be
on the approved list, an attributor would consider their resulting
beliefs justified--even though s/he is told that the perceptual
processes in the evil-demon world are unreliable.


#### Indexical Reliabilism



A number of philosophers have explored related ideas for solving the
New Evil Demon Problem. One similar strategy starts by distinguishing
two different ways a process can be reliable. Suppose we inhabit the
actual world (@), and we're evaluating a subject *S* who
inhabits some other world \(w\_s\). Then there are two different things
we could mean when we say that *S*'s belief-forming process
is reliable: we could mean that it's reliable relative to @, or
we could mean that it's reliable relative to \(w\_s\) (Sosa 1993,
2001). Comesana (2002) uses this distinction to provide a
solution to the new evil demon problem cast in the framework of
two-dimensional semantics (Stalnaker 1999). On Comesana's
proposal, the sentence, "*S* is justified in believing
*p*" has two readings: (i) that *S*'s
belief-forming process is reliable relative to @, (ii) that
*S*'s belief-forming process is reliable relative to
\(w\_s\). If \(w\_s\) is a demon world, then reading (i) will be true,
but reading (ii) is false. While Comesana's use of
two-dimensional semantics has drawn criticism (Ball &
Blome-Tillman 2013), the basic strategy of solving the New Evil Demon
problem by appealing to two types of reliability remains popular. For
discussion of a related approach, see the discussion of normality
reliabilism in
 SS3.1 below.


#### Denying justification in Demon Worlds



The foregoing responses seek to accommodate the claim that the person
in the demon world has justified beliefs (call this the "New
Evil Demon Claim"). Another response is to reject this claim.
One way of motivating the New Evil Demon Claim is by appealing to the
premise that the person in the new evil demon scenario has the very
same evidence that we do at the actual world. However, some
philosophers reject this premise in favor of an externalist conception
of evidence. For example, Williamson (2000: ch. 9) suggests that an
agent's evidence is just their knowledge. Since the victim of an
evil demon knows less than we do, it follows that they have less
evidence than we do. As Schellenberg (2016) emphasizes, this sort of
view is compatible with claiming that there is *some* evidence
that both we and the demon victim have in common. It's just that
there is further body of evidence that we possess but the demon victim
lacks. This sort of responses raises larger questions about what
reliabilists should say about the nature of evidence; for further
discussion, see
 SS4.2
 below.



Philosophers who go this route typically emphasize that the beliefs of
the person at the demon world have some positive status, even if this
status falls short of justification. For example, Lyons (2013) points
out that the inferential beliefs of the demon's victim are
formed by conditionally reliable processes, which is an epistemic good
in its own right. Other philosophers have claimed that the beliefs of
the demon's victim are blameless or excusable, even though they
are not justified (e.g., Pritchard 2012a). This issue is closely
related to a growing recent literature on the relationship between
epistemic justification and epistemic blamelessness (see, e.g., Kelp
& Simon 2017; Brown 2018; D. Greco forthcoming; Williamson
forthcoming).


### 2.3 The Generality Problem



Perhaps the most widely discussed problem for process reliabilism is
the generality problem. Originally anticipated by Goldman in
"What Is Justified Belief?", it has been pressed more
systematically by Feldman (1985) and Conee and Feldman (1998). Any
particular belief is the product of a token causal process in the
subject's mind/brain, which occurs at a particular time and
place. Such a process token can be "typed", however, in
many broader or narrower ways. Each type will have its own associated
level of reliability, often distinct from the levels of reliability of
other types it instantiates. Which repeatable type should be selected
for purposes of assigning a reliability number to the process token?
If no (unique) type can be selected, what establishes the
justificatory status of the resulting belief?



Consider a concrete example (Conee & Feldman 1998): Smith sees a
maple tree outside his window one sunny afternoon and forms the belief
that there is a maple tree near his house. How should we type his
belief-forming process? Is the relevant type *vision*? Or
perhaps something more fine-grained, such as *visual experience of
a maple tree on a sunny afternoon*? Or is it something more
coarse-grained, such as *perception*? The worry is that
Smith's token belief-forming process seems to instantiate all
these process types (and many more). So singling out any single one of
them as the "right" way of typing the process seems
arbitrary.



Reliabilists have proposed various strategies for dealing with the
generality problem. Some of the main responses include:


#### Psychological Approaches (Alston 1995; Beebe 2004; Kampa 2018; Lyons 2019)



Not every way of describing a belief-forming process carves
psychological reality at its joints. Consider, for example, the
process type, *forming a perceptual belief while wearing green
socks.* Intuitively, this is an "inappropriate" or
"irrelevant" way of describing Smith's
belief-forming process. But why is it inappropriate? According to
psychological approaches, it is inappropriate because it mentions
features of Smith's circumstances that play no causal role in
the psychological processes responsible for his belief.



In their 1998 discussion of the generality problem, Conee and Feldman
acknowledge that turning to psychology will help winnow down the
number of eligible process types. But they express skepticism that it
will always yield a unique process type. Why won't there be
multiple psychologically "real" process types responsible
for a given belief token? Subsequent developments of the psychological
approach have tried to address this worry. For example, Beebe (2004)
proposes that the relevant process type will always be an
information-processing procedure or algorithm. Of course, there will
often be indefinitely many types of this kind, of varying reliability.
To pick out the appropriate type, Beebe offers the following
instructions. Let *A* be the broadest such type. Choose a
partition that is the broadest objectively homogeneous subclass of
*A* within which the token process falls, where a class is
objectively homogeneous if no statistically relevant partition of it
can be effected. Beebe's proposal has been challenged by Dutant
and Olsson (2013), who argue that it faces a dilemma: either it does
not always yield a unique process type or it leads to trivialization
by collapsing reliability into truth. For a more recent variant of
Beebe's solution, aimed at addressing Dutant and Olsson's
concerns, see Kampa (2018).



