This paper explores the complex nature of social biases, arguing for a functional framework that recognizes their unity and diversity. The functional approach posits that all biases share a common functional role in overcoming underdetermination. This framework, I argue, provides a comprehensive understanding of how all psychological biases, including social biases, are unified. I then turn to the question of disunity, demonstrating how psychological social biases differ systematically in the mental states and processes that constitute them. These (...) differences indicate that biases at various levels of the cognitive architecture require distinct treatment along at least two dimensions: epistemic evaluation and mitigation strategies. By examining social biases through this dual lens of unity and diversity, we can more effectively identify when and how to intervene on problematic biases. Ultimately, this approach provides a nuanced understanding of the nature of social bias, offering practical guidance for addressing existing biases and proactively managing emerging biases in both human and artificial minds. (shrink)

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)

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)

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

Social psychologists often describe “implicit” racial biases as entirely unconscious, and as mere associations between groups and traits, which lack intentional content, e.g., we associate “black” and “athletic” in much the same way we associate “salt” and “pepper.” However, recent empirical evidence consistently suggests that individuals are aware of their implicit biases, albeit in partial, inarticulate, or even distorted ways. Moreover, evidence suggests that implicit biases are not “dumb” semantic associations, but instead reflect our skillful, norm-sensitive, and embodied engagement (...) with social reality. This essay draws on phenomenological and hermeneutic methods and concepts to better understand what social-psychological research has begun to reveal about the conscious access individuals have to their own racial attitudes, as well as the intentional contents of the attitudes themselves. -/- First, I argue that implicit racial biases form part of the “background” of social experience. That is, while they exert a pervasive influence on our perceptions, judgments, and actions, they are frequently felt but not noticed, or noticed but misinterpreted. Second, I argue that our unreflective racial attitudes are neither mere associations nor fully articulated, propositionally structured beliefs or emotions. Their intentional contents are fundamentally indeterminate. For example, when a white person experiences a “gut feeling” of discomfort during an interaction with a black person, there is a question about the meaning or nature of that discomfort. Is it a fear of black people? Is it anxiety about appearing racist? There is, I argue, no general, determinate answer to such questions. The contents of our unreflective racial attitudes are fundamentally vague and open-ended, although I explain how they nevertheless take on particular shapes and implications—that is, their content can become determinate—depending on context, social meaning, and structural power relations. (If, for example, a perceived authority figure, such as a politician, parent, or scientist, encourages you to believe that your uncomfortable gut feeling is a justified fear of other social groups, then that is what your gut feeling is likely to become.). (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)

Two studies examined the allegiance bias – the rendering of biased predictions by individuals who are psychologically invested in a desired outcome. In Study 1, fans of either Notre Dame or University of Miami college football read information about an upcoming game between the two teams and then explained a hypothetical victory either by Notre Dame or Miami. Although explaining a hypothetical victory biased the judgments of controls (i.e., fans of neither team) in the direction of the team explained, (...) the judgments of Notre Dame and Miami fans favored their team in every explanation condition. In addition, fans exhibited biased recall for facts favoring their own teams and this biased recall predicted fans’ judgments regarding the upcoming game. Study 2 attempted to specify a debiasing technique that might attenuate the allegiance bias. Indiana University basketball fans described what they thought might happen in an upcoming game between Indiana and the University of Michigan while anticipating having a discussion about the game (i.e., predecisional accountability) with either an Indiana fan, a Michigan fan, or a fan of unknown allegiance. As predicted, anticipating a discussion with a fan of unknown allegiance engendered game predictions that were the least biased in favor of an Indiana victory. Implications for social explanation and prediction research are discussed. (shrink)

We argue that work on norms provides a way to move beyond debates between proponents of individualist and structuralist approaches to bias, oppression, and injustice. We briefly map out the geography of that debate before presenting Charlotte Witt’s view, showing how her position, and the normative ascriptivism at its heart, seamlessly connects individuals to the social reality they inhabit. We then describe recent empirical work on the psychology of norms and locate the notions of informal institutions and soft (...) structures with respect to it. Finally, we argue that the empirical resources enrich Witt’s ascriptivism, and that the resulting picture shows theorists need not, indeed should not, choose between either the individualist or structuralist camp. (shrink)

