Collective deliberation is fuelled by disagreements and its epistemic value depends, inter alia, on how the participants respond to each other in disagreements. I use this accountability thesis to argue that deliberation may be valued not just instrumentally but also for its procedural features. The instrumental epistemic value of deliberation depends on whether it leads to more or less accurate beliefs among the participants. The procedural epistemic value of deliberation hinges on the relationships of mutual accountability that characterize appropriately conducted (...) deliberation. I will argue that it only comes into view from the second-person standpoint. I shall explain what the second-person standpoint in the epistemic context entails and how it compares to Stephen Darwall’s interpretation of the second-person standpoint in ethics. (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)

The received view of implicit bias holds that it is associative and unreflective. Recently, the received view has been challenged. Some argue that implicit bias is not predicated on “any” associative process, but it is unreflective. These arguments rely, in part, on debiasing experiments. They proceed as follows. If implicit bias is associative and unreflective, then certain experimental manipulations cannot change implicitly biased behavior. However, these manipulations can change such behavior. So, implicit bias is not associative and unreflective. This paper (...) finds philosophical and empirical problems with that argument. When the problems are solved, the conclusion is not quite right: implicit bias is not necessarily unreflective, but it seems to be associative. Further, the paper shows that even if legitimate non-associative interventions on implicit bias exist, then both the received view and its recent contender would be false. In their stead would be interactionism or minimalism about implicit bias. (shrink)

According to one picture of the mind, decisions and actions are largely the result of automatic cognitive processing beyond our ability to control. This picture is in tension with a foundational principle in ethics that moral responsibility for behavior requires the ability to control it. The discovery of implicit attitudes contributes to this tension. According to the ability argument against moral responsibility, if we cannot control implicit attitudes, and implicit attitudes cause behavior, then we cannot be morally responsible for that (...) behavior. The purpose of this paper is to refute the ability argument. Drawing on both scientific evidence in cognitive science and philosophical arguments in ethics and action theory, I argue that it is invalid and unsound because current evidence is insufficient to establish the premises that implicit attitudes are uncontrollable, that they significantly cause behavior, that responsibility always requires ability, and that even if uncontrollable attitudes did fully cause behavior, this entails that the behavior they cause is uncontrollable. The rejection of the ability argument questions the priority of the unconscious over the conscious mind in cognitive science, deprioritizes ability in theories of moral responsibility in ethics, and provides a strong reason to uphold moral responsibility for implicitly biased behavior. (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)

At the University of Sheffield between 2011 and 2012, a leading group of philosophers, psychologists, and others gathered to explore the nature and significance of implicit bias. The two volumes of Implicit Bias and Philosophy emerge from these workshops. Each volume philosophically examines core areas of psychological research on implicit bias as well as the ramifications of implicit bias for core areas of philosophy. Volume II: Moral Responsibility, Structural Injustice, and Ethics is comprised of three parts. “Moral Responsibility for Implicit (...) Bias” contains chapters examining the relationship of implicit biases to concepts that are central to moral responsibility, including control, awareness, reasons-responsiveness, and alienation. The chapters in the second part—“Structural Injustice”—explore the connections between the implicit biases held by individuals and the structural injustices of the societies in which they are situated. And finally, the third part—“The Ethics of Implicit Bias: Theory and Practice”—contains chapters examining strategies for implicit attitude change, the ramifications of research on implicit bias for philosophers working in ethics, and suggestions for combating implicit biases in the fields of philosophy and law. (shrink)

Th is paper investigates the epistemic powers of democratic institutions through an assessment of three epistemic models of democracy : the Condorcet Jury Th eorem, the Diversity Trumps Ability Th eorem, and Dewey's experimentalist model. Dewey's model is superior to the others in its ability to model the epistemic functions of three constitutive features of democracy : the epistemic diversity of participants, the interaction of voting with discussion, and feedback mechanisms such as periodic elections and protests. It views democracy as (...) an institution for pooling widely distributed information about problems and policies of public interest by engaging the participation of epistemically diverse knowers. Democratic norms of free discourse, dissent, feedback, and accountability function to ensure collective, experimentallybased learning from the diverse experiences of diff erent knowers. I illustrate these points with a case study of community forestry groups in South Asia, whose epistemic powers have been hobbled by their suppression of women's participation. (shrink)

Research suggests that interventions involving extensive training or counterconditioning can reduce implicit prejudice and stereotyping, and even susceptibility to stereotype threat. This research is widely cited as providing an “existence proof” that certain entrenched social attitudes are capable of change, but is summarily dismissed—by philosophers, psychologists, and activists alike—as lacking direct, practical import for the broader struggle against prejudice, discrimination, and inequality. Criticisms of these “debiasing” procedures fall into three categories: concerns about empirical efficacy, about practical feasibility, and about the (...) failure to appreciate the underlying structural-institutional nature of discrimination. I reply to these criticisms of debiasing, and argue that a comprehensive strategy for combating prejudice and discrimination should include a central role for training our biases away. (shrink)

How do cognition and affect interact to produce action? Research in intergroup psychology illuminates this question by investigating the relationship between stereotypes and prejudices about social groups. Yet it is now clear that many social attitudes are implicit. This raises the question: how does the distinction between cognition and affect apply to implicit mental states? An influential view—roughly analogous to a Humean theory of action—is that “implicit stereotypes” and “implicit prejudices” constitute two separate constructs, reflecting different mental processes and neural (...) systems. On this basis, some have also argued that interventions to reduce discrimination should combat implicit stereotypes and prejudices separately. We propose an alternative framework. We argue that all putative implicit stereotypes are affect-laden and all putative implicit prejudices are “semantic,” that is, they stand in co-activating associations with concepts and beliefs. Implicit biases, therefore, consist in “clusters” of semantic-affective associations, which differ in degree, rather than kind. This framework captures the psychological structure of implicit bias, promises to improve the power of indirect measures to predict behavior, and points toward the design of more effective interventions to combat discrimination. (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)