Perhaps the most fully developed version of a psychological approach
to the generality problem comes from Lyons (2019). Lyons agrees with
Beebe that the relevant psychological process types are
information-processing algorithms. But Lyons additionally suggests
that these algorithms need to be relativized to *parameters*,
understood as psychological variables that affect processing in a
law-like way. For example, *lighting conditions* are a
parameter that affects the speed and accuracy of visual information
processing. As Lyons develops this view, the appropriate process type
for a given belief token *B* is provided by the complete
algorithmic specification of every psychological process that is
causally relevant to *B*, along with the parameter values for all
of these processes. As Lyons notes, one upshot of this approach is
that the relevant process types will typically be very fine-grained.
Smith's belief-forming process type will not be *vision*,
but something more like: *visual recognition of objects based on
retinal stimulus of sort *S*, in lighting conditions *C*,
with attention distributed in manner *M**.


#### Parrying Responses (Comesana 2006; Bishop 2010; Tolly 2017)



A different approach to the generality problem is to insist that a
version of the problem arises for any adequate epistemology, not just
reliabilists. A version of this "parrying response" has
been developed by Juan Comesana (2006), who argues that every
account of doxastic justification needs to appeal to the basing
relation. This is true even of evidentialist accounts: after all,
evidentialists maintain that in order for a belief *B* to be
doxastically justified, *B* needs to be based on a body of
evidence that supports *B*. (More on evidentialism in
 SS4.2
 below.) But, Comesana argues, any attempt to characterize the
basing relation will run into the generality problem, or something
very similar to it. Moreover, Comesana contends, if
evidentialists are willing to simply take for granted some notion of
basing in their theory, then there is no reason why reliabilists
cannot follow suit, and deploy the basing relation in their solution
to the generality problem.



A rather different parrying response has been defended by Michael
Bishop (2010), who argues that the problem will arise for any theory
that allows for the possibility of "reflective
justification"--that is, having a belief *B* that is
justified on the basis of one's knowledge that one formed
*B* via a reliable form of reasoning. For further discussion, see
Matheson (2015) and Tolly (2017).



Both Comesana and Bishop focus on the idea that all
*epistemologists* face a version of the generality problem. A
related but distinct idea is to insist that versions of the generality
problem crop up everywhere, not just in epistemology. This response
has been developed recently by Goldman (forthcoming), who points out
that we regularly evaluate the reliability of all sorts of processes,
not all of them cognitive. Goldman illustrates with the example of
Geraldine, who enjoys shooting hoops at her local gym.
Geraldine's performance is a function of many factors, including
how she focuses her eyes on the target hoop, how she grips the ball,
how she selects an angle to hit the backboard, etc. Now consider
Geraldine's friend, Henry, who watches as Geraldine consistently
sinks more than 80% of her shots, using roughly the technique each
time. Henry may not be able to provide a detailed specification of
Geraldine's hoop-shooting process. Nonetheless, it seems he is
in a position to conclude that Geraldine uses *some* process
type that is responsible for her frequent attainment of her athletic
goal, and that this process is fairly reliable.



Goldman (forthcoming) argues that these considerations carry two
lessons. First, they show that the generality problem is very general,
since some version of it arises in non-epistemic contexts. Second,
Goldman takes these considerations to cast doubt on the common
assumption--voiced explicitly by Conee and Feldman (1998:
2-3)--that an adequate solution to the generality problem
will need to specify a unique process type responsible for any and
every token belief. According to Goldman, an evaluator can correctly
(and justifiably) describe a process as reliable, without being able
to specify in any detail the sort of process type at issue.


#### "Common Sense" Typing Approaches (Goldman 1979; Jonsson 2013; Olsson 2016)



Yet another strategy is to switch tack and inquire into how ordinary
people type belief-forming processes. Suppose we ask a person on the
street, "How did Smith form his belief?" Chances are,
they'll answer "vision", not "visual
experience of a maple tree on a Tuesday afternoon while
wearing..." Inspired by this observation, common sense
approaches seek to solve the generality problem in two steps. *Step
One:* develop a psychological theory of how ordinary people type
belief-forming processes. *Step Two:* Use these "common
sense" typing methods to winnow down the range of candidate
process types.



A version of this approach has been elaborated by Erik Olsson (2016),
who appeals to a well-supported psychological theory about
conceptualization called *basic-level* theory, developed by
Eleanor Rosch in the 1970s (Rosch et al. 1976). Rosch and her
collaborators studied the deployment of taxonomically related concepts
like "animal", "dog", and
"labrador". In such a taxonomy, one term is a
superordinate concept ("animal"), another is an
intermediate-level concept ("dog"), and a third is a
subordinate concept ("labrador"). It turns out that
intermediate-level concepts are overwhelmingly preferred in free
naming tasks (e.g., "What would you call this?"). For
example, in one study Rosch et al. found that, out of 540 responses,
530 to 533 converged on the same intermediate-level word for naming a
physical object. Olsson suggests that ordinary people might similarly
tend to converge on an intermediate-level concept when typing
belief-forming processes. This conjecture has been empirically
supported in work by Jonsson (2013). Jonsson showed subjects
clips in which characters arrived at various conclusions, and then
asked the subjects to specify how the characters arrived at their
beliefs. Subjects converged on the choice of verbs describing the
belief-formation processes, even without linguistic cues to guide the
process-typing task. Jonsson also found a correlation between
subjects' estimates of the reliability of the characters'
belief-forming processes and subjects' judgments about whether
the characters were justified in holding the beliefs in question. Thus
there is some evidence that folk psychological propensities lead us to
converge on belief-typing tasks, and that our reliability assessments
track our justification judgments.