Philosophical literature has focused on the concept of trust, but often considers distrust merely as an afterthought. Distrust however, because of its pervasive role in our everyday lives, can be quite damaging. Thus, understanding the rationality of distrust is crucial for understanding our testimonial practices. In this paper I analyze whether it is rational or irrational to distrust an informant on the basis of identity bias. My aim is to show that distrust is irrational when based on negative identity (...) bias. First, I adopt Annalisa Coliva’s account of social hinge epistemology where it is rationally required to assume certain basic presuppositions, such that people are generally reliable informants, to obtain propositional justification and participate in the testimonial practice. Secondly, I show how distrust based on negative identity bias can spread across other domains of interaction and jeopardize the testimonial practice as we fail to assume that people are generally reliable informants. Thirdly, I argue that considering bias as a defeater is beneficial to maintain the claim that bias-based distrust is irrational, as it prevents the acquisition of propositional justification. Finally, I show that distrust is rational when based on evidence and reason that the speaker is not reliable or sincere. (shrink)

Background: Facial attractiveness influences our perceptions of others, with beautiful faces reaping societal rewards and anomalous faces encountering penalties. The purpose of this study was to determine associations of visual attention with bias and social dispositions toward people with facial anomalies. -/- Methods: Sixty subjects completed tests evaluating implicit bias, explicit bias, and social dispositions before viewing publicly available images of preoperative and postoperative patients with hemifacial microsomia. Eye-tracking was used to register visual fixations. -/- (...) Results: Participants with higher implicit bias scores fixated significantly less on the cheek and ear region preoperatively (P = 0.004). Participants with higher scores in empathic concern and perspective taking fixated more on the forehead and orbit preoperatively (P = 0.045) and nose and lips (P = 0.027) preoperativel. -/- Conclusions: Participants with higher levels of implicit bias spent less visual attention on anomalous facial anatomy, whereas participants with higher levels of empathic concern and perspective taking spent more visual attention on normal facial anatomy. Levels of bias and social dispositions such as empathy may predict layperson gaze patterns toward those with facial anomalies and provide insights to neural mechanisms underlying the "anomalous is bad" paradigm. (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)

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)

How are biases encoded in our representations of social categories? Philosophical and empirical discussions of implicit bias overwhelmingly focus on salient or statistical associations between target features and representations of social categories. These are the sorts of associations probed by the Implicit Association Test and various priming tasks. In this paper, we argue that these discussions systematically overlook an alternative way in which biases are encoded, that is, in the dependency networks that are part of our representations (...) of social categories. Dependency networks encode information about how features in a conceptual representation depend on each other. This information determines the degree of centrality of a feature for a conceptual representation. Importantly, centrally encoded biases systematically disassociate from those encoded in salient-statistical associations. Furthermore, the degree of centrality of a feature determines its cross-contextual stability: in general, the more central a feature is for a concept, the more likely it is to survive into a wide array of cognitive tasks involving that concept. Accordingly, implicit biases that are encoded in the central features of concepts are predicted to be more resilient across different tasks and contexts. As a result, the distinction between centrally encoded and salient-statistical biases has important theoretical and practical implications. (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)

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)

chapter on perception and bias including implicit bias.

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)

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)

Modeling social interactions based on individual behavior has always been an area of interest, but prior literature generally presumes rational behavior. Thus, such models may miss out on capturing the effects of biases humans are susceptible to. This work presents a method to model egocentric bias, the real-life tendency to emphasize one's own opinion heavily when presented with multiple opinions. We use a symmetric distribution, centered at an agent's own opinion, as opposed to the Bounded Confidence (BC) model (...) used in prior work. We consider a game of iterated interactions where an agent cooperates based on its opinion about an opponent. Our model also includes the concept of domain-based self-doubt, which varies as the interaction succeeds or not. An increase in doubt makes an agent reduce its egocentricity in subsequent interactions, thus enabling the agent to learn reactively. The agent system is modeled with factions not having a single leader, to overcome some of the issues associated with leader-follower factions. We find that agents belonging to factions perform better than individual agents. We observe that an intermediate level of egocentricity helps the agent perform at its best, which concurs with conventional wisdom that neither overconfidence nor low self-esteem brings benefits. (shrink)

