This paper examines the problem of selecting a number of candidates to receive a good (admission) from a pool in which there are more qualified applicants than places. I observe that it is rarely possible to order all candidates according to some relevant criterion, such as academic merit, since these standards are inevitably somewhat vague. This means that we are often faced with the task of making selections between near-enough equal candidates. I survey one particular line of response, which says (...) that we should allow our choice of borderline candidates to be guided by non-relevant criteria such as gender-balancing. I argue that this would not, as commonly objected, be a case of sex discrimination if it is to be applied either in favour of men or women. Nonetheless, I argue that such policies are problematic because they violate the demand for publicity, which is required for legitimacy and to assure everyone that discrimination has not in fact taken place. Instead, I suggest that, if we are concerned to avoid discrimination, there may be a case for using lotteries as tie-breakers, not on grounds of fairness but to prevent taint of bias. (shrink)

abstract This paper examines the problem of selecting a number of candidates to receive a good (admission) from a pool in which there are more qualified applicants than places. I observe that it is rarely possible to order all candidates according to some relevant criterion, such as academic merit, since these standards are inevitably somewhat vague. This means that we are often faced with the task of making selections between near‐enough equal candidates. I survey one particular line of response, which (...) says that we should allow our choice of borderline candidates to be guided by non‐relevant criteria such as gender‐balancing. I argue that this would not, as commonly objected, be a case of sex discrimination if it is to be applied either in favour of men or women. Nonetheless, I argue that such policies are problematic because they violate the demand for publicity, which is required for legitimacy and to assure everyone that discrimination has not in fact taken place. Instead, I suggest that, if we are concerned to avoid discrimination, there may be a case for using lotteries as tie‐breakers, not on grounds of fairness but to prevent taint of bias. (shrink)

Many philosophers think that we should use a lottery to decide who gets a good to which two persons have an equal claim but which only one person can get. Some philosophers think that we should save identified persons from harm even at the expense of saving a somewhat greater number of statistical persons from the same harm. I defend a principled way of justifying both judgements, namely, by appealing to the decreasing marginal moral value of survival chances. I identify (...) four desiderata that, I contend, any such justification should satisfy, and explain how my account meets these desiderata, unlike some previous accounts. (shrink)

The Black Lives Matter movement has called for the abolition of capital punishment in response to what it calls “the war against Black people” and “Black communities.” This article defends the two central contentions in the movement’s abolitionist stance: first, that US capital punishment practices represent a wrong to black communities rather than simply a wrong to particular black capital defendants or particular black victims of murder, and second, that the most defensible remedy for this wrong is the abolition of (...) the death penalty. (shrink)

This is a critical discussion of the Baldus study of capital sentencing in Georgia. It concludes that the Baldus finding of a "race-of-the-victim" effect is less robust than capital-punishment abolitionists have claimed. But the flaws in the Baldus study should not comfort death-penalty advocates, for they reveal an epistemological barrier to the US Supreme Court's ever being able to satisfy itself both that the sentence reflects particularized consideration of the circumstances and character of the defendant and that it is not (...) the product of racial bias. (shrink)

