Epistemologists spend a great deal of time thinking about how we should respond to our evidence. They spend far less time thinking about the ways that evidence can be acquired in the first place. This is an oversight. Some ways of acquiring evidence are better than others. Many normative epistemologies struggle to accommodate this fact. In this article I develop one that can and does. I identify a phenomenon – epistemic feedback loops – in which evidence acquisition has gone (...) awry, with the result that even beliefs based on the evidence are irrational. Examples include evidence acquired under the influence of confirmation bias and evidence acquired under the influence of cognitively penetrated experiences caused by implicit bias. I then develop a theoretical framework which enables us to understand why beliefs that are the outputs of epistemic feedback loops are irrational. Finally, I argue that many popular approaches to epistemic normativity may need to be abandoned on the grounds that they cannot comfortably explain feedback loops. The scope of this last claim is broad: it includes almost all contemporary theories of justified/rational belief and of the epistemology of cognitive penetration. (shrink)

In this chapter we argue that emotions are mediated in an incomplete way in online social media because of the heavy reliance on textual messages which fosters a rationalistic bias and an inclination towards less nuanced emotional expressions. This incompleteness can happen either by obscuring emotions, showing less than the original intensity, misinterpreting emotions, or eliciting emotions without feedback and context. Online interactions and deliberations tend to contribute rather than overcome stalemates and informational bubbles, partially due to prevalence (...) of anti-social emotions. It is tempting to see emotions as being the cause of the problem of online verbal aggression and bullying. However, we argue that social media are actually designed in a predominantly rationalistic way, because of the reliance on text-based communication, thereby filtering out social emotions and leaving space for easily expressed antisocial emotions. Based on research on emotions that sees these as key ingredients to moral interaction and deliberation, as well as on research on text-based versus non-verbal communication, we propose a richer understanding of emotions, requiring different designs of online deliberation platforms. We propose that such designs should move from text-centred designs and should find ways to incorporate the complete expression of the full range of human emotions so that these can play a constructive role in online deliberations. (shrink)

This paper examines the ways in which social scientific discourse and classification interact with the objects of social scientific investigation. I examine this interaction in the context of the traditional philosophical project of demarcating the social sciences from the natural sciences. I begin by reviewing Ian Hacking’s work on interactive classification and argue that there are additional forms of interaction that must be treated.

The conception of conscience that dominates discussions in bioethics focuses narrowly on private regulation of behaviour resulting from explicit attitudes. It neglects to mention implicit attitudes and the role of social feedback in becoming aware of one's implicit attitudes. But if conscience is a way of ensuring that a person's behaviour is in line with her moral values, it must be responsive to all aspects of the mind that influence behaviour. There is a wealth of recent psychological work demonstrating (...) the influence of implicit attitudes on behaviour. A necessary part of having a well-functioning conscience must thus be awareness and regulation of one's implicit attitudes in addition to one's explicit attitudes; this cannot be done by an individual in isolation. On my revised conception of conscience, heeding social feedback, being emotionally self-aware and engaging in self-monitoring are important for the possession of a well-functioning conscience. Health professionals may need specific training to help them develop and maintain a well-functioning conscience, which should involve cultivation of awareness of implicit attitudes, emphasis on social feedback and techniques to enable better control over them. (shrink)

When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...) unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain. (shrink)

The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper explores the benefits of integrating ChatGPT in education in Thailand. The research strategy employed in this study was qualitative, utilizing in-depth interviews with eight key informants who were selected using purposive sampling. The collected (...) data was analyzed using content analysis and the software NVivo. The study's results indicated that ChatGPT can provide personalized learning experiences by adapting to individual student needs and preferences. Its ability to understand natural language and context can also facilitate more meaningful interactions between students and the system. Additionally, ChatGPT can assist with administrative tasks such as grading and feedback, allowing educators to focus on more personalized and meaningful interactions with students. Furthermore, ChatGPT can serve as a valuable tool for remote learning, providing students with the ability to access educational resources and support outside of traditional classroom settings. The paper also discusses potential ethical considerations in utilizing AI in education, such as data privacy and bias. Overall, this paper argues that the integration of ChatGPT in education has the potential to enhance the learning experience for students by providing personalized, interactive, and efficient support. (shrink)