Discussions in social psychology overlook an important way in which biases can be encoded in conceptual representations. Most accounts of implicit bias focus on ‘mere associations’ between features and representations of social groups. While some have argued that some implicit biases must have a richer conceptual structure, they have said little about what this richer structure might be. To address this lacuna, we build on research in philosophy and cognitive science demonstrating that concepts represent dependency relations between (...) features. These relations, in turn, determine the centrality of a feature f for a concept C: roughly, the more features of C depend on f, the more central f is for C. In this paper, we argue that the dependency networks that link features can encode significant biases. To support this claim, we present a series of studies that show how a particular brilliance-gender bias is encoded in the dependency networks which are part of the concepts of female and male academics. We also argue that biases which are encoded in dependency networks have unique implications for social cognition. (shrink)

Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias (...) can be handled more or less independently by technical experts who specialize in XAI methods. Drawing on resources from feminist epistemology, we show why technical XAI is mistaken. Specifically, we demonstrate that the proper detection of algorithmic bias requires relevant interpretive resources, which can only be made available, in practice, by actively involving a diverse group of stakeholders. Finally, we suggest how feminist theories can help shape integrated XAI: an inclusive social-epistemic process that facilitates the amelioration of algorithmic bias. (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)

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)

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)

Confirmation bias is one of the most widely discussed epistemically problematic cognitions, challenging reliable belief formation and the correction of inaccurate views. Given its problematic nature, it remains unclear why the bias evolved and is still with us today. To offer an explanation, several philosophers and scientists have argued that the bias is in fact adaptive. I critically discuss three recent proposals of this kind before developing a novel alternative, what I call the ‘reality-matching account’. According to (...) the account, confirmation bias evolved because it helps us influence people and social structures so that they come to match our beliefs about them. This can result in significant developmental and epistemic benefits for us and other people, ensuring that over time we don’t become epistemically disconnected from social reality but can navigate it more easily. While that might not be the only evolved function of confirmation bias, it is an important one that has so far been neglected in the theorizing on the bias. (shrink)

Peer reviewers at many funding agencies and scientific journals are asked to score submissions both on individual criteria and overall. The overall scores should be some kind of aggregate of the criteria scores. Carole Lee identifies this as a potential locus for bias to enter the peer review process, which she calls commensuration bias. Here I view the aggregation of scores through the lens of social choice theory. I argue that, when reviewing grant proposals, it is in (...) many cases impossible to avoid commensuration bias. (shrink)

I argue that evidentialism should be rejected because it cannot be reconciled with empirical work on bias in cognitive and social psychology.

Thomas Kelly's book 'Bias: A philosophical study', is a philosophical exploration of the phenomena of bias and our practice of attributing it. He delves into the multifaceted nature of bias and offers a norm theoretic account for conceptualizing the phenomenon as typically involving "systematic departures from the norms". As a topic of inquiry, bias has attracted comparatively less attention in philosophy than in other disciplines like psychology and statistics. Hence, this book is an interesting and relevant (...) read. Scholars working in the areas of ethics, epistemology and social epistemology can greatly benefit from it. Practitioners of AI can also gain valuable insights from the study of bias. -/- In my review of the book, I provide a critical summary of Kelly's main arguments while acknowledging its fruitfulness in understanding bias. (shrink)

Does algorithmic political bias contribute to an entrenchment and polarization of political positions? Franke argues that it may do so because the bias involves classifications of people as liberals, conservatives, etc., and individuals often conform to the ways in which they are classified. I provide a novel example of this phenomenon in human–computer interactions and introduce a social psychological mechanism that has been overlooked in this context but should be experimentally explored. Furthermore, while Franke proposes that algorithmic (...) political classifications entrench political identities, I contend that they may often produce the opposite result. They can lead people to change in ways that disconfirm the classifications. Consequently and counterintuitively, algorithmic political bias can in fact decrease political entrenchment and polarization. (shrink)