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

The increasing implementation of and reliance on machine-learning (ML) algorithms to perform tasks, deliver services and make decisions in health and healthcare have made the need for fairness in ML, and more specifically in healthcare ML algorithms (HMLA), a very important and urgent task. However, while the debate on fairness in the ethics of artificial intelligence (AI) and in HMLA has grown significantly over the last decade, the very concept of fairness as an ethical value has not yet been sufficiently (...) explored. Our paper aims to fill this gap and address the AI ethics principle of fairness from a conceptual standpoint, drawing insights from accounts of fairness elaborated in moral philosophy and using them to conceptualise fairness as an ethical value and to redefine fairness in HMLA accordingly. To achieve our goal, following a first section aimed at clarifying the background, methodology and structure of the paper, in the second section, we provide an overview of the discussion of the AI ethics principle of fairness in HMLA and show that the concept of fairness underlying this debate is framed in purely distributive terms and overlaps with non-discrimination, which is defined in turn as the absence of biases. After showing that this framing is inadequate, in the third section, we pursue an ethical inquiry into the concept of fairness and argue that fairness ought to be conceived of as an ethical value. Following a clarification of the relationship between fairness and non-discrimination, we show that the two do not overlap and that fairness requires much more than just non-discrimination. Moreover, we highlight that fairness not only has a distributive but also a socio-relational dimension. Finally, we pinpoint the constitutive components of fairness. In doing so, we base our arguments on a renewed reflection on the concept of respect, which goes beyond the idea of equal respect to include respect for individual persons. In the fourth section, we analyse the implications of our conceptual redefinition of fairness as an ethical value in the discussion of fairness in HMLA. Here, we claim that fairness requires more than non-discrimination and the absence of biases as well as more than just distribution; it needs to ensure that HMLA respects persons both as persons and as particular individuals. Finally, in the fifth section, we sketch some broader implications and show how our inquiry can contribute to making HMLA and, more generally, AI promote the social good and a fairer society. (shrink)

What training should engineering students receive to enable them to contribute to reducing bias, discrimination and the persistent lack of diversity in engineering? Collaboration is central to professional engineering work and, consequently, teamwork and group projects are increasingly present in engineering curricula. However, the influence of unconscious bias on interactions within teams can negatively affect women and underrepresented groups and is now recognised as an important engineering ethics issue. This paper describes a workshop designed to enable engineering students to work (...) equitably in diverse teams. Key features of the workshop include (1) the emotionally safe, empowering and warm environment created, (2) the creation of opportunities for students to discuss and apply the issues raised to their own engineering projects, and (3) the opportunities to practice the use of both proactive and reactive strategies to address bias and discrimination in teams. The evaluation of the workshop suggests that engineering students regarded both onsite and online formats as providing useful skills that they intended to apply in practice. Follow-up evaluations suggest that the workshop leads to behavioural change, especially the use of proactive teamwork strategies intended to reduce the impact of unconscious bias. (shrink)

In recent years, the work of organizations in the area of digitization has intensified significantly. This trend is also evident in the field of recruitment where job application tracking systems (ATS) have been developed to allow job advertisements to be published online. However, recent studies have shown that recruiting in most organizations is not inclusive, being subject to human biases and prejudices. Most discrimination activities appear early but subtly in the hiring process, for instance, exclusive phrasing in job advertisement discourages (...) qualified applicants from minority groups from applying. The existing works are limited to analyzing, categorizing and highlighting the occurrence of bias in the recruitment process. In this paper, we go beyond this and develop machine learning models for identifying and classifying biased and discriminatory language in job descriptions. We develop and evaluate a machine learning system for identifying five major categories of biased and discriminatory language in job advertisements, i.e., masculine-coded, feminine-coded, exclusive, LGBTQ-coded, demographic and racial language. We utilized the combination of linguistic features with recent state-of-the-art word embeddings representations as input features for various machine learning classifiers. Our results show that the machine learning classifiers were able to identify all the five categories of biased and discriminatory language with a decent accuracy. The Random Forest classifier with FastText word embeddings achieved the best performance with tenfolds cross-validation. Our system directly addresses the bias in the attraction phase of hiring by identifying and classifying biased and discriminatory language and thus encouraging recruiters to write more inclusive job advertisements. (shrink)

Luck egalitarianism is a responsibility-sensitive theory of distributive justice. Its application to health and healthcare is controversial. This article addresses a novel critique of luck egalitarianism, namely, that it wrongfully discriminates against those responsible for their health disadvantage when allocating scarce healthcare resources. The philosophical literature about discrimination offers two primary reasons for what makes discrimination wrong (when it is): harm and disrespect. These two approaches are employed to analyze whether luck egalitarian healthcare prioritization should be considered wrongful discrimination. Regarding (...) harm, it is very plausible to consider the policies harmful but much less reasonable to consider those responsible for their health disadvantages a socially salient group. Drawing on the disrespect literature, where social salience is typically not required for something to be discrimination, the policies are a form of discrimination. They are, however, not disrespectful. The upshot of this first assessment of the discrimination objection to luck egalitarianism in health is, thus, that it fails. (shrink)