Humanity may underestimate the rate of natural global catastrophes because of the survival bias (“anthropic shadow”). But the resulting reduction of the Earth’s future habitability duration is not very large in most plausible cases (1-2 orders of magnitude) and thus it looks like we still have at least millions of years. However, anthropic shadow implies anthropic fragility: we are more likely to live in a world where a sterilizing catastrophe is long overdue and could be triggered by unexpectedly small (...) human actions. In the same way, an over-inflated toy balloon, which will soon burst, is very fragile. Anthropic fragility can manifest itself in the higher chances of runaway global warming. It has often been suggested that the Earth's atmosphere remained life-supporting for billions of years by sheer chance. Therefore, the survival bias can be strong. It is also known that Earth-like water worlds could experience transitions into deadly moisture greenhouse (mean T = 65C). This means that relatively small anthropogenic actions could put the climate above an unpredictable tipping point, which could lead to the moisture greenhouse. Thus, it is necessary to carry out urgent geoengineering studies and prepare to prevent an unexpected climate catastrophe. There are three main counterarguments against the existence of the anthropic shadow: self-indication assumption (SIA), past observers and the Gaia hypothesis; we show that they fail. It was proposed that SIA exactly compensates the anthropic shadow as an observer unlikely to find herself in a world with a strong anthropic shadow; however, there is a baseline level of the anthropic shadow for all habitable planets, similar to the rate of evolutionary transitions like abiogenesis. There are no “past observers” as qualified observers appeared only 50 years ago. Gaia hypothesis assumes existence of self-stabilizing feedback in climate, but new types of events like quick CO2 growth could override its coping ability. We present a list of other catastrophes that may have been underestimated because of the anthropic shadow, including collider catastrophes, nuclear war and even an alien invasion. We also hypothesized that human intelligence is more likely to emerge in an unstable world that is nearing its end and thus we get a new form of Doomsday argument. (shrink)

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)

chapter on perception and bias including implicit bias.

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)

The term 'implicit bias' has very swiftly been incorporated into philosophical discourse. Our aim in this paper is to scrutinise the phenomena that fall under the rubric of implicit bias. The term is often used in a rather broad sense, to capture a range of implicit social cognitions, and this is useful for some purposes. However, we here articulate some of the important differences between phenomena identified as instances of implicit bias. We caution against ignoring these differences: (...) it is likely they have considerable significance, not least for the sorts of normative recommendations being made concerning how to mitigate the bad effects of implicit bias. (shrink)

Present-bias is the preference, all else being equal, for positive events to be located in the present rather than the non-present, and for negative events to be located in the non-present rather than the present. Very little attention has been given to present-bias in the contemporary literature on time biases. This may be because it is often assumed that present-bias is not a distinctive psychological kind; that what explains people’s being present-biased is just what explains them displaying (...) various other time-biases. According to this view, there is no need to investigate present-bias independently of investigating these other biases, since present-bias is really just a manifestation of these other biases. We call this the manifestation thesis. We take up the question of whether the manifestation thesis is true, and argue that it is not. Thus, by failing to investigate present-bias in its own right we are failing fully to understand the spectrum of ways in which people display time biases. In turn, we suggest, this may have implications for the ways we evaluate whether present-bias is rationally permissible. (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.

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)

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)

Written by a diverse range of scholars, this accessible introductory volume asks: What is implicit bias? How does implicit bias compromise our knowledge of others and social reality? How does implicit bias affect us, as individuals and participants in larger social and political institutions, and what can we do to combat biases? An interdisciplinary enterprise, the volume brings together the philosophical perspective of the humanities with the perspective of the social sciences to develop rich lines of inquiry. (...) It is written in a non-technical style, using relatable examples that help readers understand what implicit bias is, its significance, and the controversies surrounding it. Each chapter includes discussion questions and additional reading suggestions. A companion webpage contains teaching resources. The volume will be an invaluable resource for students—and researchers—seeking to understand criticisms surrounding implicit bias, as well as how one might answer them by adopting a more nuanced understanding of bias and its role in maintaining social injustice. (shrink)

Moral, social, political, and other “nonepistemic” values can lead to bias in science, from prioritizing certain topics over others to the rationalization of questionable research practices. Such values might seem particularly common or powerful in the social sciences, given their subject matter. However, I argue first that the well-documented phenomenon of motivated reasoning provides a useful framework for understanding when values guide scientific inquiry (in pernicious or productive ways). Second, this analysis reveals a parity thesis: values influence the social (...) and natural sciences about equally, particularly because both are so prominently affected by desires for social credit and status, including recognition and career advancement. Ultimately, bias in natural and social science is both natural and social— that is, a part of human nature and considerably motivated by a concern for social status (and its maintenance). Whether the pervasive influence of values is inimical to the sciences is a separate question. (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)

