chapter on perception and bias including implicit bias.

The rationality of future bias figures crucially in various metaphysical and ethical arguments (Prior 1959; Parfit 1984; Fischer 2019). Recently, however, philosophers have raised several arguments to the effect that future bias is irrational (Dougherty 2011; Suhler and Callender 2012; Greene and Sullivan 2015). Particularly, Greene and Sullivan (2015) claim that future bias is irrational because future bias leads to two kinds of irrational planning behaviors in agents who also seek to avoid regret. In this paper, (...) I join others who have objected to Greene and Sullivan’s argument (Dorsey 2016; Tarsney 2017), but for significantly different reasons that put into question an unchallenged premise in the debate. These reasons are based on the relationship between the alleged irrational planning behaviors and certain features of regret that regret shares with future bias. First, regret is dynamic, involving preferences that change over time and in inconsistent ways. Second, regret comes in degrees, meaning that we can rank our potential regrets. Because regret has these features, I show that the future-biased agents in Greene and Sullivan’s cases do not need to act in irrational ways to rationally avoid regret. (shrink)

It has been argued that implicit biases are operative in philosophy and lead to significant epistemic costs in the field. Philosophers working on this issue have focussed mainly on implicit gender and race biases. They have overlooked ideological bias, which targets political orientations. Psychologists have found ideological bias in their field and have argued that it has negative epistemic effects on scientific research. I relate this debate to the field of philosophy and argue that if, as some studies (...) suggest, the same bias also exists in philosophy then it will lead to hitherto unrecognised epistemic hazards in the field. Furthermore, the bias is epistemically different from the more familiar biases in respects that are important for epistemology, ethics, and metaphilosophy. (shrink)

B a c k g r o u n d. The article is devoted to the study of confirmatory distortion as a cognitive bias within the framework of the modern theory of argumentation. In the context of this study, the effectiveness of the critical questioning technique as an argumentation strategy aimed at reducing the negative impact of confirmatory bias is considered. M e t h o d s. To achieve the goals of the research, the method of critical (...) questions is used, which is based on the traditional principles of logic, dialectics and rhetoric. Specific lists of critical questions are developed for each argumentative scheme. R e s u l t s. The article demonstrates that standard critical questions for schemes of practical reasoning, developed by eminent specialists, are able to minimize the negative impact of confirmation bias. This is achieved by taking into account information that may conflict with the agent's action plan. C o n c l u s i o n s. The study highlights the importance of using critical questions as a tool to minimize confirmation bias. Such an approach not only contributes to the substantiation of arguments, but also stimulates self-control and the search for information that may cause doubts about one's own views. The final part of the article examines propaganda as the deliberate use of confirmatory distortion and points to the need for attention to language patterns where it occurs rather unintentionally. In connection with the specificity of the studied phenomenon, the term "confirmation bias" is proposed as a translation of the English "confirmation bias". (shrink)

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group level even when (...) they negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

To what extent should we focus on implicit bias in order to eradicate persistent social injustice? Structural prioritizers argue that we should focus less on individual minds than on unjust social structures, while equal prioritizers think that both are equally important. This article introduces the framework of transactive memory into the debate to defend the equal priority view. The transactive memory framework helps us see how structure can emerge from individual interactions as an irreducibly social product. If this is (...) right, then debiasing interventions are structural interventions. One upshot is that the utility of the individual versus structural distinction is not apparent for the purposes of intervention. (shrink)

What is the mental representation that is responsible for implicit bias? What is this representation that mediates between the trigger and the biased behavior? My claim is that this representation is neither a propositional attitude nor a mere association. Rather, it is mental imagery: perceptual processing that is not directly triggered by sensory input. I argue that this view captures the advantages of the two standard accounts without inheriting their disadvantages. Further, this view also explains why manipulating mental imagery (...) is among the most efficient ways of counteracting implicit bias. (shrink)

This paper examines the role of prestige bias in shaping academic philosophy, with a focus on its demographics. I argue that prestige bias exacerbates the structural underrepresentation of minorities in philosophy. It works as a filter against (among others) philosophers of color, women philosophers, and philosophers of low socio-economic status. As a consequence of prestige bias our judgments of philosophical quality become distorted. I outline ways in which prestige bias in philosophy can be mitigated.

