In this paper, I examine whether the use of artificial intelligence (AI) and automated decision-making (ADM) aggravates issues of discrimination as has been argued by several authors. For this purpose, I first take up the lively philosophical debate on discrimination and present my own definition of the concept. Equipped with this account, I subsequently review some of the recent literature on the use AI/ADM and discrimination. I explain how my account of discrimination helps to understand that the general claim in (...) view of the aggravation of discrimination is unwarranted. Finally, I argue that the use of AI/ADM can, in fact, increase issues of discrimination, but in a different way than most critics assume: it is due to its epistemic opacity that AI/ADM threatens to undermine our moral deliberation which is essential for reaching a common understanding of what should count as discrimination. As a consequence, it turns out that algorithms may actually help to detect hidden forms of discrimination. (shrink)

The article analyses the concept of indirect discrimination, arguing first that existing conceptualisations are unsatisfactory and second that it is best understood as equal treatment that is disadvantageous to the discriminatees because of their group-membership. I explore four ways of further refining the definition, arguing that only an added condition of moral wrongness is at once plausible and helpful, but that it entails a number of new problems that may outweigh its benefits. Finally, I suggest that the moral wrongness of (...) indirect discrimination is best accounted for in terms of the harm it does to discriminatees, and sketch three ways in which it may do so. I conclude that the analysis provides both a clearer understanding of the concept of indirect discrimination as well as indirect support for a harm-based account of the wrongness of discrimination, while suggesting that our moral obligations qua non-discrimination may be more extensive than is frequently assumed. (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)

Definition of the problem Few concepts in recent ethical debates have enjoyed as much popularity as the concept of discrimination. However, a comparative discussion of the concept, including its conceptual nuances and its ethical significance for health care, has so far been lacking. The aim of this paper is to develop a nuanced understanding of discrimination based on the philosophical and sociological literature against the background of ethically relevant medical and nursing scenarios. Methods Using practical examples from health care, we (...) discuss direct, indirect, and statistical discrimination; we examine the importance of intentions and the role of collective actors. In addition, we analyze which social groups may experience discrimination and the respective importance of forms of epistemic injustice. Conclusions We argue that despite its complexity, the concept offers significant added value because it allows us to highlight forms of disadvantage that go beyond the violation of individual specific rights or interests. As a knowledge-based system of great societal influence, health care exhibits some characteristics that can foster discrimination. Acknowledging this fact is essential in order to effectively address discrimination. (shrink)

Algorithmic discrimination has rapidly become a topic of intense public and academic interest. This article explores three issues raised by algorithmic discrimination: 1) the distinction between direct and indirect discrimination, 2) the notion of disadvantageous treatment, and 3) the moral badness of discriminatory automated decision-making. It argues that some conventional distinctions between direct and indirect discrimination appear not to apply to algorithmic discrimination, that algorithmic discrimination may often be discrimination between groups, as opposed to against groups, and that it is (...) not necessarily the case that morally bad algorithmic discrimination gives us reason to not use automated decision-making. For each of the three issues, the article explores implications for algorithmic discrimination, suggests some alternative answers, and clarifies how we may want to think of discrimination more broadly in light of lessons drawn from the context of algorithmic discrimination. (shrink)

Victims of oppressive (e.g., sexist, racist or ableist) structures sometimes internalize the unjust norms that prevail in society. This can cause these victims to develop preferences or make deci-sions that seem bad for them. Focusing on such cases, we ask: is self-discrimination disrespectful? We show that some of the most sophisticated respect theories fail to provide any clear guidance. Specifically, we show that the widely recognized view that respect has two dimensions—an interest dimension and an autonomy dimension—delivers completely opposite verdicts (...) depending on how these two dimensions (and the relation between them) are specified. A main takeaway point is that we need to distinguish between at least four different respect-based views. Whether self-discrimination caused by internalized oppression is disrespectful depends on which view one supports. (shrink)

What is the morally significant feature of discrimination? All of the following seem plausible – (i) discrimination is a kind of wrongdoing and it wrongs discriminatees, which is a matter of intrapersonal morality; (ii) in view of cases of indirect discrimination, significant normative features of discrimination are best captured in a discriminatee‐focused, or harm‐based, way; and (iii) discrimination, as an act‐type, necessarily involves interpersonal comparison. The first task of this article is to address which of intra‐ or interpersonal comparison is (...) relevant to philosophical questions concerning discrimination. I submit that each of them has a place in the theory of discrimination; while interpersonal comparison is relevant in determining whether a differentiating act counts as discrimination, intrapersonal comparison is relevant in assessing whether it is morally wrong. The second task is to develop further a harm‐based answer to the latter question. My final proposal is as follows: discrimination is pro tanto morally wrong to the extent that it makes the discriminatees worse off than they would be were it not for the discrimination at issue, where one's well‐being is understood in terms of what one endorses in one's optimum form. (shrink)

