[Accepted for publication in Introduction to Implicit Bias: Knowledge, Justice, and the Social Mind. Waiting to be copyedited. Volume will be submitted to Routledge in August 2019.] Bias and Knowledge: Two Metaphors Erin Beeghly Chapter Overview: 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. 1. Introduction In the fall of 2016, The New York Times published a six-part series of videos-Who Me? Biased?-about implicit bias and race. Part of the challenge of these videos was to convey, as quickly and effectively as possible, what implicit bias is and why anyone should care about it. To meet this challenge, filmmaker Saleem Reshamwala used metaphor. In the first video, he explained to viewers that biases are "little mental shortcuts that hold judgments that you might 2 not agree with" (Reshamwala 2016). One of his guests, psychologist Dolly Chugh, likened implicit bias to a "fog that you've been breathing in your whole life." These two metaphors-bias as fog and bias as shortcut-are two of many metaphors that one finds in popular and academic writing about implicit bias. One TedX presenter explains to her audience that implicitly biased people live "in the matrix"-a reference to a 1990s film in which characters believe that they are in touch with reality but their experiences are in fact generated by a computer (Funchess 2014). In Blindspot: Hidden Biases of Good People, psychologists Mahzarin Banaji and Anthony Greenwald write that implicit biases are "mind bugs," deploying a computer programming metaphor (Banaji & Greenwald 2013: 13). Nilanjana Dasgupta uses the image of a mirror, writing that biases are "mirror-like reflections" of the social world (Dasgupta 2013: 240). In this essay, I examine two of the most striking metaphors mentioned above: bias as fog and bias as shortcut. I argue that each metaphor makes a distinctive claim about the relationship between bias, knowledge, and error. These metaphors also clarify the range of knowledge-related objections to implicit bias. That is, they tell us that implicitly biased judgments can be wrong in different ways for different reasons. Likewise, the metaphors reveal a deep disagreement among theorists of bias. According to some theorists, implicitly biased judgments are always bad from the perspective of knowledge. According to others, biased judgments can be rational in certain cases and may even help us to gain knowledge about the world. 2. What is an Epistemic Objection? 3 The word "epistemic" comes from the Greek word "epistēmē," meaning "knowledge." Epistemic objections are objections concerning knowledge and belief (cf. Introduction). Imagine a teenager and a parent having an early morning conversation. The parent says to the teen, "You should get ready to go. The bus will be here at 8:30am." The teen replies, "That's not true. The bus is coming at 8:50." The teen is making an epistemic objection. She is arguing that her father's belief is false. Suppose the parent tries to defend his claim by saying, "I know the bus schedule. Get ready." The teen replies: "You shouldn't trust your memory. I just checked my phone for the latest bus times. The next bus is coming at 8:50." These are epistemic objections too. The teen asserts that her father's belief is unwarranted by the evidence; moreover, she points out that the way in which he formed the belief is unreliable or perhaps less reliable than the way in which she formed hers. As this example suggests, epistemic criticism is a constant feature of human life. Humans constantly evaluate each other in epistemic terms, and we are capable of reflecting on the ways in which our own judgments and processes of reasoning could be improved. 2. Metaphors and The Epistemic Significance of Bias What are the best epistemic objections to implicit bias? Is there a single objection that always applies when people make biased judgments? Might there be cases in which implicitly biased judgments are permissible or even good from the perspective of knowledge? Or, are biased judgments necessarily bad from an epistemic point of view? 4 When trying to understand how one might answer these questions, it is useful to start with metaphors. Metaphors often serve as what philosopher Elisabeth Camp calls interpretative frames. Camp explains: ...a representation [which could be visual or linguistic in nature] functions as a frame when an agent uses it to organize their overall intuitive thinking...a frame functions as an overarching, open-ended interpretative principle: it purports to determine for any property that might be ascribed to the subject, both whether and how it matters (Camp forthcoming: 5). Two features of frames are especially important. First, they make certain features of a person or thing salient in cognition or perception. Also, Camp says, metaphors attribute centrality to certain features of a person, group, or thing. For example, they identify some features of a thing as having special causal powers and as especially important to making the thing what it is (6). To better understand these two effects of metaphor, consider an example. In the play Romeo and Juliet, Romeo says about his love interest, "Juliet is the sun." Romeo's use of metaphor renders a specific feature of Juliet salient: her stunning physical beauty, i.e., her "hotness." As Juliet's beauty becomes salient, other features of her recede into the background. The metaphor also attributes centrality to Juliet's beauty. Her desire-inducing physical appearance is what makes Juliet worthy of Romeo's love and devotion. It is a driver of drama in the play and is asserted to be crucially important to making Juliet the special person she is. 5 Here is what Camp's view suggests. The metaphors used to talk about implicit bias are not mere rhetorical flourishes whose main purpose is to make discussions of implicit bias more exciting or accessible. On her view, metaphors are cognitively crucial. They reveal how speakers intuitively conceptualize a phenomenon like implicit bias. Camp puts the point like this: metaphors-and interpretative frames more generally-provide the "intuitive 'mental setting' (Woodfield 1991, 551) or background against which specific beliefs and questions are formulated" (3; Lakoff & Johnson 1980). If she is correct, investigating the metaphors associated with