In this paper, I argue against the view that the representational structure of the implicit attitudes responsible for implicitly biased behaviour is propositional—as opposed to associationist. The proposal under criticism moves from the claim that implicit biased behaviour can occasionally be modulated by logical and evidential considerations to the view that the structure of the implicit attitudes responsible for such biased behaviour is propositional. I argue, in particular, against the truth of this conditional. Sensitivity to logical and evidential considerations, I (...) contend, proves to be an inadequate criterion for establishing the true representational structure of implicit attitudes. Considerations of a different kind, which emphasize the challenges posed by the structural social injustice that implicit attitudes reflect, offer, I conclude, better support for deciding this issue in favour of an associationist view. (shrink)

Philosophers have long noted, and empirical psychology has lately confirmed, that most people are “biased toward the future”: we prefer to have positive experiences in the future, and negative experiences in the past. At least two explanations have been offered for this bias: belief in temporal passage and the practical irrelevance of the past resulting from our inability to influence past events. We set out to test the latter explanation. In a large survey, we find that participants exhibit significantly (...) less future bias when asked to consider scenarios where they can affect their own past experiences. This supports the “practical irrelevance” explanation of future bias. It also suggests that future bias is not an inflexible preference hardwired by evolution, but results from a more general disposition to “accept the things we cannot change”. However, participants still exhibited substantial future bias in scenarios in which they could affect the past, leaving room for complementary explanations. Beyond the main finding, our results also indicate that future bias is stake-sensitive and that participants endorse the normative correctness of their future-biased preferences and choices. In combination, these results shed light on philosophical debates over the rationality of future bias, suggesting that it may be a rational response to empirical realities rather than a brute, arational disposition. (shrink)

Many philosophers appeal to intuitions to support some philosophical views. However, there is reason to be concerned about this practice as scientific evidence has documented systematic bias in philosophically relevant intuitions as a function of seemingly irrelevant features (e.g., personality). One popular defense used to insulate philosophers from these concerns holds that philosophical expertise eliminates the influence of these extraneous factors. Here, we test this assumption. We present data suggesting that verifiable philosophical expertise in the free will debate-as measured (...) by a reliable and validated test of expert knowledge-does not eliminate the influence of one important extraneous feature (i.e., the heritable personality trait extraversion) on judgments concerning freedom and moral responsibility. These results suggest that, in at least some important cases, the expertise defense fails. Implications for the practice of philosophy, experimental philosophy, and applied ethics are discussed. (shrink)

Are individuals morally responsible for their implicit biases? One reason to think not is that implicit biases are often advertised as unconscious, ‘introspectively inaccessible’ attitudes. However, recent empirical evidence consistently suggests that individuals are aware of their implicit biases, although often in partial and inarticulate ways. Here I explore the implications of this evidence of partial awareness for individuals’ moral responsibility. First, I argue that responsibility comes in degrees. Second, I argue that individuals’ partial awareness of their implicit biases makes (...) them (partially) morally responsible for them. I argue by analogy to a close relative of implicit bias: moods. (shrink)

In this chapter, we explore whether agents have an epistemic duty to eradicate implicit bias. Recent research shows that implicit biases are widespread and they have a wide variety of epistemic effects on our doxastic attitudes. First, we offer some examples and features of implicit biases. Second, we clarify what it means to have an epistemic duty, and discuss the kind of epistemic duties we might have regarding implicit bias. Third, we argue that we have an epistemic duty (...) to eradicate implicit biases that have negative epistemic impact. Finally, we defend this view against the objection that we lack the relevant control over implicit bias that’s required for such a duty. We argue that we have a kind of reflective control over the implicit biases that we are duty-bound to eradicate. And since, as we show, we have this control over a wide variety of implicit biases, there are a lot of implicit biases that we have epistemic duties to eradicate. (shrink)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, (...) overgeneralized conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science. (shrink)

When interests and preferences of researchers or their sponsors cause bias in experimental design, data interpretation or dissemination of research results, we normally think of it as an epistemic shortcoming. But as a result of the debate on science and values, the idea that all extra-scientific influences on research could be singled out and separated from pure science is now widely believed to be an illusion. I argue that nonetheless, there are cases in which research is rightfully regarded as (...) epistemologically deficient due to the influence of preferences on its outcomes. I present examples from biomedical research and offer an analysis in terms of social epistemology. (shrink)