### 2.4 Further Challenges to Reliabilism



In addition to these three main objections, a number of further
challenges have been raised for reliabilism, including the three that
follow.


#### The Bootstrapping Problem



Consider the following case, due to Vogel (2000): Roxanne is a driver
who believes whatever her gas gauge says about the state of her fuel
tank, although she has no antecedent reasons to believe it is
reliable. So Roxanne often looks at the gauge and arrives at
conjunctive beliefs like the following: *On this occasion the gauge
reads "Full" & the tank is full.* Now, the
perceptual process by which she arrives at the belief that the gauge
reads "Full" is reliable, and so is the process by which
she arrives at the belief that the tank is full (given that the gauge
functions reliably). According to reliabilism, therefore, her belief
in the indicated conjunction should be justified. Now Roxanne deduces
the proposition, *On this occasion, the gauge is reporting
accurately*. From multiple instances of this reasoning, she
induces the further conclusion: *The gauge is generally
reliable.* Finally, with a little more deduction she concludes she
is *justified in believing* that her gas tank is full. Since
deduction and induction are reliable processes, Roxanne must also be
justified in believing that her gas gauge is full. But is this verdict
plausible? Definitely not, says Vogel, because such bootstrapping
amounts to a vicious form of epistemic circularity.



In response to this problem, we should start by noting that this
problem is not specific to reliabilism (Cohen 2002). Indeed, the
problem arises for all theories that allow for "basic
justification"--that is, justification that is obtained via
some process or method *X* without antecedent justification for
believing that *X* is reliable. As van Cleve (2003) forcefully
argues, theories that do not allow for basic justification seem to
lead to wide-ranging skepticism.



If we wish to allow for basic justification, can we still give a
principled explanation of why some forms of bootstrapping seem
illegitimate (for example, the case of Roxanne)? This is an area of
active research. One suggestion is that illegitimate forms of
bootstrapping involve *No Lose Investigations*. Roughly, a No
Lose Investigation into a hypothesis \(h\) is an investigation that
could never, in principle, count against \(h\). (For suggestions along
these lines, see Kornblith 2009; Titelbaum 2010; Douven & Kelp
2013.) Another suggestion is that illegitimate forms of bootstrapping
all involve *epistemic feedback* (Weisberg 2010). Suppose an
agent believes premises \(p\_1\) ... \(p\_n\) from which she infers
lemmas \(l\_1\) ... \(l\_n\), from which she in turn infers a
conclusion \(c\). Epistemic feedback is present when the probability
of \(c\) conditional on \(l\_1\) ... \(l\_n\) is greater than the
probability of \(c\) conditional on \(p\_1\) ... \(p\_n\).
Roxanne's case can be understood in these terms. She first
believes various premises about the gas gauge readings (e.g., *The
gas gauge read full at time \(t\); the gauge reads half-empty at
\(t^\*\)*). She then infers various lemmas about the state of the
gas tank (e.g., *The tank was full at \(t\); the tank was
half-empty at \(t^\*\)*). Finally, by conjoining these premises with
these lemmas, she comes to believe the conclusion: *The gas tank is
reliable*. The probability of this conclusion conditional on just
the lemmas (that is, the beliefs about the state of the gas tank) is
higher than the probability of the conclusion conditional on the
premises (that is, the gas gauge readings). Perhaps by imposing a ban
on either No Lose Investigations or epistemic feedback (or both), we
can account for the intuition about Roxanne, while still allowing for
basic justification. (For an overview of various responses to the
bootstrapping problem, see Weisberg 2012.)


#### The Problem of Defeat



Another challenge for reliabilism comes from the phenomenon of
epistemic defeat. Consider a case where an agent reliably forms a
belief that \(p\) at some initial time, and later receives some
evidence (perhaps misleading evidence) indicating that \(p\) is false.
For example, suppose Alice looks at a red vase in good lighting
conditions, and forms the belief that the vase is red. A friend comes
along and tells her that she is actually looking at a white vase
illuminated by red lights. It seems that the receipt of this testimony
renders her belief unjustified, even though it was originally formed
via a reliable process. Can reliabilists accommodate this verdict?



In "What is Justified Belief?", Goldman acknowledged this
sort of problem, and suggested adding a "No Defeaters"
condition to the theory of epistemic justification. There, he
elucidated an account of defeat in counterfactual terms. Roughly, your
belief *B* is defeated provided there is some reliable (or
conditionally reliable) process *X* available to you such that,
if you were you use *X*, you would no longer hold *B*. On
this view, Alice's belief is defeated because if she were to use
the process *believing her friend's testimony,* she would
not have believed *B*. However, this account of defeat has been
subject to various challenges. For example, Beddor (2015) argues that
it commits a version of the "counterfactual fallacy",
rendering it susceptible to counterexamples. And both Lyons (2009:
124) and Beddor (2021) point out that it has trouble accommodating
cases where one defeater is defeated by another.