implicit bias will tell us something interesting about how theorists intuitively understand bias and its epistemic significance. These metaphors will also give us a vivid entry point into thinking about when and why implicit biased judgments are problematic from an epistemic point of view. 4. Living in a Fog Start with the metaphor of fog. Fog is "a state of the weather in which thick clouds of water vapor or ice crystals suspended in the atmosphere form at or near the earth's surface, obscuring or restricting visibility to a greater extent than mist" (OED 2017a). At the website for Take the Lead-an organization that promotes women in business-writer Michele Weldon says: Implicit gender bias has hung around women leaders in the workplace in nearly every imaginable sector and discipline for generations. The bias surrounds the workplace culture in a fog at times thick and impenetrable, and at other times, a mist that only feels instinctively palpable (Weldon 2016). 6 If implicit bias is fog, the effect is obvious: people will have a hard time perceiving the world as it really is (cf Siegel, Ch. 5). Sensory perceptions of other people and the world will become fuzzy, impaired. If you look at someone through a fog, for example, you might think, "I can't really see you as you are. I see the fog, and I see a blurry version of you." In the Times video, the metaphor is taken a step further. Not only does fog obstruct visual and auditory perception, it becomes internalized. "We've all grown up in a culture," says Chugh, "with media images, news images, conversations we've heard at home, and education...think of that as a fog that we've been breathing our whole lives, we never realized what we've been taking in." That fog, Reshamwala adds, "causes associations that lead to biases." For example, when you hear peanut butter, you think jelly. That association exists because peanut butter and jelly are typically paired together in our culture. Similarly, Chugh observes, "in many forms of media, there is an overrepresentation of black men and violent crime being paired together." The result is, as educational scholar Shaun Harper puts it in the video, "deep down inside we have been taught [or perhaps have simply absorbed the view] that black men are violent and aggressive and not to be trusted, that they're criminals, that they're thugs." Remember that metaphors, like all interpretative frames, are supposed to do two important things. First, they render certain aspects of a phenomenon more salient in cognition, and they assert claims about the causal centrality of certain properties. What becomes salient if we think of implicit bias as fog? Here is one thing: its epistemic badness. Bias, if it is a kind of fog, clouds vision and distorts hearing. Cognitive fog is no better. 7 When people talk about the fog of war, what they mean is that war creates an environment where soldiers cannot think clearly, cannot accurately evaluate risks, and cannot make good decisions. Oppressive social conditions create something similar, according to this metaphor: the fog of oppression. This way of thinking about bias resonates, in particular, with theorists of oppression, especially philosophers of race. In The Racial Contract, for example, Charles Mills describes conditions of white supremacy as requiring "a certain schedule of structured blindness and opacities in order to establish and maintain the white polity" (Mills 1999: 19). Applied to bias, the thought is something like this. Many folks today may not explicitly endorse racist, sexist, classist, or otherwise prejudiced views. Yet they-especially but not exclusively members of dominant groups-absorb these problematic views and, as a result, think and act in ways that reproduce conditions of injustice. Even so, they do not recognize themselves as being part of the problem; sometimes they don't even realize that there is a problem. Mills prefers to use the metaphor of collective hallucination to describe this state of ignorance (18). But fog is supposed to function similarly. For oppressive conditions to persist, the fog/hallucination must continue. How does bias-understood as fog-frustrate accurate vision and cognition? Here is one possibility: through group stereotypes. Stereotypes fit the description of 'fog' at least in one way. They exist in the world and not just in individuals' minds. During the eighteenth and nineteenth centuries, the word "stereotype" was a technical term in the printing industry. Stereotypes were the metal plates used in printing presses (see Figure A). The process of creating these plates was called 'stereotyping.' The first book stereotyped in the U.S. was the New Testament in 1814. By 8 the early twentieth century, every newspaper office had a stereotyping room, where both fullpage plates for regular pages and smaller plates for advertising were produced. Common images and phrases reproduced by this technology were also deemed "stereotypical." In the Figure B, for instance, one sees a stereotypical Japanese person as represented in U.S. World War II propaganda. In Figure C, one finds a stereotypical image of 'nerdy' Asian American kids from the late 1980s, featured on the cover of Time Magazine. Remember what Chugh says: media and news images partially constitute the fog. This claim dovetails with assertions by feminist scholars that stereotypes exist "in the social imaginary" (Fricker 2007; Rankine and Loffreda 2017) and in "the mind of the world" (Siegel 2017). Figure A: Example of Stereotype Plate for Printing Press Figure B: Stereotypical Image of Japanese Person in WWII Propaganda 9 Figure C: Stereotypic Image of Nerdy Asian-American Kids (1987) A very common claim about stereotypes-which would explain why they constitute a kind of fog-is that stereotypes are necessarily false or misleading. As philosopher Lawrence Blum notes, By and large, the literature on stereotypes (both social psychological and cultural) agrees that the generalizations in question are false or misleading, and I think this view generally accords with popular usage...The falseness of a stereotype is part of, and is a necessary condition of, what is objectionable about stereotypes in general (Blum 2004: 256). If stereotypes were always false or misleading, one could diagnose what is epistemically wrong with implicit bias in simple terms. Implicit biases would be constituted by group stereotypes. Once internalized, stereotypes would cause individuals to form inaccurate beliefs about social groups and the individuals that belong to them. 10 Thinking about the metaphor of bias as fog thus leads us to think of the epistemic significance of implicit bias in a particular way. Biases are always epistemically bad, if we adopt the metaphor, and their badness is multi-dimensional. Biases are widely thought to articulate false or misleading claims about groups, which-once internalized-taint perceptual and cognitive judgments about individuals. 