All else being equal, most of us typically prefer to have positive experiences in the future rather than the past and negative experiences in the past rather than the future. Recent empirical evidence tends not only to support the idea that people have these preferences, but further, that people tend to prefer more painful experiences in their past rather than fewer in their future (and mutatis mutandis for pleasant experiences). Are such preferences rationally permissible, or are they, as time-neutralists contend, (...) rationally impermissible? And what is it that grounds their having the normative status that they do have? We consider two sorts of arguments regarding the normative status of future-biased preferences. The first appeals to the supposed arbitrariness of these preferences, and the second appeals to their upshot. We evaluate these arguments in light of the recent empirical research on future-bias. (shrink)

Recent social‐psychological research suggests that a considerable amount of, for example, racial and gendered discrimination may be connected to implicit biases: mental processes beyond our direct control or endorsement, that influence our behaviour toward members of socially salient groups. In this article I seek to improve our understanding of the phenomenon of implicit bias, including its moral status, by examining it through the lens of a theory of discrimination. In doing so, I also suggest ways to improve this theory (...) of discrimination, by creating conceptual space for implicit bias discrimination. I explore two ways of distinguishing direct and indirect discrimination and spell out the resulting four different forms of discrimination. The resulting taxonomy provides some room for implicit bias discrimination. I also deal with four challenges to my proposal for capturing implicit bias within discrimination theory: the metaphysical challenge, the moral insignificance challenge, the causal connection challenge, and the challenge from irreducibly collective bias. (shrink)

Sally Haslanger has recently argued that philosophical focus on implicit bias is overly individualist, since social inequalities are best explained in terms of social structures rather than the actions and attitudes of individuals. I argue that questions of individual responsibility and implicit bias, properly understood, do constitute an important part of addressing structural injustice, and I propose an alternative conception of social structure according to which implicit biases are themselves best understood as a special type of structure.

Our focus here is on whether, when influenced by implicit biases, those behavioural dispositions should be understood as being a part of that person’s character: whether they are part of the agent that can be morally evaluated.[4] We frame this issue in terms of control. If a state, process, or behaviour is not something that the agent can, in the relevant sense, control, then it is not something that counts as part of her character. A number of theorists have argued (...) that individuals do not have control, in the relevant sense, over the operation of implicit bias. We will argue that this claim is mistaken. We articulate and develop a notion of control that individuals have with respect to implicit bias, and argue that this kind of control can ground character-based evaluation of such behavioural dispositions. (shrink)

This book represents the first major attempt by any author to provide an integrated account of the evidence for bias in human reasoning across a wide range of disparate psychological literatures. The topics discussed involve both deductive and inductive reasoning as well as statistical judgement and inference. In addition, the author proposes a general theoretical approach to the explanations of bias and considers the practical implications for real world decision making. The theoretical stance of the book is based (...) on a distinction between preconscious heuristic processes which determine the mental representation of 'relevant' features of the problem content, and subsequent analytic reasoning processes which generate inferences and judgements. Phenomena discussed and interpreted within this framework include feature matching biases in propositional reasoning, confirmation bias, biasing and debiasing effects of knowledge on reasoning, and biases in statistical judgement normally attributed to 'availability' and 'representativeness' heuristics. In the final chapter, the practical consequences of bias for real life decision making are considered, together with various issues concerning the problem of 'debiasing'. The major approaches discussed are those involving education and training on the one hand, and the development of intelligent software and interactive decision aids on the other. (shrink)

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and paradoxes: (...) the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

To arrive at their final evaluation of a manuscript or grant proposal, reviewers must convert a submission’s strengths and weaknesses for heterogeneous peer review criteria into a single metric of quality or merit. I identify this process of commensuration as the locus for a new kind of peer review bias. Commensuration bias illuminates how the systematic prioritization of some peer review criteria over others permits and facilitates problematic patterns of publication and funding in science. Commensuration bias also (...) foregrounds a range of structural strategies for realigning peer review practices and institutions with the aims of science. (shrink)