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)

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)

As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are (...) hampered by conflations of various understandings of bias, ranging from neutral deviations from a standard to morally problematic instances of injustice due to prejudice, discrimination, and disparate treatment. This terminological confusion impedes efforts to address clear cases of discrimination. -/- In this paper, we examine the promises and challenges of different approaches to disambiguating bias and designing for justice. While both approaches aid in understanding and addressing clear algorithmic harms, we argue that they also risk being leveraged in ways that ultimately deflect accountability from those building and deploying these systems. Applying this analysis to recent examples of generative AI, our argument highlights unseen dangers in current methods of evaluating algorithmic bias and points to ways to redirect approaches to addressing bias in generative AI at its early stages in ways that can more robustly meet the demands of justice. (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)

Why does social injustice exist? What role, if any, do implicit biases play in the perpetuation of social inequalities? Individualistic approaches to these questions explain social injustice as the result of individuals’ preferences, beliefs, and choices. For example, they explain racial injustice as the result of individuals acting on racial stereotypes and prejudices. In contrast, structural approaches explain social injustice in terms of beyond-the-individual features, including laws, institutions, city layouts, and social norms. Often these two approaches are seen as competitors. (...) Framing them as competitors suggests that only one approach can win and that the loser offers worse explanations of injustice. In this essay, we explore each approach and compare them. Using implicit bias as an example, we argue that the relationship between individualistic and structural approaches is more complicated than it may first seem. Moreover, we contend that each approach has its place in analyses of injustice and raise the possibility that they can work together—synergistically—to produce deeper explanations of social injustice. If so, the approaches may be complementary, rather than competing. (shrink)

In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive nature and function of a third-party audit, and the uncertain and shifting regulatory landscape, we suggest that second-party assessments are currently the primary mechanisms for analyzing the social impacts of systems that incorporate artificial intelligence. We then discuss two kinds of as-sessments: (...) an ethical risk assessment and a narrower, technical algo-rithmic bias assessment. We explain how the two assessments depend on each other, highlight the importance of situating the algorithm within its particular socio-technical context, and discuss a number of lessons and challenges for algorithm assessments and, potentially, for algorithm audits. The discussion builds on our team’s experience of advising and conducting ethical risk assessments for clients across dif-ferent industries in the last four years. Our main goal is to reflect on the key factors that are potentially ethically relevant in the use of algo-rithms, and draw lessons for the nascent algorithm assessment and audit industry, in the hope of helping all parties minimize the risk of harm from their use. (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)

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)

Having a confirmation bias sometimes leads us to hold inaccurate beliefs. So, the puzzle goes: why do we have it? According to the influential argumentative theory of reasoning, confirmation bias emerges because the primary function of reason is not to form accurate beliefs, but to convince others that we’re right. A crucial prediction of the theory, then, is that confirmation bias should be found only in the reasoning domain. In this article, we argue that there is evidence (...) that confirmation bias does exist outside the reasoning domain. This undermines the main evidential basis for the argumentative theory of reasoning. In presenting the relevant evidence, we explore why having such confirmation bias may not be maladaptive. (shrink)

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)

The use of performance feedback in the workplace has gained popularity over the years, yet school heads have been challenged in providing it to teachers. In the initial interview, they shared that evaluation results can impact teachers’ motivation, and that feedback should be done carefully. However, they failed to clearly articulate a specific mechanism that had been applied in this vital role. Also, no studies have provided clear detail on the feedback mechanism used by school heads in (...) the past. For this reason, a study explored the feedback mechanisms employed by school heads in conveying the performance evaluation results to teachers. This study employed a narrative inquiry, and interviews were conducted with five school heads and five teachers who were chosen purposively for this research. Responses were recorded using a voice recorder. These responses were transcribed and analyzed using thematic narrative analysis. Based on transcripts, the study identified six emergent themes, such as conversational (one-on-one), relational, reflective, technical, reinforcing, and properly situated mechanisms in conveying performance evaluation results to teachers. Thus, a new feedback mechanism framework was developed. (shrink)