5. Taking Short Cuts If one were looking for the most popular metaphor about bias, there would be no contest. Implicit bias is most often thought of as a shortcut (Ross 2014; Google 2014; UCLA 2016). In The Times video, one finds this metaphor alongside bias as fog. Yet the convergence is puzzling. The two metaphors have contradictory implications when it comes to the epistemic significance of bias. They also potentially diverge in their appraisals of when and why implicitly biased judgments undermine knowledge. To see this, think about what a shortcut is. Here are two definitions: "a path or a course taken between two places which is shorter than the ordinary road" and "a compendious method of attaining some object" (OED 2017b). The metaphor of bias as a shortcut is largely due to psychologists Daniel Kahneman and Amos Tversky. Since the early 1970s, their work on heuristics and biases has been enormously influential in psychology, economics, legal theory, and philosophy (Kahneman & Tversky 1973a; 1973b; 1974). Humans, they argue, often engage in fast ways of thinking. Fast thinking 11 saves time and mental energy. It also sometimes results in correct predictions and can be reasonable. However, fast thinking is unreliable in certain contexts, leading "to severe and systematic errors" (Tversky & Kahneman 1973a: 237). Their life's work consists in documenting the myriad of ways in which biases cause unreliable judgments. In the 1980s and 90s, Kahneman & Tversky's work was taken up by social psychologists who studied stereotyping. In an influential textbook on social cognition, Susan Fiske and Shelley Taylor wrote that humans are "cognitive misers" (Fiske & Taylor 1984). We have limited time, knowledge, and attention. Because of this, they argue, humans automatically opt for quick, efficient ways of thinking. Hence we stereotype. Stereotyping is a substitute for more careful, slow ways of forming judgments about individuals. To see how biases function as shortcuts, consider an example that I have used elsewhere, which I call I Need a Doctor. Imagine a panicked father in an emergency room, holding an unconscious child in his arms. "Where is the doctor?" he might yell, "I need a doctor." The man might grab the first person he sees in a white coat, relying on the stereotype that doctors wear white coats, not caring that he is grabbing this or that particular doctor, not caring about the doctor at all in their individuality. Using shortcuts sometimes works. However, it will sometimes also fail. For example, during a recent emergency room visit, I saw a sign on the wall. It read: "Doctor wears blue scrubs." A sign like this was necessary because white coats are strongly associated with doctors. Stereotypically, doctors wear white coats. As one M.D. puts it, the white coat "has served as the preeminent symbol of physicians for over 100 years" (Hochberg 2007: 310). Likewise, white coats are associated with competence. As one recent study found: "patients 12 perceived doctors as more trustworthy, responsible, authoritative, knowledgeable, and caring in white coats" (Tiang et al. 2017: 1). When the father reaches for the person in the white coat, he is thus doing something entirely typical. He is using a stereotypic association to identify someone as a doctor, and he is forming expectations about that person on that basis. Depending on how one describes the details of this case, his judgment may even count as a manifestation of implicit bias. However we describe the case, this much is clear: his judgment and behavior betrays reliance on a cognitive shortcut. What is rendered salient if we think of implicit biases as shortcuts? Their epistemic virtues! Shortcuts are, by definition, "compendious," which means "economical," "profitable," "direct," and "not circuitous" (OED 2017c). To call stereotypes shortcuts is thus to pay them a compliment. It is to underscore their pragmatic and cognitive utility. This metaphor also emphasizes the universality of bias. Philosopher Keith Frankish writes: an implicitly biased person is one who is disposed to judge others according to a stereotyped conception of their social group (ethnic, gender, class, and so on), rather than by their individual talents (Frankish 2016: 24). Since all humans have the disposition to use stereotypic shortcuts, we are all biased. In The Times videos, Reshamwala emphasizes the normalcy and universality of bias repeatedly. "If you're seeing this," he says, "and are thinking that it doesn't apply to you. Well, you might be falling prey to the blindspot bias. That's a scientific name for a mental bias that allows you to see 13 biases in others but not yourself. We're [all] biased!" The universality of bias is due to the fact that stereotypes-in the form of schemas associated with social groups-structure human cognition in foundational ways (Beeghly 2015). One can already see how the metaphor of bias as shortcut differs from that of bias as fog. When someone says implicit bias is fog, they are committed to saying that it is always an obstruction, something that makes it harder to perceive and judge individuals clearly. When someone says that bias is a shortcut, they imply-whether intentionally or not-that biases could facilitate perception and judgment by providing an efficient means of judging and making predictions about individuals. In medical contexts where doctors wear white coats, for example, and hospital staff wears other attire, relying on the stereotype of doctors as wearing white coats will help you quickly and reliably predict who is and who is not doctor. It is also possible that some stereotypes are based on a lifetime of experience, perception, even wisdom, including stereotypes based on gender, ethnicity, and religion. 