This article addresses the moral and legal difficulties sport governing bodies encounter as human rights promoters. The case presented here is the 2023 decision by the International Olympic Committee (IOC) to allow athletes from Russia and Belarus to compete in international sport under neutral colours, after recommending complete exclusion a year before due to the Russian invasion of Ukraine. While IOC’s change of mind was influenced by UN experts on human rights, claiming that the ban discriminated against Russian athletes, the (...) same experts fail to take into account competing human rights elements that could favour the ban. To that end, this article discusses the complexities of prioritizing human rights in an Olympic context and, deriving from that, demonstrates the existence of moral and legal support for upholding the exclusion of Russia. Finally, the analysis of how to prioritize morally and legally between competing human rights offers deliberative material to other sport governing bodies which could be used to carve out preventive measures prior to their next encounter with a similar situation. (shrink)

Credentialism refers to the practice of hiring or promoting applicants on the basis of their educational qualifications. In this paper, we argue that this can amount to wrongful discrimination against the less qualified. A standard way to defend credentialism appeals to the fact that it minimizes the costs of production. We argue that this argument has unacceptable implications in some cases involving disability- and gender-based discrimination. We claim that, once we appropriately revise this argument, credentialism is revealed to be similarly (...) wrongfully discriminatory. We then consider two objections and draw some preliminary lessons for policymaking. (shrink)

Can a minority agent, Jamal, discriminate against a majority agent, Dave, conceptually speaking? Taking an experimental-philosophical approach, this article addresses the conceptual puzzle by investigating both the ordinary usage of discrimination and whether the academic literature reflects the folk concept. First, it provides a conceptual analysis of discrimination as it is used across the discrimination research field. The analysis produces two novel definitions of discrimination: a symmetric conception, which implies multi-directionality, and an asymmetric conception, which implies uni-directionality. Then, I empirically (...) investigate the US lay concept of discrimination (N = 1,487). The highlight of the paper is an experiment on whether US ordinary usage is symmetric or asymmetric (Study 1), tested across four contexts and three traits (Hiring: Gender, Club: Sexuality, Dating: Race, Parental: Gender). In addition, I study which groups are most often discriminated against, according to respondents, to record potential sensitivity to the frequency of discrimination (Study 2). Overall, the results show that ordinary usage in the US is symmetric across different contexts and traits, and that paradigmatic minority groups are most often discriminated against. So, according to respondents, Jamal can discriminate against Dave, although Jamal is more often discriminated against than Dave. (shrink)

Discrimination is usually thought of in terms of socially salient groups, such as race or gender. Some scholars argue that the rise of algorithmic decision‐making poses a challenge to this notion. Algorithms are not bound by a social view of the world. Therefore, they may not only inherit pre‐existing social biases and injustices but may also discriminate based on entirely new categories that have little or no meaning to humans at all, such as ‘being born on a Tuesday’. Should this (...) prospect change how we theorize about discrimination, and should we protect these algorithmic groups, as some have suggested? I argue that the phenomenon is adequately described as ‘discrimination’ when a group is systematically disadvantaged. At present, we lack information about whether any algorithmic group meets this criterion, so it is difficult to protect such groups. Instead, we should prevent algorithms from disproportionately disadvantaging certain individuals, and I outline strategies for doing so. (shrink)

It is usually accepted that whether or not indirect discrimination is a form of immoral discrimination, it appears to be structurally different from direct discrimination. First, it seems that either one involves the agent focusing on different things while making a decision. Second, it seems that the victim’s group membership is relevant to the outcomes of either sort of action in different ways. In virtue of these two facts, it is usually concluded that indirect discrimination is structurally different from direct (...) discrimination. I argue against the notion that indirect discrimination and direct discrimination have significantly different structures. I first argue that both kinds of discrimination involve similar decision-making processes. Second, I analyze how being in a social group affects personal identity, and from there argue that indirect discrimination and direct discrimination are about group membership similarly. In virtue of these two arguments, I conclude that direct and indirect discrimination are structurally similar. (shrink)

Statistical discrimination is a form of discrimination that uses statistical inferences about the groups to which individuals belong as grounds for treating them differently. It remains unclear what, if anything, makes statistical discrimination wrong. My thesis argues that statistical discrimination is wrong because, and insofar as, it contributes to existing social injustice. After an introduction to the issues in section 1, section 2 clarifies the concept of statistical discrimination and its differences with non-statistical discrimination. Section 3 discusses different accounts that (...) seek to explain when and why statistical discrimination is wrong. I examine two approaches, one of which regards the wrong of statistical discrimination as part of discrimination in general, while the other conceives of the wrong as distinctive to statistical discrimination itself. I argue the former approach is better. Among different accounts within the approach, the context-based consequentialist account that explains the wrong in relation to existing social injustice is most promising. Section 4 uses racial profiling as an example to illustrate how the account can help explain this hard case of statistical discrimination, calling upon an argument developed by Benjamin Eidelson. (shrink)