The possibilities of unconscious perception and unconscious bias prompt parallel debates about unconscious mental content. This chapter argues that claims within these debates alleging the existence of unconscious content are made fraught by ambiguity and confusion with respect to the two central concepts they involve: consciousness and content. Borrowing conceptual resources from the debate about unconscious perception, the chapter distills the two conceptual puzzles concerning each of these notions and establishes philosophical strategies for their resolution. It then argues that (...) empirical evidence for unconscious bias falls victim to these same puzzles, but that progress can be made by adopting similar philosophical strategies. Throughout, the chapter highlights paths forward in both debates, illustrates how they serve as fruitful domains in which to study the relationship between philosophy and empirical science, and uses their combined study to further understanding of a general theory of unconscious content. (shrink)

Endocrinologists apply the idea of feedback loops to explain how hormones regulate certain bodily functions such as glucose metabolism. In particular, feedback loops focus on the maintenance of the plasma concentrations of glucose within a narrow range. Here, we put forward a different, organicist perspective on the endocrine regulation of glycaemia, by relying on the pivotal concept of closure of constraints. From this perspective, biological systems are understood as organized ones, which means that they are constituted of a (...) set of mutually dependent functional structures acting as constraints, whose maintenance depends on their reciprocal interactions. Closure refers specifically to the mutual dependence among functional constraints in an organism. We show that, when compared to feedback loops, organizational closure can generate much richer descriptions of the processes and constraints at play in the metabolism and regulation of glycaemia, by making explicit the different hierarchical orders involved. We expect that the proposed theoretical framework will open the way to the construction of original mathematical models, which would provide a better understanding of endocrine regulation from an organicist perspective. (shrink)

For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations and that (...) many popular XAI designs implicitly and problematically assume that Western explanatory needs are shared cross-culturally. Additionally, we systematically reviewed over 200 XAI user studies and found that most studies did not consider relevant cultural variations, sampled only Western populations, but drew conclusions about human-XAI interactions more generally. We also analyzed over 30 literature reviews of XAI studies. Most reviews did not mention cultural differences in explanatory needs or flag overly broad cross-cultural extrapolations of XAI user study results. Combined, our analyses provide evidence of a cultural bias toward Western populations in XAI research, highlighting an important knowledge gap regarding how culturally diverse users may respond to widely used XAI systems that future work can and should address. (shrink)

This paper offers an unorthodox appraisal of empirical research bearing on the question of the low representation of women in philosophy. It contends that fashionable views in the profession concerning implicit bias and stereotype threat are weakly supported, that philosophers often fail to report the empirical work responsibly, and that the standards for evidence are set very low—so long as you take a certain viewpoint.

This chapter is centered around an apparent tension that research on implicit bias raises between virtue and social knowledge. Research suggests that simply knowing what the prevalent stereotypes are leads individuals to act in prejudiced ways—biasing decisions about whom to trust and whom to ignore, whom to promote and whom to imprison—even if they reflectively reject those stereotypes. Because efforts to combat discrimination obviously depend on knowledge of stereotypes, a question arises about what to do next. This chapter argues (...) that the obstacle to virtue is not knowledge of stereotypes as such, but the “accessibility” of such knowledge to the agent who has it. “Accessibility” refers to how easily knowledge comes to mind. Social agents can acquire the requisite knowledge of stereotypes while resisting their pernicious influence, so long as that knowledge remains, in relevant contexts, relatively inaccessible. (shrink)

In analyzing implicit bias, one key issue is to clarify its metaphysical nature. In this paper, I develop a novel account of implicit bias by highlighting a particular kind of belief-like state that is partly constituted by phenomenal experiences. I call these states ‘qualiefs’ for three reasons: qualiefs draw upon qualitative experiences of what an object seems like to attribute a property to this very object, they share some of the distinctive features of proper beliefs, and they also (...) share some characteristics of what Gendler calls ‘aliefs’. I proceed as follows: First, I develop a general theory of qualiefs. Second, I argue that implicit bias involves generic qualiefs that involve experiences that have been shaped by stereotypes. Elaborating on the particular content of a generic qualief, I explain why we are unaware of the bias even though it involves an experience. Third, I demonstrate that the qualief-model best explains the key features of implicit bias: it accounts for the biases´ implicitness and automaticity. Moreover, it elucidates how implicit bias can be insensitive to logical form and evidence, but at the same time it can serve as propositional input to further mental states. (shrink)