5.1 The Diversity of Epistemic Objections to Bias In addition to revealing the potential epistemic benefits of bias, the metaphor of bias as shortcut also invites us to think more carefully about the conditions under which implicitly biased judgments are epistemically problematic. Consider, first, the objection that implicit biases are constituted by false, unwarranted stereotypes. As I noted in section 4, stereotypes are typically thought of as false or misleading 14 group generalizations. Often they are also thought to be unwarranted by evidence. This way of thinking about stereotyping fits perfectly with the metaphor of bias as fog. However, once one starts to think of stereotypes as shortcuts, one begins to wonder, "is it really true that stereotypes are always false and based on limited experience?" Think about the following gender stereotype: women are empathetic. This stereotype is likely true, if considered as a claim about most women or as a claim about the relative frequency of empathic characteristics in women compared to men. We live in a patriarchal society. When women in a society like ours are raised to value empathy and actually tend to self-describe as empathic, when they tend to fill social roles where empathy is required or beneficial, women will, on average, have a greater disposition for empathy than men and one that is stable over time (Klein & Hodges 2001; Ickes 2003). Accordingly, the claim that women are empathetic could be true. Moreover, as feminist scholars have argued about similar stereotypes, we would be justified in implicitly or explicitly believing it was true (de Beauvoir 1953: xxiv; Haslanger 2012: 449; Haslanger 2017: 4). Such observations complicate epistemic evaluations of bias. If biased judgments were always based on false, unwarranted beliefs about groups, we would have a decisive epistemic objection to people using them. Of course one shouldn't deploy false, unwarranted beliefs to judge individuals. On the other hand, if the stereotypes that drive biased judgments might sometimes be true and warranted by the evidence, one cannot always invoke this objection to explain why people should never judge others in implicitly biased ways. After all, the objection will only sometimes apply. To find an objection that always applies, one must get more creative. 15 Thinking of biases as shortcuts helps here. In the literature on heuristics and biases-where the metaphor that we are considering originated-authors tend to articulate epistemic objections that apply to processes of reasoning that involve stereotyping. Consulting this literature, one finds ample reason to think that implicitly biased judgments are always or usually unreliable. The reason for their unreliability is not premised on the falsity or lack of justification of stereotypes. Biased judgments would be unreliable, according to these theorists, even if the stereotypes being deployed were true and warranted. Here are three examples. (A) The Representativeness Heuristic. Suppose someone handed you the following character sketch: Steve is shy and withdrawn, invariably helpful but with little interest in people or in the world of reality. A meek and tidy soul, he has need for order and structure and a passion for detail (Kahneman 2011: 7). That person then asks you, "Is it more probable that Steve is a librarian or a farmer?" What would you say? If you were like typical research participants, you would say that Steve is probably a librarian. In giving this answer, one relies on what Tversky and Kahneman call the representativeness 16 heuristic. Here is the OED definition of a heuristic, as understood by psychologists: "designating or relating to decision making that is performed through intuition or common sense" (OED 2017d). The opposite of heuristic is "systematic." Systematic ways of reasoning adhere to the norms of ideal rationality, as modeled by decision theorists. When people use the representativeness heuristic, they make judgments about the likelihood of people having this or that property-for example, the property of being a librarian-based on stereotypes. Thinking quickly, we automatically expect that Steve will be a librarian because he fits the stereotype of a librarian. The problem with using the representativeness heuristic is that it involves ignoring a great deal of other information. "Did it occur to you," writes Kahneman, that there are 20 male farmers for each librarian in the United States? Because there are so many farmers, it is almost certain that more meek and tidy souls will be found at tractors than at library desks (7). If you stereotyped Steve, he says, you committed base rate neglect. A person neglects base rates if they ignore background statistics-such the percentages of librarians and farmers in the population at large-when reasoning. Implicitly biased people, one might worry, always make judgments by ignoring base rates. Their predictions and expectations of individuals are thus unreliable. 17 (B) The Availability Heuristic. Implicitly biased people also make use of the availability heuristic. When people use this heuristic, Kahneman says, their task is to estimate the size of a category or the frequency of an event but ... [they instead] report an impression of ease with which instances come to mind" (130). Because one is not paying attention to actual probabilities, one ends up overestimating or underestimating the probability of an event or property occurring (Tversky & Kahneman 1973b; Lichtenstein et al 1978). This effect very often occurs when properties are dangerous or striking. But it may occur in other cases as well. The mere existence of a trait as part of a cultural stereotype may bring it more easily to mind than would otherwise be the case. For example, we may overestimate the percentage of mothers among women because, stereotypically, women bear children. If implicitly biased people use the availability heuristic, they would often have unreliable predictions, expectations, educated guesses, and beliefs about individuals. (C) The Affect Heuristic. Implicit biases may also leave us open to non-cognitive biases. Stereotypes can bring to mind aversions and affinities and are often laden with