In this paper I explore the nature of confabulatory explanations of action guided by implicit bias. I claim that such explanations can have significant epistemic benefits in spite of their obvious epistemic costs, and that such benefits are not otherwise obtainable by the subject at the time at which the explanation is offered. I start by outlining the kinds of cases I have in mind, before characterising the phenomenon of confabulation by focusing on a few common features. Then I (...) introduce the notion of epistemic innocence to capture the epistemic status of those cognitions which have both obvious epistemic faults and some significant epistemic benefit. A cognition is epistemically innocent if it delivers some epistemic benefit to the subject which would not be attainable otherwise because alternative (less epistemically faulty) cognitions that could deliver the same benefit are unavailable to the subject at that time. I ask whether confabulatory explanations of actions guided by implicit bias have epistemic benefits and whether there are genuine alternatives to forming a confabulatory explanation in the circumstances in which subjects confabulate. On the basis of my analysis of confabulatory explanations of actions guided by implicit bias, I argue that such explanations have the potential for epistemic innocence. I conclude that epistemic evaluation of confabulatory explanations of action guided by implicit bias ought to tell a richer story, one which takes into account the context in which the explanation occurs. (shrink)

_Anthropic Bias_ explores how to reason when you suspect that your evidence is biased by "observation selection effects"--that is, evidence that has been filtered by the precondition that there be some suitably positioned observer to "have" the evidence. This conundrum--sometimes alluded to as "the anthropic principle," "self-locating belief," or "indexical information"--turns out to be a surprisingly perplexing and intellectually stimulating challenge, one abounding with important implications for many areas in science and philosophy. There are the philosophical thought experiments and paradoxes: (...) the Doomsday Argument; Sleeping Beauty; the Presumptuous Philosopher; Adam & Eve; the Absent-Minded Driver; the Shooting Room. And there are the applications in contemporary science: cosmology ; evolutionary theory ; the problem of time's arrow ; quantum physics ; game-theory problems with imperfect recall ; even traffic analysis. _Anthropic Bias_ argues that the same principles are at work across all these domains. And it offers a synthesis: a mathematically explicit theory of observation selection effects that attempts to meet scientific needs while steering clear of philosophical paradox. (shrink)

Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the (...) existence of the bias itself, making it difficult to identify, mitigate, or evaluate using standard resources in epistemology and ethics. I demonstrate these points in the case of mitigation techniques by presenting what I call ‘the Proxy Problem’. One reason biases resist revision is that they rely on proxy attributes, seemingly innocuous attributes that correlate with socially-sensitive attributes, serving as proxies for the socially-sensitive attributes themselves. I argue that in both human and algorithmic domains, this problem presents a common dilemma for mitigation: attempts to discourage reliance on proxy attributes risk a tradeoff with judgement accuracy. This problem, I contend, admits of no purely algorithmic solution. (shrink)

If you care about securing knowledge, what is wrong with being biased? Often it is said that we are less accurate and reliable knowers due to implicit biases. Likewise, many people think that biases reflect inaccurate claims about groups, are based on limited experience, and are insensitive to evidence. Chapter 3 investigates objections such as these with the help of two popular metaphors: bias as fog and bias as shortcut. Guiding readers through these metaphors, I argue that they (...) clarify the range of knowledge-related objections to implicit bias. They also suggest that there will be no unifying problem with bias from the perspective of knowledge. That is, they tell us that implicit biases can be wrong in different ways for different reasons. Finally, and perhaps most importantly, the metaphors reveal a deep—though perhaps not intractable—disagreement among theorists about whether implicit biases can be good in some cases when it comes to knowledge. (shrink)

“Implicit bias” is a term of art referring to relatively unconscious and relatively automatic features of prejudiced judgment and social behavior. While psychologists in the field of “implicit social cognition” study “implicit attitudes” toward consumer products, self-esteem, food, alcohol, political values, and more, the most striking and well-known research has focused on implicit attitudes toward members of socially stigmatized groups, such as African-Americans, women, and the LGBTQ community.[1] For example, imagine Frank, who explicitly believes that women and men are (...) equally suited for careers outside the home. Despite his explicitly egalitarian belief, Frank might nevertheless implicitly associate women with the home, and this implicit association might lead him to behave in any number of biased ways, from trusting feedback from female co-workers less to hiring equally qualified men over women. Psychological research on implicit bias is relatively recent (§1), but a host of metaphysical (§2), epistemological (§3), and ethical questions (§4) about implicit bias are pressing.[2]. (shrink)