In this paper, I argue that instead of primarily paying attention to the nature of implicit attitudes that are taken to cause implicit discrimination, we should investigate how discrimination can be implicit in itself. I propose to characterize implicit discrimination as unintentional discrimination: the person responds to facts unintentionally and often unconsciously which are, given their end, irrelevant and imply unfair treatment. The result is a unified account of implicit bias that allows for the different ways in which it can (...) display itself and can be explained. Furthermore, the view can account for the central characteristics of implicit bias: (1) that it is, for a variety of reasons, difficult to control, (2) that we are not necessarily unconscious of implicit bias but not properly conscious either, and (3) that we can unintentionally discriminate regardless of whether we claim to care about fairness. (shrink)

Faced with a choice between saving one stranger and saving a group of strangers, some people endorse weighted lotteries, which give a strictly greater chance of being saved to the group of strangers than the single stranger. In this paper I attempt to criticize this view. I first consider a particular version of the weighted lotteries, Frances Kamm's procedure of proportional chances, and point out two implausible implications of her proposal. Then, I consider weighted lotteries in general, and claim (1) (...) that the correct thing to distribute is not the chance of being saved but the good of being saved, (2) that assigning some chance to the single stranger is not the only way to give a positive (and equal) respect to the people concerned, and (3) that the weighted lottery appears to be deceptive since it would show the respect to the single stranger in a negligible way. (shrink)

이 글은 인공지능에 의한 차별과 그 책임 논의를 철학적 차원에서 본격적으로 연구하기에 앞선 예비적 고찰이다. 인공지능에 의한 차별을 철학자들의 연구를 요하는 당면 ‘문제’로 제기하고, 이를 위해 ‘인공지능에 의한 차별’이라는 문제의 성격과 원인을 규명하는 것이 이 글의 주된 목적이다. 인공지능은 기존 차별을 그대로 반복하여 현존하는 차별의 강화 및 영속화를 야기할 수 있으며, 이는 먼 미래의 일이 아니다. 이러한 문제는 현재 발생 중이며 공동체적 대응을 요구한다. 그러나 철학자의 입장에서 그와 관련한 책임 논의를 다루기는 쉽지 않다. 그 이유는 크게 인공지능의 복잡한 기술적 문제와 (...) 전통적 책임 개념의 한계라 할 수 있다. 여기서는 특히 인공지능과 관련된 기술적 개념을 중심으로 문제를 파악하고, 이와 관련하여 인간 행위자의 책임 및 그 역량을 규명한다. 통칭 인공지능으로 이해되는 것은 알고리즘에 기반한 자동화 시스템이며, 알고리즘의 편향성이 인공지능에 의한 차별을 야기할 수 있다. 알고리즘이 겉보기에 인간 행위자와 독립적으로 작동하는 것처럼 보일지라도, 인간 행위자가 그에 개입하고 있음을 밝힌다. 인간 행위자가 편향된 입력 자료를 사용하거나 편향된 설계를 할 수 있다는 점에서, 알고리즘의 편향성은 인간 행위자의 편향성과 불가분의 관계이기 때문이다. 그러므로 인간 행위자는 인공지능에 의한 차별문제에 대응할 책임이 있으며, 책임 역량을 갖고 있다. 마지막으로 인공지능에 의한 차별 논의를 위한 철학 연구의 추후 과제를 정리한다. (shrink)