Traditionally, social entities (i.e., social properties, facts, kinds, groups, institutions, and structures) have not fallen within the purview of mainstream metaphysics. In this chapter, we consider whether the exclusion of social entities from mainstream metaphysics is philosophically warranted or if it instead rests on historical accident or bias. We examine three ways one might attempt to justify excluding social metaphysics from the domain of metaphysical inquiry and argue that each fails. Thus, we conclude that (...) class='Hi'>social entities are not justifiably excluded from metaphysical inquiry. Finally, we ask how focusing on social entities could change the character of metaphysical inquiry. We suggest that starting from examples of social entities might lead metaphysicians to rethink the assumption that describing reality in terms of intrinsic, independent, and individualistic features is preferable to describing it in terms of relational, dependent, and non-individualistic features. (shrink)

Philosophers who have written about implicit bias have claimed or implied that individuals are not responsible, and therefore not blameworthy, for their implicit biases, and that this is a function of the nature of implicit bias as implicit: below the radar of conscious reflection, out of the control of the deliberating agent, and not rationally revisable in the way many of our reflective beliefs are. I argue that close attention to the findings of empirical psychology, and to the (...) conditions for blameworthiness, does not support these claims. I suggest that the arguments for the claim that individuals are not liable for blame are invalid, and that there is some reason to suppose that individuals are, at least sometimes, liable to blame for the extent to which they are influenced in behaviour and judgment by implicit biases. I also argue against the claim that it is counter-productive to see bias as something for which individuals are blameworthy; rather, understanding implicit bias as something for which we are liable to blame could be constructive. (shrink)

The reasonable person standard is used in adjudicating claims of self-defence. In US law, an individual may use defensive force if her beliefs that a threat is imminent and that force is required are beliefs that a reasonable person would have. In English law, it is sufficient that beliefs in imminence and necessity are genuinely held; but the reasonableness of so believing is given an evidential role in establishing the genuineness of the beliefs. There is, of course, much contention over (...) how to spell out when, and in virtue of what, such beliefs are reasonable. In this chapter, we identify some distinctive issues that arise when we consider that implicit racial bias might be implicated in the beliefs in imminence and necessity. Considering two prominent interpretations of the reasonable person standard, we argue that neither is acceptable. On one interpretation, we risk unfairness to the defendant-who may non-culpably harbour bias. On another, the standard embeds racist stereotypes. Whilst there are formulations of the defence that may serve to mitigate these problems, we argue that they cannot be avoided in the presence of racist social structures. (shrink)

O fenômeno de aceleração social, intimamente ligado a nossa modernização tecnológica e os sistemas políticos e sociais que adotamos, vem sendo alvo de questionamentos por parte da teoria crítica por diversos filósofos e sociólogos, principalmente em relação a se tal "aceleração" seja algo que, possa ser justificável pelo bem comum da sociedade. De fato, as rápidas mudanças que ocorreram no último século causaram uma tremenda mudança em nossos estilos-de-vida, e na maneira como experienciamos o mundo. Que a nossa sociedade (...) mudou e continua a mudar é um fato evidente quando olhamos criticamente para o passado e presente, e comparamos diferentes épocas da história humana. Neste ensaio tentaremos explorar algumas possíveis hipóteses que fundamentem o comportamento aceleracionista em certos fatores e mecanismo biológicos que caracterizam os sistemas de motivação e saciação humanos. Também tentaremos mostrar como certos fenômenos sociais podem auxiliar em fortalecer este tipo de comportamento, e suas possíveis origens evolutivas. Este estudo tem como objetivo principal fundamentar a Tese Aceleracionista em evidências neurofisiológicas, cognitivo-comportamentais, evolutivas e sociais. Palavras-chave: aceleração; recompensa; saciação; ciências cognitivas; teoria dos gêneros. (shrink)