But even if we reject an account of defeat along these lines, the
reliabilist may have other options for dealing with the problem. For
example, some might suggest that we can handle this problem by
appropriately typing the agent's belief. Perhaps after Alice
receives her friend's testimony, her belief is no longer the
result of *vision* alone, but rather of *vision while
disregarding testimony that vision is unreliable*. (See Constantin
2020; Nagel 2021 for versions of this response.) An important question
for this response is whether it is consistent with our most promising
theories of process-typing; in this regard, the problem of defeat is
connected to the generality problem. Another strategy for handling
defeat is to modify reliabilism by incorporating some evidentialist
elements into the theory. For now, we will defer a more detailed
discussion of this maneuver to
 SS4.2
 below.



It is also worth noting that the reliabilist's treatment of
defeat may bear on other problems facing reliabilism. Consider again
the clairvoyance objection. Yet another response to this objection,
suggested briefly by Goldman (1986: 112) is that Norman's belief
is *prima facie* justified, but it is defeated. Whether this
response is viable will depend on the details of the
reliabilist's theory of defeat.


#### The Temporality Problem



A more recent challenge to reliabilism, due to Frise (2018), is the
"temporality problem". Reliabilists maintain that the
justificatory status of a belief depends on the reliability of the
process responsible for that belief. But, Frise points out, a process
can be more reliable at one time than at another. To give one of
Frise's examples, weather forecasting has improved over time. So
the process type, *forming a belief based on the forecast* is
more reliable now than it was twenty years ago. This raises a question
about the temporal parameters that we should use when evaluating
reliability. Suppose we are evaluating whether a belief *B* is
justified at a time *t*. Do we restrict our attention to whether
the belief-forming process responsible for *B* is reliable at
*t*? Or do we look at whether it has been reliable at all times
up until *t*? Or all times that are temporally close to *t*?
Or something else?



This issue has not received much attention from reliabilists, though
see Tolly (2019) for an exception. One question that merits further
investigation is whether the reliabilist's preferred solution to
the generality problem will generalize to help with the temporality
problem. For example, according to the "common sense"
approach described above, there is considerable convergence in
ordinary people's judgments about how to type belief-forming
processes. If this is right, is there also convergence in ordinary
people's judgments about which times are relevant to assessing
the reliability of a given process? If so, could we use this common
sense consensus to make progress on the temporality problem?


## 3. New Developments for Reliabilism



We now turn to consider some relatively recent developments in
reliabilist epistemology. In the next section, we turn to consider
various cousins and spin-offs of reliabilism.


### 3.1 Normality Reliabilism



As we saw in
 SS2.2,
 a crucial question facing reliability theories concerns the domain in
which a process is assessed for reliability. Recently, some writers
have explored the idea that we should take this domain to be the
*normal conditions* for the use of a given process.



For example, Jarrett Leplin (2007, 2009) rejects the common view of
reliable processes as those that produce a high ration of truths to
falsehoods. In its place, Leplin advances a conception of reliability
according to which a process/method is reliable if it would never
produce or sustain false beliefs under *normal* conditions (see
Leplin 2007: 33: 2009: 34-35). A similar proposal has been
developed by Peter Graham (e.g., Graham, 2012, 2020). Graham draws on
an etiological account of function due to Larry Wright (1973) and Ruth
Millikan (1984), among others, to advance a theory of epistemic
entitlement in terms of proper functioning. Then, like Leplin, Graham
tries to use a normality approach to address some familiar
counterexamples to process reliabilism.



Why favor a normality-based version of reliabilism? One motivation
comes from the new evil demon problem. The victim of the evil demon
forms beliefs using perception--a process that is unreliable at
their world. But, the response runs, the normal conditions for
perception are free from evil demons and the like. At these worlds,
perception is indeed reliable.



There remains work to be done in developing a normality-based version
of reliability, particularly when it comes to elucidating the notion
of "normal conditions" here. But at the very least
normality-based approaches offer a welcome variant on more traditional
forms of reliabilism. Normality-based approaches also parallel recent
developments in the analysis of knowledge. For example, D. Greco
(2014), taking inspiration from an idea in Dretske (1981), develops an
information-theoretic analysis of knowledge, which he cashed out in
terms of normal conditions. In a similar vein, both Goodman and Salow
(2018) and Beddor and Pavese (2020) have proposed "normal
conditions" variants of a safety condition on knowledge (of the
sort discussed in
 SS1).


### 3.2 Beyond Individualistic Reliabilism



Most versions of reliabilism are "individualistic" in at
least two senses. First, they assume that the justificatory status of
an agent's belief depends entirely on the reliability of
processes that take place within that agent's head. Second, they
assume that the bearers of justificatory status are the beliefs of
individual agents, rather than groups. Recently, several philosophers
have developed versions of reliabilism that revise or abandon these
individualistic assumptions.



Sanford Goldberg (2010) advances a distinctive view of testimonial
belief that abandons the first individualistic assumption. Goldberg
invites us to imagine that an informant (*A*) forms a perceptual
belief that *p*, which they convey via testimony to an audience
(*B*), who then comes to believe *p*. However,
*A*'s perceptual belief that *p* was formed in a way
that falls just shy of the threshold for justification. Goldberg
contends that *B*'s testimony-based belief that *p*
does not amount to knowledge. What's more, the reason why it
does not amount to knowledge is that it is not justified. After all,
the belief could well be true, and free from Gettierization. But if
*B*'s belief that *p* is not justified, this
justificatory failing is not due to any unreliability in
*B*'s mental processing of *A*'s testimony.
Rather, it's due to the fact that *A*'s original
belief that *p* was insufficiently justified. Goldberg concludes
that the justificatory status of testimonial beliefs depends--in
part--on the reliability of the testifier's cognitive
processes.