The vegan ideal is entailed by arguments for ethical veganism based on traditional moral theory (rights and/or utilitarianism) extended to animals. The most ideal lifestyle would abjure the use of animals or their products for food since animals suffer and have rights not to be killed. The ideal is discriminatory because the arguments presuppose a male physiological norm that gives a privileged position to adult, middle-class males living in industrialized countries. Women, children, the aged, and others have substantially different nutritional (...) requirements and would bear a greater burden on vegetarian and vegan diets with respect to health and economic risks, than do these males. The poor and many persons in Third World nations live in circumstances that make the obligatory adoption of such diets, where they are not already a matter of sheer necessity, even more risky.Traditional moral theorists (such as Evelyn Pluhar and Gary Varner whose essays appear in this issue) argue that those who are at risk would beexcused from a duty to attain the virtue associated with ethical vegan lifestyles. The routine excuse of nearly everyone in the world besides adult, middle-class males in industrialized countries suggests bias in the perspective from which traditional arguments for animal rights and (utilitarian) animal welfare are formulated. (shrink)

Although the demographics on male versus female death-row prisoners suggest that males are the criminal justice system’s primary targets, the author argues that the system still discriminates against women. Utilizing postmodern scholarship, he argues that female prisoners are punished primarily for violating dominant norms of gender correctness.

For nearly five years, bioethicists and neurologists debated whether Jahi McMath, an African American teenager, was alive or dead. While Jahi's condition provides a compelling study for analyzing brain death, circumscribing her life status to a question of brain death fails to acknowledge and respond to a chronic, if uncomfortable, bioethics problem in American health care—namely, racial bias and unequal treatment, both real and perceived. Bioethicists should examine the underlying, arguably broader social implications of what Jahi's medical treatment and experience (...) represented. On any given day, disparities in the quality of health care and health outcomes for people of color in comparison to whites are evidenced in American hospitals and clinics. These disparities are not entirely explained by differences in patient education, insurance status, employment, income, expressed preference for treatments, and severity of disease. Instead, research indicates that, even for African Americans able to gain access to health care services and navigate institutional nuances, disparities persist across a broad range of services, including diagnostic screening and general medical care, mental health diagnosis and treatment, pain management, HIV‐related care, and treatments for cancer, heart disease, diabetes, and kidney disease. (shrink)

This book presents and deconstructs the existing explanations for the differential career development of qualified men and women. It reframes the problem of discrimination in the workplace as a matter of organizational ethics, social responsibility and compliance with existing equal opportunity laws. Sensitive points are identified where social biases, decision-makers' individual economic interests and shortcomings of organizational incentive policies may lead to discrimination against qualified women. The ideas put forward are empirically tested in an original laboratory experiment that examines personnel (...) selection in the male-dominated field of science and technology. It contrasts the selection of applicants with gendered and gender-blind applications available to subjects under controlled conditions. 30% of participants were high-level decision-makers, which is unprecedented in this field of research. The results, highly relevant for organizational practice, are explained and discussed in detail. (shrink)

A much discussed question in the philosophy of death is whether both of the following claims are true: (1) it is at least typically appropriate to prefer dying further in the future to dying less far in the future; and (2) it is at least typically appropriate not to prefer having been created further in the past to having been created less far in the past. Some philosophers have tried to defend (1) and (2) by appeal to the alleged appropriateness (...) of future bias—roughly, greater concern for certain goods and bads in one's future than for certain goods and bads in one's past. I argue that such approaches to defending (1) and (2) probably cannot succeed, by arguing that even if a very strong version of future bias is appropriate, it does not follow that (1) and (2) are both true. Philosophers attracted to the conjunction of (1) and (2) ought to try to defend it by appeal to something other than future bias. (shrink)