Some artificial intelligence systems can display algorithmic bias, i.e. they may produce outputs that unfairly discriminate against people based on their social identity. Much research on this topic focuses on algorithmic bias that disadvantages people based on their gender or racial identity. The related ethical problems are significant and well known. Algorithmic bias against other aspects of people’s social identity, for instance, their political orientation, remains largely unexplored. This paper argues that algorithmic bias against (...) people’s political orientation can arise in some of the same ways in which algorithmic gender and racial biases emerge. However, it differs importantly from them because there are strong social norms against gender and racial biases. This does not hold to the same extent for political biases. Political biases can thus more powerfully influence people, which increases the chances that these biases become embedded in algorithms and makes algorithmic political biases harder to detect and eradicate than gender and racial biases even though they all can produce similar harm. Since some algorithms can now also easily identify people’s political orientations against their will, these problems are exacerbated. Algorithmic political bias thus raises substantial and distinctive risks that the AI community should be aware of and examine. (shrink)

We argue that the core social being system is unlike other core systems in that it participates in frequent, widespread learning. As a result, the social being system is less constant throughout the lifespan and less informationally encapsulated than other core systems. This learning supports the development of the precursors of bias, but also provides avenues for preempting it.

Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case (...) from medical epistemology, recently discussed in a paper by Bennett Holman. I will argue that evidential accounts cannot adequately capture cases of sponsorship bias that involve the manufacturing of certainty because of their neutrality with respect to the role of non-epistemic values in scientific practice. If my argument holds, it further highlights the importance of integrating social and ethical concerns into epistemological analysis, especially in applied contexts. One can only properly grasp sponsorship bias as an epistemological problem if one resists the methodological tendency to analyze social, ethical, and epistemological issues in isolation from each other. (shrink)

Psychologists and philosophers have not yet resolved what they take implicit attitudes to be; and, some, concerned about limitations in the psychometric evidence, have even challenged the predictive and theoretical value of positing implicit attitudes in explanations for social behavior. In the midst of this debate, prominent stakeholders in science have called for scientific communities to recognize and countenance implicit bias in STEM fields. In this paper, I stake out a stakeholder conception of implicit bias that responds (...) to these challenges in ways that are responsive to the psychometric evidence, while also being resilient to the sorts of disagreements and scientific progress that would not undermine the soundness of this call. Along the way, my account advocates for attributing collective (group-level) implicit attitudes rather than individual-level implicit attitudes. This position raises new puzzles for future research on the relationship (metaphysical, epistemic, and ethical) between collective implicit attitudes and individual-level attitudes. (shrink)

How feasible are conceptual engineering projects of social concepts that aim for the engineered concept to be widely adopted in ordinary everyday life? Predominant frameworks on the psychology of concepts that shape work on stereotyping, bias, and machine learning have grim implications for the prospects of conceptual engineers: conceptual engineering efforts are ineffective in promoting certain social-conceptual changes. Specifically, since conceptual components that give rise to problematic social stereotypes are sensitive to statistical structures of the environment, (...) purely conceptual change won’t be possible without corresponding world change. This tradition, however, tends to ignore that concepts don’t only encode statistical, but also causal information. Paying attention to this feature of concepts, I argue, shows that conceptual engineering is not only possible. There is an imperative to conceptually-engineer. (shrink)

It has recently been suggested that politically motivated cognition leads progressive individuals to form beliefs that underestimate real differences between social groups and to process information selectively to support these beliefs and an egalitarian outlook. I contend that this tendency, which I shall call ‘egalitarian confirmation bias’, is often ‘Mandevillian’ in nature. That is, while it is epistemically problematic in one’s own cognition, it often has effects that significantly improve other people’s truth tracking, especially that of stigmatized individuals (...) in academia. Due to its Mandevillian character, egalitarian confirmation bias isn’t only epistemically but also ethically beneficial, as it helps decrease social injustice. Moreover, since egalitarian confirmation bias has Mandevillian effects especially in academia, and since progressives are particularly likely to display the bias, there is an epistemic reason for maintaining the often-noted political majority of progressives in academia. That is, while many researchers hold that diversity in academia is epistemically beneficial because it helps reduce bias, I argue that precisely because political diversity would help reduce egalitarian confirmation bias, it would in fact in one important sense be epistemically costly. (shrink)