evaluative and emotional significance (Madva & Browstein 2016). Some of the most interesting work on affect and biases has been done by Paul Slovic and colleagues. Slovic introduced the idea of an affect heuristic. As before, the idea with heuristics is that people aim to find easy ways of answering questions when thinking quickly and intuitively. Emotions can be helpful for this purpose. A person may simply consult his feelings to determine what he should think and do. If one's feelings are clear cut, one can 'just go with it' and suppose 18 that affect provides the right answer to the question. "Using an overall, readily available affect impression can be easier and more efficient than weighing the pros and cons of various reasons or retrieving relevant examples from memory," writes Slovic, "especially when the required judgment or decision is complex or mental resources are limited" (Slovic et al. 2004: 314). Think, first, about the content of stereotypes. Stereotypes will often be affectively laden. Just as people vastly overestimate the likelihood of being attacked by a shark while swimming due to fear, they may vastly overestimate the likelihood that individuals from stigmatized groups will possess negative properties stereotypically attributed to them. Emotion-not facts-would guide estimation of probabilities. Of course emotions-especially ones like fear-are not a reliable sources of probabilistic information. So using this heuristic in conjunction with stereotypes would lead to unreliable judgments. A second observation concerns relationship between moods, quick thinking, and stereotyping. What psychologists have found is that people in happy or positive moods often think quickly, hence they tend to stereotype (Park J. & M. Banaji 2000; Chartrand, Van Baaren, & Bargh 2006; Forgas 2011; Holland et al. 2012). For example, Forgas (2011) asked research participants to read a one-page philosophy essay written by "Robin Taylor." Attached to the essay was either a picture of a middle-aged white man with glasses-a stereotypical-looking philosopher-or a young white woman with "frizzy" hair-someone who poorly fits the stereotype of a philosopher. When the essay was attributed to the middle-aged white male, participants tended to rate it more positively. This bias was most pronounced when participants were in a good mood. In contrast, participants in bad moods were less influenced by stereotypes when evaluating the 19 essay. They spent more time reading and thinking about the essay, and they evaluated the essay as just as good no matter who wrote it. As such experiments show, affect plays a complex role in our epistemic life and can undermine our ability to evaluate others in fair, unbiased ways (Madva 2018). By paying attention to the literature on biases and heuristics, we seem to have found a promising epistemic objection to biases. The objection is that biased judgments are unreliable because they are the product of fast thinking. What we need to do, the argument goes, is to slow down, reason more carefully, and judge persons as individuals. Have we now found a foolproof objection to bias? Perhaps not. Within the literature on heuristics and biases, theorists often do not make the above argument. They argue that fast thinking will sometimes but not always lead us astray (Kahneman & Tversky 1973a: 48; Jussim 2012: 360388). For instance, Kahneman offers a list of purportedly accurate stereotypes, including "young men are more likely than elderly women to drive aggressively" (2011: 151). According to him, because stereotypes like this track the truth, they are reliable. So the representativeness heuristic-despite his emphasis on the ways in which it fails in certain contexts-will not always violate norms of epistemic rationality; nor will it always be untrustworthy in terms of the knowledge it provides. The point generalizes. In medical contexts where doctors exclusively wear white coats, we may be able to reliably pick out who is and is not a doctor based on attire. Similar claims can be made about gender stereotypes like 'women are empathetic.' 20 This line of argument picks up further steam when one considers that stereotyping-a major cause of biased judgments and perception-shares a good deal in common with inductive reasoning about kinds of things in general. Notice that we have "pictures in our heads" of lightning storms and rivers, tables and skyscrapers, skunks and otters, just as we have stereotypes of social groups. We make generalizations about all kinds of things, and doing so is epistemically useful. By relying on kind-based generalizations, we save time and energy. We get around better in the world, having a better sense of what to expect from new things, situations, and people. We can avoid potentially dangerous situations and seek out advantageous ones. Stereotyping can also fail in all the same ways as kind-based reasoning more generally. We may form stereotypes based on a limited sample size then overgeneralize. Our past experience with social groups may not be a reliable guide to the future. Our expectations can lead us to pay attention only to what confirms them and ignore disconfirming evidence. We may systemically over-estimate the likelihood of events based on heuristics. Despite these problems, no one is tempted to say that kind-based reasoning in general is always epistemically bad. The above claims culminate in what I call the argument from symmetry. The argument goes like this. If we claim that it is always epistemically bad to use stereotypes (which is what happens when people make implicitly biased judgments), we will have to endorse this thought in other domains as well. For example, we will have to say that there is always something epistemically bad with forming expectations about objects like chairs or nonhuman animals or physical events like lightning storms on the basis of group membership. Yet, the argument continues, it is very hard to believe that kind-based reasoning about anything whatsoever is necessarily epistemically 21 problematic. Parity of reasoning requires us to see stereotyping people as sometimes rational and, indeed, potentially good from the perspective of knowledge in certain contexts. In response to this argument, one could insist that stereotypic judgments about humans