Turn next to the second individualistic assumption: the bearers of
justificatory status are always the beliefs of individual agents. A
new movement in social epistemology has called this assumption into
question. This movement starts with the observation that we routinely
ascribe beliefs to groups. For example, we talk about whether the jury
believes the defendant is guilty, or what the Committee on Climate
Change believes to be the causes of global warming. A burgeoning body
of literature investigates the nature of group belief, and the ways in
which group belief depends on the beliefs of the group's
members. For important work on this topic, see Gilbert (1989); List
and Pettit (2011); for an overview, see the entry on
 belief merging and judgment aggregation.



In addition to inquiring into the conditions under which a group holds
a particular belief, we can also inquire into the conditions under
which group beliefs are *justified*. Some social
epistemologists have sought to answer this question in reliabilist
terms. For example, Goldman (2014) develops a view of group
justification that is modelled on the way inference transmits
justification within an individual agent. According to process
reliabilism for individuals, inferential justification depends on two
factors: (a) the justifiedness of the premise beliefs and (b) the
*conditional reliability* of the inferential process used.
Similarly, Goldman suggests, group justification depends on two
analogous factors: (a) the justifiedness of the members' beliefs
and (b) the conditional reliability of the belief aggregation function
(a function that specifies the way in which the group's beliefs
depend on the members' beliefs). The details of Goldman's
proposal have been critically discussed by both Lackey (2016) and Dunn
(forthcoming), both of whom propose alternative accounts of the
conditions under which group beliefs are justified.


### 3.3 Reliabilism and Degrees of Belief



Historically, reliabilism has been offered as an account of the
justificatory status of full or outright belief. However, it's
widely thought that beliefs come in degrees: a person might believe
that it's sunny and also believe that it's Monday, but
have a higher degree of belief in the former than the latter. This
raises the question: can reliabilism be extended to provide an account
of the justificatory status of degrees of belief?



Formal epistemologists have long been interested in different
"scoring rules"--functions that measure the accuracy
or inaccuracy of degrees of belief (hereafter, credences). For
example, one widely discussed scoring rule is the *Brier score*
(Brier 1950). Let \(C(p)\) be an agent's credence in \(p\); let
\(T(p)\) be \(p\)'s indicator function, which equals 1 if \(p\)
is true, and 0 if \(p\) is false. \(C(p)\)'s Brier score is
calculated by the formula:

 

\[(C(p)-T(p))^2\]


Thus, a credence of 1 in a true proposition will get a Brier score of
0--the best score possible. A credence of 1 in a false
proposition will get a Brier score of 1--the worst score
possible. An intermediate credence of .6 will get a Brier score of .16
if the proposition is true, and .36 if it is false.



Given a particular scoring rule *R*, we can develop a measure of
process reliability (Dunn 2015; Tang 2016; Pettigrew 2021). Let
*X* be some credence-forming process: that is, a process that
outputs credences in a range of propositions. We can use *R* to
score all of the credences that *X* produces. Average all of
these scores, and we have a measure of *X*'s degree of
reliability. Process reliabilists can then use this measure of
reliability to give an account of justification for credences: a
credence is (*prima facie*) justified iff it is produced by a
reliable credence-forming process.



What is the most suitable scoring rule for process reliabilism to use?
Recent work has begun to tackle this question. In what follows, we
confine ourselves to discussing two particularly prominent scoring
rules--the Brier score and a calibration score.



Given its prominence in the literature, the Brier score is a natural
option. But using the Brier score to measure the reliability of
credence-forming processes faces challenges. For example, Dunn (2015)
and Tang (2016) object that if the Brier score is used, a
credence-forming process that only outputs mid-level credences (say, a
credence of .6) will never qualify as highly reliable; hence the
credences it produces will never count as highly justified. Both Dunn
and Tang object to this consequence. For instance, Tang argues that
sometimes a particular input requires having a mid-level credence. If
I have a vague visual experience of the silhouette of a horse, then it
seems I should only have a mid-level credence that there is a horse in
front of me: a credence of .6 in this proposition might well be
justified, whereas a credence of 1 or 0 would not.



Another option is to measure the reliability of credence-forming
processes using a *calibration score*. To see what it means for
a credal state to be well-calibrated, consider the following example
from van Fraassen:



> 
> 
> Consider a weather forecaster who says in the morning that the
> probability of rain equals .8. That day it either rains or does not.
> How good a forecaster is he? Clearly, to evaluate him we must look at
> his performance over a longer period of time. Calibration is a measure
> of agreement between judgments and actual frequencies... This
> forecaster was perfectly calibrated over the past year, for example,
> if, for every number *r*, the proportion of rainy days among
> those days on which he announced probability *r* for rain,
> equaled *r*. (van Fraassen 1984: 245)
> 
> 
> 



According to the calibration approach, a credence is justified iff it
is produced by a well-calibrated process. This avoids the objection to
using the Brier score: after all, a credence-forming process that
produces mid-level credences can still be well-calibrated.



However, the calibration approach has also elicited criticism. Goldman
(1986) asks us to imagine an agent *A*, 70% of whose opinions
turn out to be true. *A* can achieve a perfectly calibrated
credence function by adopting a .7 credence in every proposition about
which she has an opinion. However, Goldman argues that it's
wrong to automatically conclude that *A*'s credal state is
perfectly reliable. If *A* has no good reason for adopting a .7
credence in many of the propositions in question, then her credal
state shouldn't count as justified. Dunn (2015) defends the
calibration approach, arguing that the relevant question is whether
the *process* that produced *A*'s credal state is
reliable. In order to answer this question, it's not enough to
look at the truth-ratio of *A*'s opinions at the actual
world; rather, we should look across a range of nearby worlds. If
it's just a matter of chance that 70% of the propositions
*A* has an opinion about are true, then by looking at the
truth-values of *A*'s opinions at nearby worlds the
calibration approach will be able to avoid the counterintuitive
consequence that *A*'s credal state is perfectly
reliable.