The my-side bias is a well-documented cognitive bias in the evaluation of arguments, in which reasoners in a discussion tend to overvalue arguments that confirm their prior beliefs, while undervaluing arguments that attack their prior beliefs. The first part of this paper develops and justifies a Bayesian model of myside bias at the level of individual reasoning. In the second part, this Bayesian model is implemented in an agent-based model of group discussion among myside-biased agents. The agent-based (...) model is then used to perform a number of experiments with the objective to study whether the myside bias hinders or enhances the ability of groups to collectively track the truth, that is, to reach the correct answer to a given binary issue. An analysis of the results suggests the following: First, whether the truth-tracking ability of groups is helped or hindered by myside bias crucially depends on how the strength of myside bias is differentially distributed across subgroups of discussants holding different beliefs. Second, small groups are more likely to track the truth than larger groups, suggesting that increasing group size has a detrimental effect on collective truth-tracking through discussion. (shrink)

The social sciences face a problem of sample non-representation, where the majority of samples consist of undergraduate students from Euro-American institutions. The problem has been identified for decades with little trend of improvement. In this paper, I trace the history of sampling theory. The dominant framework, called the design-based approach, takes random sampling as the gold standard. The idea is that a sampling procedure that is maximally uninformative prevents samplers from introducing arbitrary bias, thus preserving sample representation. I (...) show how this framework, while good in theory, faces many challenges in application. Instead, I advocate for an alternative framework, called the model-based approach to sampling, where representative samples are those balanced in composition, however they were drawn. I argue that the model-based framework is more appropriate in the social sciences because it allows for systematic assessment of imperfect samples and methodical improvement in resource-limited scientific contexts. I end with practical proposals of improving sample quality in the social sciences. (shrink)

Recent work in social psychology suggests that people harbor “implicit race biases,” biases which can be unconscious or uncontrollable. Because awareness and control have traditionally been deemed necessary for the ascription of moral responsibility, implicit biases present a unique challenge: do we pardon discrimination based on implicit biases because of its unintentional nature, or do we punish discrimination regardless of how it comes about? The present experiments investigated the impact such theories have upon moral judgments about racial discrimination. The (...) results show that different theories differ in their impact on moral judgments: when implicit biases are defined as unconscious, people hold the biased agent less morally responsible than when these biases are defined as automatic (i.e., difficult to control), or when no theory of implicit bias is provided. (shrink)

It has recently been argued that to tackle social injustice, implicit biases and unjust social structures should be targeted equally because they sustain and ontologically overlap with each other. Here I develop this thought further by relating it to the hypothesis of extended cognition. I argue that if we accept common conditions for extended cognition then people’s implicit biases are often partly realized by and so extended into unjust social structures. This supports the view that we should (...) counteract psychological and social contributors to injustice equally. But it also has a significant downside. If unjust social structures are part of people’s minds then dismantling these structures becomes more difficult than it currently is, as this will then require us to overcome widely accepted ethical and legal barriers protecting people’s bodily and personal integrity. Thus, while there are good grounds to believe that people’s biases and unjust social structures ontologically overlap, there are also strong ethical reasons to reject this view. Metaphysical and ethical intuitions about implicit bias hence collide in an important way. (shrink)

I argue that introspection recruits the same mental mechanism as that which is required for the production of ordinary speech acts. In introspection, in effect, we intentionally tell ourselves that we are in some mental state, aiming thereby to produce belief about that state in ourselves. On one popular view of speech acts, however, this is precisely what speakers do when speaking to others. On this basis, I argue that every bias discovered by social epistemology applies to introspection (...) and other forms of self-directed representation. If so, it becomes unclear in what sense social epistemology is social. (shrink)

How, if at all, do the findings of social psychology impact upon philosophical analyses of discrimination? In this chapter, I outline key findings from three research programs from psychology – concerning in-group/out-group favoritism; implicit bias; and stereotype threat. I argue that each set of findings presents challenges to how philosophical analyses of group discrimination are formulated, and propose possible revisions to be explored in future work.