are never permissible: we have an epistemic and ethical duty to judge persons as individuals. However, it is not clear that such a duty exists or, if it does, how to articulate it. Philosopher Benjamin Eidelson notes: Taken literally, the principle [of treating persons as individuals] seems to express a broad hostility to forming judgments about individual people by appeal to generalizations about whole classes of people (Eidelson 2013: 204). It is absurd to think that epistemic norms require never using group generalizations (Levin 1992: 23; Schauer 2006: 19; Arneson 2007: 787). We would lack schemas for organizing our social world. We couldn't learn about groups of people. We would be forbidden from categorizing unfamiliar individuals as members of types and forming expectations about them based on group membership. For example, in I Need a Doctor, the father would be forbidden on epistemic grounds from identifying the white-coated person as a doctor. The injunction to always treat persons as individuals in the way specified above is not only epistemically odd; it is also ethically troubling. Imagine a woman who believes that people of color in her community are often subject to police harassment. When she sees an unfamiliar 22 black man, she expects that he, too, has likely experienced police harassment at some point in his life. This person is "using race as a proxy for being subject to unjust race-based discrimination," as Elizabeth Anderson puts it (Anderson 2010: 161). She is thus failing to treat someone as an individual. Yet, I would say, she has done nothing epistemically or ethically wrong as of yet. Indeed, stereotyping here may be the best ethical and epistemic response. Perhaps the epistemic and moral duty to treat person as individuals can be interpreted in a more plausible way. For example, Kasper Lippert-Rasmussen has suggested: X treats Y as an individual if, and only if, X's treatment of Y is informed by all relevant information, statistical or non-statistical, reasonably available to X (Lippert-Rasmussen 2011: 54). Call this the use-all-your-information conception of treating persons as individuals. Adopting this conception, one might argue that implicitly biased people always fail to treat persons as individuals because they fail to use all relevant, reasonably available information when judging others. Such a claim fails, however. Biased judgments will only sometimes involve failing to treat person as individuals, as defined above. When agents face serious informational deficits-and thus have very little information reasonably available to them-they will count as treating persons as individuals, even if they stereotype others based on group generalizations (Beeghly 2018). Likewise, it is possible for someone to use all the relevant information reasonably 23 available to her in forming a prediction about someone; yet implicit group stereotypes-which she might disavow-may corrupt how she interprets or weighs that information. In such a case, her judgment would be epistemically problematic. But the reason why it is problematic is not that she has failed to use all of her information. What's gone wrong is something different. Though she uses all her information, she fails to weigh different pieces of evidence appropriately. What is the upshot? Perhaps it is that the range of epistemic objections to implicit bias is astoundingly wide. Or, maybe the lesson here is that no single epistemic problem will be present in all epistemically problematic cases of implicitly bias. The last possibility is very important to philosophers. One thing that philosophers like to do is create theories. A theory of what's epistemically wrong with implicit bias could be unified or non-unified. Unified theories are so-called because they identify a single property or set of properties that all epistemically bad cases of bias allegedly have in common, in virtue of which the cases count as bad. Non-unified theories are so-called because they identify multiple properties that bad cases of bias might have in common. Though all wrongful cases are alleged to share one of many wrong-making properties specified in the list, no single property mentioned on the list will be found in every wrongful case. If the analysis so far is on the right track, we should not expect a unified theory of what's epistemically wrong with implicit bias to succeed. Certainly implicit biases hamper our knowledge in many cases, but there seems to be no single objection that fully explains why they 24 do so in every case. Just as importantly, we have not yet been able to definitively rule out the possibility that implicitly biased judgments are sometimes epistemically rational and are, perhaps even, sometimes unobjectionable from an epistemic point of view. An important project for future research is to consider these issues more systemically, in the hopes of better understanding the conditions under which implicitly biased judgments are epistemically problematic. 5.2 Why Implicit Biases are Not Just Shortcuts I am not fully onboard with the metaphor of bias as shortcut, despite its advantages. There are a few reasons why. First, thinking of bias as a shortcut encourages us to believe that biased judgments are primarily due to quick thinking. If that were true, we could rid ourselves of biases by attending more carefully to the facts. Yet, as philosopher Louise Antony notes, ...it is a kind of fantasy to think that biases intrude only when our guard is down-a fantasy that permits us to think that if we were only more careful in our thinking, more responsible or more virtuous in our epistemic practice, things would be all right. That leaves intact the conviction that there is within each one of us some epistemic still place from which we can see clearly and judge soundly... (Antony 2016: 160). The reality is that stereotypes are always with us. They structure how we-as humans-see the world and move in it. Even when thinking carefully, biases can shape our judgments. A recent 25 meta-analysis of the role of gender in hiring decisions, for example, found that people who were motivated not to discriminate displayed less gender bias when evaluating women job candidates in male-dominated fields; however, they were still not able to get rid of their biases completely (Koch