Tang (2016) objects to the calibration approach on the grounds that a
credence-forming process can be well-calibrated even though that
process is insensitive to relevant evidence. In light of the perceived
shortcomings of the calibration approach (and those of alternative
scoring rules), Tang proposes a synthesis of reliabilism and
evidentialism, where evidentialism can roughly be understood as the
view that a belief's justification is determined by how well it
is supported by the believer's evidence. According to
Tang's proposal, a credence of \(C(p)\) is only justified if it
is based on some ground \(g\), such that the objective probability of
the credence having a true content given \(g\) approximates \(C(p).\)
More recently, Pettigrew (2021) has argued that these two approaches
should not be viewed as competitors at all. Pettigrew suggests that we
can develop a version of the calibration approach that makes reference
to the agent's evidence. Once we do, this version turns out to
be extensionally equivalent to a version of Tang's approach.
Both Tang and Pettigrew's approaches to this issue can thus be
viewed as syntheses of reliabilism and evidentialism, to be discussed
in more detail in
 SS4.2
 below.



Only recently have philosophers started to systematically explore the
possibility of using scoring rules to provide a reliabilist theory of
credal justification. Given its position at the intersection of
traditional and formal epistemology, this will likely prove to be a
rich and important area of ongoing research.


## 4. Cousins and Spin-offs of Reliabilism



A number of theories have "branched off" from process
reliabilism, borrowing some key ideas but parting company with respect
to others. This section discusses two such cousins of process
reliabilism: virtue reliabilism and syntheses of reliabilism and
evidentialism.


### 4.1 Virtue Reliabilism



As its label suggests, virtue reliabilism is a branch of virtue
epistemology that emerged in the mid-1980s in the wake of process
reliabilism and shares some significant features with it. In
particular, one of its central theoretical notions, that of an
epistemic competence, resembles that of a reliable belief-forming
process type. And its notion of the exercise of an epistemic
competence resembles that of a token of a reliable process. Leading
proponents of virtue reliabilism include Ernest Sosa (1991, 2007,
2010, 2015), John Greco (1999, 2010) and Duncan Pritchard (2012b).
Here we will focus primarily on Sosa's version.



Most virtue reliabilists do not explicitly use the notion of a
"reliable process", preferring instead the notions of
"competence", "virtue", "skill" or
"ability". How should we understand these notions? Sosa
often characterizes competences in terms of dispositions, for
instance:



> 
> 
> A competence is a certain sort of disposition to succeed when you try.
> So, exercise of a competence involves aiming at a certain outcome. It
> is a competence in part because it is a disposition to succeed
> reliably enough when one makes such attempts... It is thus tied
> to a conditional of the form: if one tried to \(\varphi\), one would
> (likely enough) succeed. (2015: 96)
> 
> 
> 



*Epistemic competences*--the sort of competence that is
relevant to epistemology--are dispositions of a specific variety:
dispositions to arrive at the truth.



One question that arises for such accounts of competence is how we are
to understand the dispositions in question. Are they general
dispositions of an agent to arrive at the truth about some matter? Or
are they to be understood as implicitly relativized to belief-forming
processes or methods, in which case an epistemic competence is really
of the form: *a disposition to arrive at the truth when employing
process *X**?



From a process reliabilist perspective, it's necessary to
relativize the dispositions to belief-forming processes or methods.
After all, process reliabilists will insist that in order to know
whether an agent's belief that *p* is justified or counts
as knowledge, it's not enough to know whether the agent is
generally disposed to arrive at truths about *p*-related matters.
Instead, we'll need to know whether the agent's particular
belief that *p* was the result of a reliable process. (After all,
an agent could form the belief that *p* via an ultra-reliable
process, even if she's generally disposed to form beliefs about
*p*-related matters in highly unreliable ways.) In effect,
committed process reliabilists will suggest that virtue reliabilists
face a dilemma: either epistemic competences are general dispositions
of the agent, in which case they won't be able to perform the
various jobs required of them (specifically, explaining whether a
belief is justified, or amounts to knowledge), or they are implicitly
relativized to processes, in which case epistemic competences are not
significantly different from reliable belief-forming processes. In the
latter case, epistemic competences "collapse" into
reliable processes.



In at least some discussions of epistemic competences, virtue
reliabilists indicate a willingness to relativize epistemic
competences to processes. For example, Sosa describes good eyesight
and color vision as paradigmatic epistemic competences (Sosa 1991:
271; 2010: 467)--both of which are also standard examples of
reliable processes. If epistemic competences are understood as
involving reliable processes, then virtue reliabilism inherits many of
the challenges facing process reliabilism--in particular, the
generality problem. (In virtue reliabilist terms, this will amount to
the question: "How exactly should we type epistemic
competences?") Of course, this result is unsurprising if the
generality problem is a problem for everyone who tries to give an
adequate theory of justified belief, as proponents of the
"parrying response" suggest
 (SS2.3).



Virtue reliabilism differs from traditional process reliabilism in its
choice of analysandum. Historically process reliabilists have focused
on giving an account of *justification*; by contrast, virtue
reliabilists have focused on giving an account of *knowledge*.
However, one certainly could try to extend one's virtue
reliabilism to justification. Indeed, if one assumes that knowledge
entails justification, being a virtue reliabilist about the former
seems to lead naturally to virtue reliabilism about the latter. And if
epistemic competences are understood as reliable processes, the
resulting virtue reliabilist account of justification would presumably
amount to a version of process reliabilism.