In this paper, I sketch a general framework for theorizing about bias and bias attributions. According to the account, paradigmatic cases of bias involve systematic departures from genuine norms. I attempt to show that the account illuminates a number of important psychological phenomena, including: the fact that accusations of bias frequently inspire not only denials but also countercharges of bias (“you only think that I'm biased because you're biased!”); the fact that we tend to see (...) ourselves as less biased than our peers (the so‐called ‘bias blind spot’); and the fact that we tend to see people who share our views as less biased than people who don't. I explore the circumstances in which we're committed to believing that those who disagree with us are not only mistaken but also biased simply because they disagree with us in the way that they do. In addition, the account also sheds light on another notorious and well‐documented psychological phenomenon: the fact that introspection is an unreliable way of detecting our biases. On the account that I offer, the unreliability of introspection for this purpose isn't a contingent fact that depends on the finer details of human psychology but rather holds of necessity: even God could not have made us creatures who reliably detect our own biases by way of introspection. (shrink)

Online information intermediaries such as Facebook and Google are slowly replacing traditional media channels thereby partly becoming the gatekeepers of our society. To deal with the growing amount of information on the social web and the burden it brings on the average user, these gatekeepers recently started to introduce personalization features, algorithms that filter information per individual. In this paper we show that these online services that filter information are not merely algorithms. Humans not only affect the design of the (...) algorithms, but they also can manually influence the filtering process even when the algorithm is operational. We further analyze filtering processes in detail, show how personalization connects to other filtering techniques, and show that both human and technical biases are present in today’s emergent gatekeepers. We use the existing literature on gatekeeping and search engine bias and provide a model of algorithmic gatekeeping. (shrink)

When ethical decisions have to be taken in critical, complex medical situations, they often involve decisions that set the course for or against life-sustaining treatments. Therefore the decisions have far-reaching consequences for the patients, their relatives, and often for the clinical staff. Although the rich psychology literature provides evidence that reasoning may be affected by undesired influences that may undermine the quality of the decision outcome, not much attention has been given to this phenomenon in health care or ethics consultation. (...) In this paper, we aim to contribute to the sensitization of the problem of systematic reasoning biases by showing how exemplary individual and group biases can affect the quality of decision-making on an individual and group level. We are addressing clinical ethicists as well as clinicians who guide complex decision-making processes of ethical significance. Knowledge regarding exemplary group psychological biases (e.g. conformity bias), and individual biases (e.g. stereotypes), will be taken from the disciplines of social psychology and cognitive decision science and considered in the field of ethical decision-making. Finally we discuss the influence of intuitive versus analytical (systematical) reasoning on the validity of ethical decision-making. (shrink)

Necessity, but not possibility, is typically thought to be rare and suspicion-worthy. This manifests in an asymmetry in the burden of proof incurred by modal claims. In general, claims to the effect that some proposition is impossible/necessary require significant argumentative support and, in general, claims to the effect that some proposition is possible/contingent are thought to be justified freely or by default. Call this the possibility bias. In this paper, I argue that the possibility bias is not epistemically (...) justified. We should regard possibility with at least as much suspicion, that is to say as incurring at least as much of an explanatory demand, as necessity. In fact, I suggest that we might even be justified in reversing the burden of proof asymmetry and adopting a necessity bias. This has quite radical implications for philosophical methodology and hence for many first-order philosophical concerns. (shrink)

Research on bias in peer review examines scholarly communication and funding processes to assess the epistemic and social legitimacy of the mechanisms by which knowledge communities vet and self-regulate their work. Despite vocal concerns, a closer look at the empirical and methodological limitations of research on bias raises questions about the existence and extent of many hypothesized forms of bias. In addition, the notion of bias is predicated on an implicit ideal that, once articulated, raises questions (...) about the normative implications of research on bias in peer review. This review provides a brief description of the function, history, and scope of peer review; articulates and critiques the conception of bias unifying research on bias in peer review; characterizes and examines the empirical, methodological, and normative claims of bias in peer review research; and assesses possible alternatives to the status quo. We close by identifying ways to expand conceptions and studies of bias to countenance the complexity of social interactions among actors involved directly and indirectly in peer review. (shrink)