Two self-report experiments examined how religiosity affects attributions made for the outcome of a tornado. Undergraduate students and online adults read a fictional vignette about a tornado that hits a small town in the United States. The townspeople met at church and prayed or prepared emergency shelters for three days before the tornado; either no one died or over 200 people died from the tornado. Participants made attributions of cause to God, prayer, faith, and worship. In both studies, individuals identifying (...) as Christian made more attributions to God, prayer, faith, and worship, but only when no one died; when townspeople died, Christian participants made fewer attributions to God, prayer, faith, and worship. Individuals identifying as agnostic or atheist did not show this bias. Directions for future research in terms of implicit religious beliefs and normative evaluations of religion are discussed. (shrink)

Disability might be relevant to decisions about life support in intensive care in several ways. It might affect the chance of treatment being successful, or a patient’s life expectancy with treatment. It may affect whether treatment is in a patient’s best interests. However, even if treatment would be of overall benefit it may be unaffordable and consequently unable to be provided. In this paper we will draw on the example of neonatal intensive care, and ask whether or when it is (...) justified to ration life-saving treatment on the basis of disability. We argue that predicted disability is relevant both indirectly and directly to rationing decisions. (shrink)

This paper focuses on three distinct issues in Fischer’s Death, Immortality, and Meaning in Life, viz. meaning in life, fearing death, and asymmetrical attitudes between our prenatal and postmortem non-existence. I first raise the possibility that life’s total meaning can be negative and argue that immoral or harmful acts are plausibly meaning-detracting acts, which could make the lives of historically impactful evil dictators anti-meaningful. After that, I review Fischer’s two necessary conditions for meaning in life and argue against each. In (...) the second section, I review Fischer’s argument that we should fear death in virtue of it bringing about a permanent loss of our viewpoint. I offer an opposing argument that only intrinsic badness is a fitting object of fear. Since death is extrinsically bad, it cannot merit fear, even though it can be the appropriate object of other negative attitudes. In the third and final section, I consider Fischer’s solution to the asymmetry problem, which appeals to the rationality of temporal bias. I then raise two worries about it. I first argue that temporal bias is not necessarily, as Fischer claims, survival conducive. I then argue that, even if it is, this may actually be an epistemic defeater for the rationality of temporal bias. (shrink)

Frailty is a state of increased vulnerability to poor resolution of homeostasis after a stressor event. Frailty is most frequently assessed in the old using the Clinical Frailty Scale (CSF) which ranks frailty from 1 to 9. This assessment typically takes less than one minute and is not validated in patients with learning difficulties or those under 65 years old. The National Institute for Health and Care Excellence (NICE) developed guidelines that use “frailty” as one of the priority-setting criteria (...) for how scarce, but potentially lifesaving, health care resources should be allocated during the COVID-19 pandemic. Similar guidelines have been developed elsewhere. This paper discusses the ethical implications of such rationing and argues that this is an unproven and ethically problematic form of health care rationing. It specifically discusses: (1) how the frailty ascription becomes a self-fulfilling prophecy, (2) the problematic use of “frailty” in COVID-19 “triage,” (3) the circularity of the link between age and frailty, (4) indirect discrimination because of the use of a seemingly neutral criterion in health care rationing, and (5) the difficult link between comorbidities and frailty. It is found that there was no research into the use of global frailty scores as a criterion for access to acute treatment before January 2020 and so it is concerning how readily frailty scoring has been adopted to ration access to potentially lifesaving treatments. Existing gerontological frailty scoring systems have not been developed for this purpose, and repurposing them creates significant ethical issues. (shrink)