Let us turn now to virtue reliabilist accounts of knowledge. How do
virtue reliabilists propose to understand knowledge in terms of
epistemic competences? There are a variety of slightly different
proposals in the literature (J. Greco 2009, 2010; Sosa 2007, 2015;
Turri 2011). However, virtue reliabilists typically understand
knowledge as involving some sort of explanatory relation between
having a true belief and the exercise of an epistemic competence. For
instance, Sosa (2007) holds that *S* knows *p* if and only
if *S* aptly believes *p*, where *S*'s belief is
apt if and only if it is correct *because* of the exercise of
an epistemic competence (see also J. Greco 2009, 2010 for a closely
related account). More recently, Sosa (2010, 2015) defends a similar
account couched in terms of "manifestation": knowledge is
belief whose correctness manifests the agent's epistemic
competence (see Turri 2011 for a similar account).



How do such accounts handle Gettier cases? Sosa 2007: 94-97
discusses Lehrer's (1965) Nogot/Havit case, in which a subject
*S* truly believes that someone here owns a Ford, but he only
does so on the basis of Nogot's misleading testimony. Sosa
claims that while *S* holds this belief because of the exercise
of an epistemic competence, *S*'s belief isn't
correct *because* of the exercise of an epistemic competence.
This explanation raises important questions about how to understand
the relevant "because of" relation here: what exactly is
the difference between a true belief being held because of an
epistemic competence, and a belief being correct because of an
epistemic competence? Other ways of fleshing out the details of a
virtue reliabilist analysis raise similar questions.



Even if a virtue reliabilist account of knowledge can handle some
Gettier cases, there remains a question of whether it will be able to
handle the full spectrum of Gettier cases. One case that has been
thought to cause particular trouble for virtue reliabilists is the
fake barn scenario (introduced by Goldman 1976, who credits the
example to Carl Ginet). In the fake barn scenario, Henry sees from the
road the one genuine barn in an area filled with many convincing barn
facades. Henry forms a true belief that there's a barn in
front of him; what's more, the fact that he correctly believes
there's a barn in front of him seems to be causally explained by
an exercise of his visual competence. (See Lackey 2007 for a forceful
statement of this point.)



One response to this challenge is to abandon the hope that virtue
reliabilism on its own will solve every Gettier case. Pritchard
(2012b) takes this line, opting for a view that combines elements of
virtue epistemology with a safety requirement on knowledge (where,
again, safety is roughly the requirement that the belief in question
couldn't easily have been held falsely). On Pritchard's
view, Henry's belief that he sees a barn is unsafe, hence fails
to count as knowledge. Whether this reply is adequate is a matter of
debate; for relevant discussion, see Lackey (2006); Beddor and Pavese
(2020).



A full assessment of these issues is beyond the scope of the current
article. This much is clear: one feature that distinguishes virtue
reliabilism from classical process reliabilism is its distinctive
treatment of knowledge. However, this treatment gives rise to
important questions--questions that remain very much an area of
active research.


### 4.2 Syntheses of Reliabilism and Evidentialism



Process reliabilism and evidentialism have long been viewed as
competitors, even antitheses of one another, with one of them
(reliabilism) being a paradigm of externalism and the other
(evidentialism) a paradigm of internalism. However, a number of
epistemologists have recently questioned whether these views are
necessarily opposed. For example, Comesana (2010), Goldman
(2011), Tang (2016), Goldberg (2018), Pettigrew (2021), Miller (2019)
and Beddor (2021) have all developed reliabilist views that
incorporate certain elements traditionally associated with
evidentialism.



Let us start with Comesana's version of a hybrid view.
Comesana defends:




**Evidentialist Reliabilism:** *S*'s belief
that *p* is justified if and only if:


1. *S* has some evidence *e*,
2. The belief that *p* is based on *e*, and either:
	1. *e* doesn't include any beliefs and the type,
	*producing a belief that p based on e* is actually reliable,
	or
	2. *e* includes beliefs of *S*, all of these beliefs are
	justified, and the type *producing a belief that *p* based on
	*e** is conditionally actually reliable.




There are a few respects in which this departs from standard versions
of reliabilism. The most obvious is that it involves an *evidential
requirement*. This is intended to serve two functions. First, it
is designed to help with the clairvoyance problem. One crucial feature
of Norman's situation is that he has no evidence regarding his
clairvoyance, or regarding the whereabouts of the President. This is
at least one of the reasons (says Comesana) why we have the
intuition that Norman is not justified. Second, Comesana
suggests that by incorporating bodies of evidence into the
belief-forming process, we can make headway on the generality problem.
On this view, the relevant type for a given belief-forming process is
always: *producing a belief that such-and-such on the basis of body
of evidence e*.



While incorporating the notion of evidence into a reliablist theory
carries potential advantages, it also raises issues of its own. As
we've seen, traditional process reliabilists resisted defining
"justification" in terms of evidence because they
didn't want an analysis that relied on any unreduced epistemic
notions (Goldman 1979). Moreover, even those who do not share these
reductive ambitions may well want some account of the notion of
evidence possession that appears in clause 1) of Evidentialist
Reliabilism. Comesana suggests following Conee and Feldman
(2004) in opting for a "mentalist" construal of our
evidence, according to which our evidence ultimately consists in
various mental states. While this is a start, there remains the
question of *which* mental states constitute a subject's
evidence. Are they conscious experiences? States that are accessible
to consciousness? Beliefs?