Data‐driven algorithms are widely used to make or assist decisions in sensitive domains, including healthcare, social services, education, hiring, and criminal justice. In various cases, such algorithms have preserved or even exacerbated biases against vulnerable communities, sparking a vibrant field of research focused on so‐called algorithmic biases. This research includes work on identification, diagnosis, and response to biases in algorithm‐based decision‐making. This paper aims to facilitate the application of philosophical analysis to these contested issues by providing an overview of three (...) key topics: What is algorithmic bias? Why and how can it occur? What can and should be done about it? Throughout, we highlight connections—both actual and potential—with philosophical ideas and concerns. (shrink)

Future-biased agents care not only about what experiences they have, but also when they have them. Many believe that A-theories of time justify future bias. Although presentism is an A-theory of time, some argue that it nevertheless negates the justification for future bias. Here, I claim that the alleged discrepancy between presentism and future bias is a special case of the cross-time relations problem. To resolve the discrepancy, I propose an account of future bias as a (...) preference for certain tensed truths properly relativized to the present. (shrink)

Social Conformity and Response Bias Revisited: The Influence of "Others" on Japanese Respondents This study was undertaken to investigate the impact of other respondents' answers on individual responses in survey studies. The study employed four different conditions and manipulated the direction and the level of social pressure. The results have confirmed that social desirability bias hugely impacts individual answers. It was found that respondents are seven times more likely to choose a socially unacceptable option if majority of the (...) preceding respondents also have chosen the same option. Additionally, the existence of an interviewer during data collection was found to be a factor pressuring respondents to give more socially acceptable responses. (shrink)

Humans typically display hindsight bias. They are more confident that the evidence available beforehand made some outcome probable when they know the outcome occurred than when they don't. There is broad consensus that hindsight bias is irrational, but this consensus is wrong. Hindsight bias is generally rationally permissible and sometimes rationally required. The fact that a given outcome occurred provides both evidence about what the total evidence available ex ante was, and also evidence about what that evidence (...) supports. Even if you in fact evaluate the ex ante evidence correctly, you should not be certain of this. Then, learning the outcome provides evidence that if you erred, you are more likely to have erred low rather than high in estimating the degree to which the ex ante evidence supported the hypothesis that that outcome would occur. (shrink)

Recent philosophy has paid considerable attention to the way our biases are liable to encroach upon our cognitive lives, diminishing our capacity to know and unjustly denigrating the knowledge of others. The extent of the bias, and the range of domains to which it applies, has struck some as so great as to license talk of a new form of skepticism. I argue that these depressing consequences are real and, in some ways, even more intractable than has previously been (...) recognized. For the difficulties we face in this domain are fueled not only by implicit biases but by various other sorts of entrenched cognitive attitudes we bear toward others, whether or not we judge them to be our peers. Inasmuch as the epistemic standing of this broader set of attitudes is itself quite dubious, the problem of epistemic injustice turns out to be just one special case—albeit of a particularly nasty kind—from a broader domain of cases where the collaborative character of knowledge clashes with tendencies that make collaboration difficult. This makes the threat of skepticism all the greater, and at the same time makes it harder to see what path of escape there might be. (shrink)

At the University of Sheffield during 2011 and 2012, a leading group of philosophers, psychologists, and others gathered to explore the nature and significance of implicit bias. The two volumes of Implicit Bias and Philosophy emerge from these workshops. Each volume philosophically examines core areas of psychological research on implicit bias as well as the ramifications of implicit bias for core areas of philosophy. Volume I: Metaphysics and Epistemology is comprised of two parts: “The Nature of (...) Implicit Attitudes, Implicit Bias, and Stereotype Threat,” and “Skepticism, Social Knowledge, and Rationality.” The first part contains chapters examining the relationship between implicit attitudes and “dual process” models of the mind; the role of affect in the formation and change of implicit associations; the unity (or disunity) of implicit attitudes; whether implicit biases are mental states at all; and whether performances on stereotype-relevant tasks are automatic and unconscious or intentional and strategic. The second part contains chapters examining implicit bias and skepticism; the effects of implicit bias on scientific research; the accessibility of social stereotypes in epistemic environments; the effects of implicit bias on the self-perception of members of stigmatized social groups as rational agents; the role of gender stereotypes in philosophy; and the role of heuristics in biased reasoning. (shrink)