BackgroundThe state of the world is one with scarce medical resources where longevity is not equally distributed. Given such facts, setting priorities in health entails making difficult yet unavoidable decisions about which lives to save. The business of saving lives works on the assumption that longevity is valuable and that an early death is worse than a late death. There is a vast literature on health priorities and badness of death, separately. Surprisingly, there has been little cross-fertilisation between the academic (...) fields of priority setting and badness of death. Our aim is to connect philosophical discussions on the badness of death to contemporary debates in health priorities.DiscussionTwo questions regarding death are especially relevant to health priorities. The first question is why death is bad. Death is clearly bad for others, such as family, friends and society. Many philosophers also argue that death can be bad for those who die. This distinction is important for health priorities, because it concerns our fundamental reasons for saving lives. The second question is, ‘When is the worst time to die?’ A premature death is commonly considered worse than a late death. Thus, the number of good life years lost seems to matter to the badness of death. Concerning young individuals, some think the death of infants is worse than the death of adolescents, while others have contrary intuitions. Our claim is that to prioritise between age groups, we must consider the question of when it is worst to die.ConclusionsDeprivationism provides a more plausible approach to health priorities than Epicureanism. If Deprivationism is accepted, we will have a firmer basis for claiming that individuals, in addition to having a health loss caused by morbidity, will have a loss of good life years due to mortality. Additionally, Deprivationism highlights the importance of age and values for health priorities. Regarding age, both variants of Deprivationism imply that stillbirths are included in the Global Burden of Disease. Finally, we suggest that the Time-Relative Interest Account may serve as an alternative to the discounting and age weighting previously applied in the Global Burden of Disease. (shrink)

The present comment concerns a recent AI & Ethics article which purports to report evidence of speciesist bias in various popular computer vision (CV) and natural language processing (NLP) machine learning models described in the literature. I examine the authors' analysis and show it, ironically, to be prejudicial, often being founded on poorly conceived assumptions and suffering from fallacious and insufficiently rigorous reasoning, its superficial appeal in large part relying on the sequacity of the article's target readership.

Cesario criticizes the experimental design of studies of bias by claiming that acting on stereotypes in the experimental situation might not be an “error” from a Bayesian perspective. However, social psychologists might have an ethical reason to label the observed decision-maker biases as “erroneous.” Decision-making can be considered as “biased” and “erroneous,” because it reflects illegal and morally condemnable discrimination.

Drawing upon empirical studies of racial discrimination dating back to the 1940’s, the Movement for Black Lives platform calls for the abolition of capital punishment. Our purpose here is to defend the Movement’s call for death penalty abolition in terms congruent with its claim that the death penalty in the U.S. is a “racist practice” that “devalues Black lives.” We first sketch the jurisprudential history of race and capital punishment in the U.S., wherein courts have occasionally expressed worries about racial (...) injustice but have usually taken such evidence to warrant reform but not outright abolition. We argue that the racial discrimination at issue flows in significant part from implicit biases concerning race, criminality, and violence, which do not fit comfortably within the picture of racial bias advanced by the courts. The case for abolition, we contend, rests on Black Americans as a class (not merely those who interact with the criminal justice system as capital defendants or as murder victims) being subject to such bias and thereby not being accorded equal status under the law. (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)

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

In this paper I take issue with Heidegger's use of the concept of death as a means of disclosing human finitude. I argue that Being‐towards‐death is inadequate to the disclosure of Dasein's thrownness which is necessary for the kind of authentic historizing that Heidegger describes and furthermore leads to a reading of authenticity which is preclusive of Being‐with‐Others, I suggest that this difficulty may be alleviated through increased attention to the opposite boundary of Dasein's existence, namely its birth. Although I (...) do not pursue the project here of conducting a phenomenology of birth, I suggest some directions for proceeding with that task, and I illustrate that a greater emphasis on Dasein's beginning will increase the richness of our understanding of our Being‐with‐Others. (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. Its 12 chapters (...) are 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 annotated reading suggestions. And a companion webpage contains teaching resources. The volume is 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)

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)

Philosophers and psychologists routinely explore questions surrounding reasoning, inquiry, and bias, though typically in disciplinary isolation. What is the source of our intellectual errors? When can we trust information others tell us? This volume brings together researchers from across the two disciplines to present ideas and insights for addressing the challenges of knowing well in a complicated world in four parts: how to best describe the conceptual and empirical terrain of reason and bias; how reasoning and bias influence basic perception (...) of the physical world; how to assess knowledge and expertise in ourselves and others; and how people approach reasoning and knowledge among and about groups. Together, the chapters show what philosophers and psychologists can do together when they shine light on the challenges of reaching the truth and avoiding errors. Reason, Bias, and Inquiry is a multidisciplinary meditation for readers who are awash in information but are uncertain how to manage it to make informed decisions. (shrink)