et al. 2015). Second, by using the metaphor of a shortcut, one implies that biased people are holding and using stereotypes because they are lazy, rushed for time, or overwhelmed by the world's complexity (Bargh 1999). However, biased judgments don't just occur because people are pressed for time and overwhelmed with stimuli. They happen because we exist in a world where certain kinds of people stand in particular power relationships to one another. Stereotyping- whether implicit or explicit-is always wrapped up in power, privilege, ideologies, and histories of oppression. Likewise, stereotypes serve an evaluative function and are often used to keep individuals in their 'appropriate' social place (McGreer 2015; Haslanger 2019). It is no accident that the metaphor of bias as shortcut largely hides the ideological and social dimensions of bias. The metaphor identifies implicit biases with mental states; hence it renders the psychological elements of the phenomenon central and salient. Biases are typically described as cognitive shortcuts, after all. Nothing is said about their origin or social function, and their existence is often alleged to be a matter of innate cognitive architecture. The connection between bias, the social world, and group oppression-which was foregrounded in the metaphor of bias as fog-is thus lost. 6. Concluding Thoughts on the Epistemic Significance of Implicit Bias 26 In this chapter, I have explored two metaphors used to think about implicit bias: bias as fog and bias as shortcut. Like any metaphor, neither one is perfect. Both misrepresent the phenomenon of bias in some respects. On the other hand, both metaphors bring something important to the table. Perhaps that is why the two co-exist in the Reshamwala's video for The New York Times. Thinking of bias as a shortcut encourages us to pay attention to the relationship between biased judgments and fast thinking. Thinking of bias as fog, in contrast, brings out its connection to group oppression and the ways in which false stereotypes frustrate knowledge. Considering these two metaphors together is also productive for a different reason: it calls attention to a pressing question about the epistemic significance of bias. That is, what is the actual connection between bias, knowledge, and error? If implicit bias is fog, it is always epistemically bad; however, if biases are shortcuts, implicitly biased judgments are not always bad from the point of view of knowledge. Which claim is correct? Significantly, we are not yet able to definitively answer that question. The crux of the matter is whether implicit bias has any epistemically positive role to play in our individual and collective attempts to gain knowledge of the world and of the people in it. If one is to defend the epistemic claim behind the metaphor of bias as fog, one must push back against the argument from symmetry (mentioned earlier). One strategy is this: identify special epistemic problems that occur when we deploy social stereotypes in perception and cognition, which do not occur when we use other kinds of generalizations (Siegel cf., Chapter 5; Holroyd and Puddifoot cf., Chapter 6). A second strategy is to argue that we face higher epistemic 27 standards when judging persons (and, perhaps, non-human animals) for ethical reasons and, thus, lower epistemic standards apply when we reason about other kinds of things (cf. Basu Chapter 9). A third strategy is to link the use of stereotypes to collective epistemic practices and, in particular, to the existence of epistemic vices like laziness and lack of imagination that flourish in members of socially privileged groups (cf. McHugh and Davidson Chapter 7; Medina 2013). I am not sure which metaphor will ultimately win out-or whether we have to choose. Both are tempting, albeit for different reasons. But, more than anything, what they reveal is how much there is to learn about the conditions under which biased judgments are epistemically problematic. This essay has only been able to scratch the surface. Investigating further, one would have to consider a range of other epistemic objections to biased judgments, actions, and speech (Gendler 2001; Blum 2004; Haslanger 2012; Medina 2013; Munton 2018). Even scratching the surface, one can understand why these two metaphors are so prevalent in popular discussions of implicit bias. They simplify and provide an accessible frame from which to begin deeper philosophical reflections on bias, knowledge, and justice. Might it be possible, for example, that that judging other humans according to reliable shortcuts gives us knowledge but is unethical and unjust? In what ways does oppression impact our evidence and what can be true of people in our world? Such questions bring us to the heart of a deep disagreement about the knowledge and bias, a disagreement that has no end in sight. 28 REFERENCES Anderson, E. (2010) The Imperative of Integration, Princeton, NJ: Princeton University Press. Antony, L. (2016) "Bias: Friend or Foe? Reflections on Saulish Skepticism," in M. Brownstein & J. Saul (eds.) Implicit Bias and Philosophy: Volume 1, Oxford: Oxford University Press, 157190. Arneson, R. (2007) "What is Wrongful Discrimination?" San Diego Law Review, 43: 775-808. Banaji M. & A. Greenwald. (2013) Blindspot: The Hidden Biases of Good People, New York: NY: Delacorte. Bargh, J. (1999) "The Cognitive Monster: The Case Against the Control of Automatic Stereotype Effects," in S. Chaiken & Y. Trope (eds.) Dual-process Theories in Social Psychology, New York, NY: Guilford Press, 361-382. Beeghly, E. (2015) "What is a Stereotype? What is Stereotyping?" Hypatia, 30: 675-691. ----. (2018) "Failing to Treat Persons as Individuals," Ergo, 25 (5): 687-711. Blum, L. (2004) "Stereotypes and Stereotyping: A Moral Analysis," Philosophical Papers, 33: 251-289. Camp. E. (forthcoming) "Imaginative Frames for Scientific Inquiry: Metaphors, Telling Facts, and Just-So Stories," in P. Godfrey-Smith & A. Levy (eds.) The Scientific Imagination: Philosophical and Psychological Perspectives, Oxford: Oxford University Press. Chartrand, T, R. van Baaren, & J. Bargh. (2006) "Linking Automatic Evaluation to Mood and Processing Style: Consequences for Experienced Affect, Impression Formation, and Stereotyping," Journal of Experimental Psychology, 135: 70-77. Dasgupta, N. (2013) "Implicit Attitudes and Beliefs Adapt to Situations: A Decade of Research on the Malleability of Implicit Prejudice, Stereotypes, and the Self-Concept," Advances in Experimental Social Psychology, 47: 233-279. Eidelson B. (2013) "Treating People as Individuals," in D. Hellman & S. Moreau, Philosophical Foundations of Discrimination Law, Oxford: Oxford University Press, 203-227. Fiske, S. & S. Taylor. (1984/1991) Social Cognition, 1st ed, New York, NY: McGraw Hill Inc. Forgas, J. (2011) "She Just Doesn't Look Like a Philosopher...? Affective Influences on the Halo Effect in Impression Formation," European Journal of Social Philosophy, 41: 812-817. Frankish, K. (2016) "Playing Double: Implicit Bias and Self-Control," in M. Brownstein & J. Saul (eds.) Implicit Bias and Philosophy: Volume 1, Oxford: Oxford University Press, 23-46. 