Suppose you think that whether you believe some proposition A at some future time t might have a causal influence on whether A is true. For instance, maybe you think a woman can read your mind, and either (1) you think she will snap her fingers shortly after t if and only if you believe at t that she will, or (2) you think she will snap her fingers shortly after t if and only if you don't believe at t (...) that she will. Let A be the proposition that she snaps her fingers shortly after t. In case (1), theoretical rationality seems to leave it open whether you should believe A or not. Perhaps, for all it has to say, you could just directly choose whether to believe A. David Velleman seems to be committed to something close to that, but his view has been unpopular. In case (2), you seem to be in a theoretical dilemma, a situation where any attitude you adopt toward A will be self-undermining in a way that makes you irrational. Such theoretical dilemmas ought to be impossible, just as genuine moral dilemmas ought to be impossible, but it is surprisingly hard to show that they are (perhaps because they aren't). I study cases analogous to (1) and (2) in a probabilistic framework where degrees of belief rather than all-or-nothing beliefs are taken as basic. My principal conclusions are that Velleman's view is closer to the truth than it is generally thought to be, that case (2) type theoretical dilemmas only arise for hyperidealised agents unlike ourselves, and that there are related cases that can arise for agents like us that are very disturbing but might not quite amount to theoretical dilemmas. (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)

(This contribution is primarily based on "Implicit Bias, Moods, and Moral Responsibility," (2018) Pacific Philosophical Quarterly. This version has been shortened and significantly revised to be more accessible and student-oriented.) Are individuals morally responsible for their implicit biases? One reason to think not is that implicit biases are often advertised as unconscious. 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)

What is the status of research on implicit bias? In light of meta‐analyses revealing ostensibly low average correlations between implicit measures and behavior, as well as various other psychometric concerns, criticism has become ubiquitous. We argue that while there are significant challenges and ample room for improvement, research on the causes, psychological properties, and behavioral effects of implicit bias continues to deserve a role in the sciences of the mind as well as in efforts to understand, and ultimately (...) combat, discrimination and inequality. (shrink)

Marginal comments on student essays are a near-universal method of providing feedback in philosophy. Widespread as the practice is, however, it has well-known drawbacks. Commenting on students' work in the form of a video has the potential to improve the feedback experience for both instructors and students. The advantages of video feedback can be seen by examining it from both the professor's and the student's perspective. In discussing the professor's perspective, this article shares observations based on the (...) author's experience delivering feedback through video. Turning to the student's view, it discusses qualitative feedback solicited from students that indicates a clear preference for video feedback over written marginalia. In particular, students describe video feedback as more informative, more personal, better at suggesting improvements on future assignments, enhancing the professor's ability to communicate through tone of voice and gesture, and easier to understand compared to written feedback. (shrink)

It has widely been assumed, by philosophers, that our first-person preferences regarding pleasurable and painful experiences exhibit a bias toward the future (positive and negative hedonic future-bias), and that our preferences regarding non-hedonic events (both positive and negative) exhibit no such bias (non-hedonic time-neutrality). Further, it has been assumed that our third-person preferences are always time-neutral. Some have attempted to use these (presumed) differential patterns of future-bias—different across kinds of events and perspectives—to argue for the irrationality (...) of hedonic future-bias. This paper experimentally tests these descriptive hypotheses. While as predicted we found first-person hedonic future-bias, we did not find that participants were time-neutral in all other conditions. Hence, the presumed asymmetry of hedonic/non-hedonic and first/third-person preferences cannot be used to argue for the irrationality of future-bias, since no such asymmetries exist. Instead, we develop a more fine-grained approach, according to which three factors—positive/negative valence, first/third-person, and hedonic/non-hedonic—each independently influence, but do not determine, whether an event is treated in a future-biased or time-neutral way. We discuss the upshots of these results for the debate over the rationality of future-bias. (shrink)

The underrepresentation of women, people of color, and especially women of color—and the corresponding overrepresentation of white men—is more pronounced in philosophy than in many of the sciences. I suggest that part of the explanation for this lies in the role played by the idealized rational self, a concept that is relatively influential in philosophy but rarely employed in the sciences. The idealized rational self models the mind as consistent, unified, rationally transcendent, and introspectively transparent. I hypothesize that acceptance of (...) the idealized rational self leads philosophers to underestimate the influence of implicit bias on their own judgments and prevents them from enacting the reforms necessary to minimize the effects of implicit bias on institutional decision-making procedures. I consider recent experiments in social psychology that suggest that an increased sense of one’s own objectivity leads to greater reliance on bias in hiring scenarios, and I hypothesize how these results might be applied to philosophers’ evaluative judgments. I discuss ways that the idealized rational self is susceptible to broader critiques of ideal theory, and I consider some of the ways that the picture functions as a tool of active ignorance and color-evasive racism. (shrink)