This study provides a ‘pyramid of hate’ perspective on issues and challenges facing minority religious communities in social and political climates that bestow permission to hate. Previous research shows that adverse social stereotypes and biases, together with non-inclusive policies and practices at the level of the state, create an enabling environment that signals the legitimacy of public hostility towards a minority community. This paper argues that such climates of hate within and outside the workplace may be better understood by paying (...) attention to the multiple levels of hate, i.e., biased attitudes, biased actions, discrimination and violence. In its extreme form, such climate may lead to indiscriminate massacres and genocide. This contextual study draws on interviews with 76 Shia Muslim professionals and employees in Pakistan to provide a ‘pyramid of hate’ perspective on issues of bias, discrimination and violence facing them. The study unveils a range of experiences, from subtle bias and stereotyping to blatant harassment, discrimination and hostilities facing Shia professionals and employees in Pakistan. The study is unique as it integrates the notion of pyramid of hate into management and organization studies and advances this theory by examining issues of sect-based bias, discrimination and violence within one religion. (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)

That discrimination exists in courts of law is beyond dispute. In American murder cases, for instance, studies show that blacks who kill a white are much more likely to receive the death penalty than if they kill a black. Indeed, in Georgia, they are 30 times more likely to be condemned, and in Texas a staggering 90 times more likely. Conversely, in Texas, of 143 whites convicted of killing a black, only one was sentenced to die. But how extensive is (...) discrimination in the courtroom? Is it strictly a matter of racial prejudice, or does it respond to a wide range of social factors? In Sociological Justice, eminent legal sociologist Donald Black challenges the conventional notion that law is primarily an affair of rules and that discrimination is an aberration. Law, he contends, is a social process in which bias is inherent. Indeed, Black goes well beyond the documented instances of racial discrimination to show how social status, the degree of intimacy, speech, organization, and numerous other factors all greatly influence whether a complaint will be filed in court, who will win, and what the punishment or other remedy will be. Moreover, he extends his analysis to include not only the litigants, but also the lawyers, the jurors, and the judge, describing how their social characteristics can also influence a case. Sociological Justice introduces a new field of legal scholarship that will have important consequences for the future of law: the sociology of the case. Black discusses how lawyers can use the sociology of the case to improve their practice and, for those interested in reform, he suggests ways to minimize bias in the courtroom. Beyond this, Black demonstrates that modern jurisprudence, with its assumption that like cases will be treated in like fashion, is out of touch with reality. He urges the adoption of a new sociological jurisprudence, with a new morality of law, that explicitly addresses the social relativity of justice. A major contribution to legal scholarship, this thought-provoking volume is essential reading for anyone interested in law and justice in modern society. (shrink)

ABSTRACT In 1975 John Harris envisaged a survival lottery to redistribute organs from one to a greater number in order to reduce number of deaths as a consequence of organ failure. In this paper I reach a conclusion about when running a survival lottery is permissible by looking at the reason prospective participants have for allowing the procedure from a contractual perspective. I identify three versions of the survival lottery. In a National Lottery, everyone within a jurisdiction is a candidate (...) for being a donor for everyone else, disregarding all differences between individuals' eventual possibility of needing an organ. In a Group Specific Lottery, it is a question of running a lottery among members of a specific group who share the same probability of getting organ failure. In a Local Lottery one randomises among individuals who are already in need of a new organ but who happen to be compatible and in need of different organs. While the first is vulnerable to considerations of fairness, it is difficult to perceive a feasible way to implement the second option that does not come with a host of unwelcome consequences. I argue, however, that it is permissible to run Local Lotteries. (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)