29 Fricker, M. (2009) Epistemic Injustice: Power and The Ethics of Knowing, Oxford: Oxford University Press. Funchess, M. (2014) "Implicit Bias-How It Affects Us & How We Push Through" Tedx Talk, [ONLINE], 16 October 2014. Available at https://www.youtube.com/watch?v=Fr8G7MtRNlk [Accessed: 10 June 2017]. Gendler, T. S. (2011) "On The Epistemic Costs of Implicit Bias," Phil Studies 156: 33-63. Google. (2014) "Google Video on Implicit Bias: Making the Unconscious Conscious," [ONLINE], 25 September 2014. Available at https://www.youtube.com/watch?v=NW5s_-Nl3JE [Accessed: 10 June 2017]. Haslanger, S. (2012) "Ideology, Generics, and Common Ground," Resisting Reality: Social Construction and Social Critique, Oxford: OUP. __________. (2019) "Cognition as a Social Tool," Australasian Philosophical Review, forthcoming. Holland, R., M. de Vries, B. Hermsen, & A. van Kippenberg. (2012) "Mood and the AttitudeBehavior Link: The Happy Act on Impulse, The Sad Think Twice," Social Psychology and Personality Science 3: 356-264. Hochberg, M. (2007) "History of Medicine: The Doctor's White Coat-A Historical Perspective," American Medical Association Journal of Ethics, 9: 310-314. Ickes, W. (2003) Everyday Mind Reading: Understanding What Other People Think and Feel, Amherst, NY: Prometheus. Jussim, L. (2012) Social Perception and Social Reality, Oxford: Oxford University Press. Kahneman, D. & A. Tversky (1973) "On the Psychology of Prediction," Psychological Review, 80: 237-251. -----. (1973b) "Availability: A Heuristic for Judging Frequency and Probability," Cognitive Psychology, 5: 207–232. -----. (1974) "Judgment Under Uncertainty: Heuristics and Biases," Science, 185: 11241131. Kahneman, D. Thinking Fast and Slow. New York, NY: Farrar, Strauss, & Girroux, 2011. Kang, J. (2016) "Implicit Bias, Preface: Biases and Heuristics," Bruin X, UCLA Office of Equity, Diversity, and Inclusion [ONLINE], September 9, 2016. Available at: https://www.youtube.com/watch?v=R0hWjjfDyCo&feature=youtu.be [Accessed: 10 June 2017]. 30 Klein, K. & S. Hodges (2001) "Gender Difference, Motivation, and Empathic Accuracy: When It Pays To Understand," Personality and Social Psychology Bulletin 27: 720-730. Koch A., S. D'Mello, & P. Sackett. (2015) "A Meta-Analysis of Gender Stereotypes and Bias in Experimental Simulations of Employment Decision Making," Journal of Applied Psychology, 100: 128-161. Lakoff J. & M. Johnson. (1980) Metaphors We Live By, Chicago, IL: University of Chicago. Levin, M. (1992) "Responses to Race Differences in Crime," Journal of Social Philosophy, 23: 5-29. Lichtenstein et al. "Judged Frequency of Lethal Events," Journal of Experimental Psychology: Human Learning and Memory 4 (1978): 551-578. Lippert-Rasmussen, K. (2011) "We are all Different": Statistical Discrimination and the Right to be Treated as an Individual," Journal of Ethics, 15: 47-59. McGeer, V. (2015) "Mind-Making Practices: The Social Infrastructure of Self-knowing Agency and Responsibility," Philosophical Explorations, 18: 259 – 281. Madva, A. (2018) "Implicit Bias, Moods, and Moral Responsibility," Pacific Philosophical Quarterly, 99 (S1): 53-78. Medina, J. (2013) The Epistemology of Resistance: Gender and Racial Oppression, Epistemic Injustice, and Resistant Imaginations, Oxford: OUP. Mills, C. (1999) The Racial Contract, Ithaca, NY: Cornell University Press. Munton, J. (2017) "Perceptual Skill and Social Structure," Philosophy and Phenomenological Research: 1-31. https://doi.org/10.1111/phpr.12478. Oxford English Dictionary Online. (2017a) "fog, n.2," Oxford University Press [ONLINE] March 2017. [Accessed: 31 May 2017]. -----. (2017b) "shortcut \ short-cut, n.1," Oxford University Press [ONLINE] March 2017. [Accessed: 31 May 2017]. -----. (2017c) "compendious, adj," Oxford University Press [ONLINE] March 2017. [Accessed: 31 May 2017]. -----. (2017d) "heuristic, adj. B1b," Oxford University Press [ONLINE] March 2017. [Accessed: 12 June 2017]. 31 Park, J. & M. Banaji. (2000) "Mood and Heuristics: The Influence of Happy and Sad States on Sensitivity and Bias in Stereotyping," Journal of Personality and Social Psychology, 78: 10051023. Rankine, C. and B. Loffreda. (2017) "The Racial Imaginary," in The Manifesto Project, eds., Rebecca Hazelton and Alan Michael Parker, Akron, OH: University of Akron Press, 162-172. Ross, H. (2014) Everyday Bias: Identifying and Navigating Unconscious Judgments in Everyday Life, New York, NY: Rowman & Littlefield Publishers. Reshamwala, S. (2016) "Peanut Butter, Jelly, and Racism" in Who Me Biased? New York Times Video [ONLINE], Available at: https://www.nytimes.com/video/us/100000004818663/peanutbutter-jelly-and-racism.html [Accessed: 10 June 2017]. Siegel, S. (2017) The Rationality of Perception, Oxford: Oxford University Press. Slovic, P et al. (2004) "Risk as Analysis and Risk as Feelings: Some Thoughts about Affect, Reason, Risk, and Rationality," Risk Analysis, 24: 311-322. Tiang, K.W., A.H. Razack, & K.L. Ng (2017) "The 'Auxiliary' White Coat Effect in Hospitals: Perceptions of Patients and Doctors," Singapore Medical Journal, [ONLINE] 4 April 2017. Available at: doi: 10.11622/smedj.2017023 Weldon, M. (2016) "Implicit Gender Bias: Strategies to Own the Power To Succeed as Women Leaders," The Movement Blog [ONLINE], 1 November 2016. Available at: https://www.taketheleadwomen.com/blog/implicit-gender-bias-strategies-to-own-the-power-tosucceed-as-women-leaders/ [Accessed: 10 June 2017].