Recent empirical research has substantiated the finding that very many of us harbour implicit biases: fast, automatic, and difficult to control processes that encode stereotypes and evaluative content, and influence how we think and behave. Since it is difficult to be aware of these processes - they have sometimes been referred to as operating 'unconsciously' - we may not know that we harbour them, nor be alert to their influence on our cognition and action. And since they are difficult to (...) control, considerable work is required to prevent their influence. We here focus on the implications of these findings for epistemology. We first look at ways in which implicit biases thwart our knowledge seeking practices (sections 1 & 2). Then we set out putative epistemic benefits of implicit bias, before considering ways in which epistemic practices might be improved (section 3). Finally, we consider the distinctive challenges that the findings about implicit bias pose to us as philosophers, in the context of feminist philosophy in particular (section 4). (shrink)

Nearly everyone prefers pain to be in the past rather than the future. This seems like a rationally permissible preference. But I argue that appearances are misleading, and that future-biased preferences are in fact irrational. My argument appeals to trade-offs between hedonic experiences and other goods. I argue that we are rationally required to adopt an exchange rate between a hedonic experience and another type of good that stays fixed, regardless of whether the hedonic experience is in the past or (...) future. (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)

In recent years, a disagreement has erupted between two camps of philosophers about the rationality of bias toward the near and bias toward the future. According to the traditional hybrid view, near bias is rationally impermissible, while future bias is either rationally permissible or obligatory. Time neutralists, meanwhile, argue that the hybrid view is untenable. They claim that those who reject near bias should reject both biases and embrace time neutrality. To date, experimental work has (...) focused on future-directed near bias. The primary aim of this paper is to shed light on the debate by investigating past-directed near bias. If people treat the past and future differently with respect to near bias, by being future-directed but not past-directed near biased, then this supports a particular version of the hybrid view: temporal metaphysic hybridism. If people treat the past and future the same with respect to near bias, then this supports a simple version of time neutralism, which explains both future bias and near bias in terms of the functioning of a single mechanism: the anticipatory/retrospectory mechanism. Our results undermine the claim that people are future-directed, but not past-directed, near biased, and hence do not support temporal metaphysic hybridism. They also fail to support simple time-neutralism; instead, they suggest that there are multiple mechanisms that differently shape future- and past-directed preferences. (shrink)

The Western Philippines University – College of Education’s Project MATHEMATICS (Mathematics Enhanced Mentoring, Assistance, and Training to In-need and Challenged Students) was implemented as part of the Adopt-a-School Program to address the mathematical needs of Laura Vicuña Center – Palawan youths. To evaluate the extent of the project implementation, the study assessed its impact through the feedback gathered from the clients served. It specifically described the quality of project implementation, determined the attainment of project objectives, and enumerated client (...) class='Hi'>feedback. A concurrent triangulation mixed-method research design was used with 32 clientele samples selected purposively. The study utilized a survey, problem set test, and focus-grouped interview to obtain data pertinent to the study’s objectives. The findings revealed an aspirational quality of the implemented project, improved mathematical performance, and the client’s desire for ongoing mentoring. The implications and limitations of the study are discussed, along with recommendations for future extension projects, monitoring and evaluation, and re-planning activities. (shrink)

Addressing biases in natural-language processing (NLP) systems presents an underappreciated ethical dilemma, which we think underlies recent debates about bias in NLP models. In brief, even if we could eliminate bias from language models or their outputs, we would thereby often withhold descriptively or ethically useful information, despite avoiding perpetuating or amplifying bias. Yet if we do not debias, we can perpetuate or amplify bias, even if we retain relevant descriptively or ethically useful information. Understanding this (...) dilemma provides for a useful way of rethinking the ethics of algorithmic bias in NLP. (shrink)

Future-bias is preferring some lesser future good to a greater past good because it is in the future, or preferring some greater past pain to some lesser future pain because it is in the past. Most of us think that this bias is rational. I argue that no agents have future-biased preferences that are rationally evaluable—that is, evaluable as rational or irrational. Given certain plausible assumptions about rational evaluability, either we must find a new conception of future-bias (...) that avoids the difficulties I raise, or we must conclude that future-biased preferences are not subject to rational evaluation. (shrink)

The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under (...) certain conditions. (shrink)