One possibility--not pursued directly by
Comesana--would be to appeal to reliabilist resources to
provide an answer. Goldman (2011) makes a suggestion along these lines
in developing his preferred synthesis of reliabilism and
evidentialism. Goldman points out that while reliabilists have not
traditionally appealed to the notion of evidence, the notions of
mental or psychological *states* play an important role in
reliabilist theories. After all, in addition to belief-forming
*processes*, there are also *states* that serve as
*inputs* to those processes. These include both doxastic states
(beliefs, primarily) and various experiences (perceptual, memorial,
etc.). Although reliabilists typically do not call these states
"evidence", there is no principled reason why they could
not do so. A similar suggestion is made by Beddor (2021), framed in
terms of *reasons* rather than *evidence*. On
Beddor's proposal, a given psychological state *s*
constitutes a *prima facie* reason for an agent to hold a
belief *B* just in case there is some reliable (or, in the case
of inferential beliefs, conditionally reliable) process available to
the agent that is disposed to produce *B* when fed *s* as
input. (More on the applications of this sort of view below.) Perhaps,
then, not only does a reliabilist-evidentialist hybrid help address
problems for reliabilism, it also helps answer some pressing questions
that have historically faced evidentialists.



A further question that arises for reliabilist-evidentialist hybrids
concerns the role of historical features (or the lack thereof) in the
theory of justifiedness. As noted in
 SS1
 above, traditional forms of reliabilism make the epistemic status of
a belief at a time *t* depend not only on features of the agent
at *t*, but also on facts about how the believer acquired the
belief in question. Here's an example that motivates this
"historicist" dimension to traditional reliabilism
(Goldman 1999). Last year Sally read about the health benefits of
broccoli in a New York Times science section story. She then forms a
justified belief in broccoli's beneficial effects. She still
retains that belief today but no longer recalls the evidence she had
upon first reading the story. And she hasn't encountered any
further evidence in the interim, from any kind of source. Isn't
her belief in broccoli's beneficial effects still justified?
Presumably this is because of her past acquisition. True, she also has
a different kind of evidence, namely, her (justified) belief that
whenever she seems to remember a (putative) fact it is usually true.
But this is not her entire evidence. It is an important determinant of
her belief's justificatory status at *t* that she was
justified in forming it originally on the basis of good evidence (of
another kind). Had her original belief been based on very poor
evidence, e.g., reading a similar story in an untrustworthy news
source, so that the belief wasn't justified from the start, her
belief at time *t* would be unjustified--or at least much
*less justified*. This indicates that the evidence she acquired
originally still has *some impact* on the justificatory status
of her belief at *t*.



Notably, Comesana's Evidentalist Reliabilism lacks any
such historical condition on justifiedness. However, other versions of
a hybrid theory do incorporate a historical condition, and emphasize
it as a selling point of the view (Goldman 2011; Goldberg 2018; Beddor
2021). For example, Goldman (2011) advocates a
"two-component" approach to justification, which makes
room for a "degree of support" dimension of justification
as well as a "proper causal generation" dimension. Here is
one simple way of developing such a theory:




**Two-Component Hybrid View:** *S*'s belief
that *p* is justified at *t* iff both:


1. *S*'s total evidence at *t* supports
believing *p*,
2. *S*'s belief that *p* is the result of
a reliable belief-forming process.




Condition 1
 incorporates the traditional evidentialist take on justification.
(Though, as noted above, this condition could itself be given a
reliabilist spin, if we characterize evidence as the inputs to
reliable processes). By contrast,
 condition 2
 captures the causal generation dimension of justification. Goldman
suggests that a two-component view is nicely positioned to preserve
the best of both approaches.



A final motivation for hybrid views is also worth noting. We saw
earlier
 (SS2.4)
 that some authors have argued that reliabilists have trouble
accounting cases of defeat -- cases where an agent reliably forms
a belief that *p* at some initial time, and later receives
evidence indicating that *p* is false. Intuitively, this further
evidence defeats *S*'s justification for believing
*p*, rendering their belief unjustified (even if it was
previously justified). Recently, some authors have suggested that the
best way of accommodating defeat in a reliabilist framework is to draw
on evidentialist elements (broadly construed). For example, Miller
(2019) defends a version of a Two-Component Hybrid View. On her view,
cases of defeat are cases where
 condition 1
 (the evidential support condition) is not satisfied.



Another approach to this issue is developed in Beddor (2021), who
offers a synthesis of a reliabilist view with a "reasons
first" account of justification of the sort developed by John
Pollock (see, e.g., Pollock 1987, 1995). On Pollock's view, a
belief is justified as long as it is based on a chain of undefeated
reasons that support it. One distinctive feature of Pollock's
framework is that he goes on to define defeaters in terms of reasons:
a defeater for a belief *B* is a *prima facie* reason to
believe that *B* is false (rebutting defeater) or a *prima
facie* reason to believe that the agent's beliefs do not
support *B* (undercutting defeater). Beddor suggests that by
supplementing this account with a reliabilist analysis of *prima
facie* reasons (of the sort sketched above), we get a view that is
faithful to the main motivations for reliabilism, while also providing
a more satisfactory treatment of defeat.



Thus there are a number of different ways of developing a hybrid of
reliabilism and evidentialism. Such hybrids hold considerable promise
for overcoming some of the problems facing both reliabilism and
evidentialism. In view of this promise, such hybrids are a potentially
fruitful area for further research.