With twentieth- and twenty-first-century philosophy of science’s unfolding acceptance of the nature of scientific inquiry being value-laden, the persistent worry has been that there are no means for legitimate negotiation of the social or non-epistemic values that enter into science. The rejection of the value-free ideal in science has thereby been coupled with the spectres of indiscriminate relativism and bias in scientific inquiry. I challenge this view in the context of recently expressed concerns regarding Canada's death of evidence (...) controversy. The worry, raised by Stathis Psillos, is that as constructivist accounts of science demoted the previously secure status of evidence for drawing justified conclusions in science, we were left with no rational delineation between the right and wrong values for science. The implication for the death of evidence controversy is that we may have no rational grounds for claiming that the Canadian Government is wrong to interfere with scientific enterprise. But he does offer another avenue for reaching the conclusion that the wrong social values are directing the current stifling of some sectors of Canadian science. Psillos draws from standpoint epistemologies to devise a salient defence of ‘valuing evidence’ as a universalizable social value. That is, government bodies ought to enable scientific research via adequate funding as well as political non-interference. In this paper, I counter that non-epistemic values can be rationally evaluated and that standpoint epistemology’s universalizable standpoint provides an inadequate framework for negotiating social values in science. Regarding, I draw from the evidence-based medicine debate in philosophy of medicine and from feminist empiricist investigations into the science–values relationship in order to make the argument for empirically driven value arbitration. If social values can be rationally chosen in the context of justification, then we can have grounds for charging the Canadian leadership with being ‘at war with science’. I further argue that my recommended empiricist methodology is preferable to Psillos’s search for universalizable perspectives for negotiating social values in science because the latter method permits little more than the trivial conclusion that evidence is valuable to science. (shrink)

One of the predominant debates in AI Ethics is the worry and necessity to create fair, transparent and accountable algorithms that do not perpetuate current social inequities. I offer a critical analysis of Reuben Binns’s argument in which he suggests using public reason to address the potential bias of the outcomes of machine learning algorithms. In contrast to him, I argue that ultimately what is needed is not public reason per se, but an audit of the implicit moral (...) assumptions of societies within which algorithms are built and applied. Public justification is appealing since it offers us the possibility to align the decision-making outcomes of the algorithm with the core moral values of stakeholders within a constitutional democratic society. My concern is that the common moral principles that form the foundation of public reason are not necessarily neutral, as they still express specific moral ideals and normative standards even if there is moral agreement by society as a whole, or among different stakeholders within society. Appealing to such normative standards may thus still lead to algorithmic outcomes being biased as common moral values may very well still be discriminatory even though they are formed from a consensus, and even if public reason is applied as a kind of filter for potential algorithmic outcomes. Hence, I argue that these implicit moral norms within society that we take as a given in public reasoning, need to be audited from generation to generation in order to effectively mitigate potential algorithmic bias. (shrink)

A topic of special importance when it comes to responsibility and implicit bias is responsibility for knowledge. Are there strategies for becoming more responsible and respectful knowers? How might we work together, not just as individuals but members of collectives, to reduce the negative effects of bias on what we see and believe, as well as the wrongs associated with epistemic injustice? To explore these questions, Chapter 9 introduces the concept of epistemic responsibility, a set of practices developed (...) through the cultivation of basic epistemic virtues, such as open-mindedness, epistemic humility, and diligence that help knowers seek information about themselves, others, and the world. (shrink)

The issue of common method variance and bias in Indonesia still has not gained much attention; even the terminology is less popular, except among psychometric enthusiasts and experts. In fact, the potential for common method variance and bias infiltrating in research results is very high, especially in studies that use a single method, a single source, and concurrent design, which are highly favored by psychological lecturers and researchers in Indonesia. This paper is a critical review, exposing the debate (...) and serious impact regarding common method variance and bias, as well as procedures for detecting, addressing and correcting its effects. The author hoped this paper contributes in filling the gap in the literature, especially in Psychology Research Methodology text books in the Indonesian language, so that psychological researches in Indonesia continue to increase their quality and to have their better place in international publications. (shrink)