It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the (...) resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

What is discrimination and what makes wrongful discrimination wrong? Even after an ever-rising tide of research over the course of the past twenty-five or so years these questions still remain hard to answer. Exercising candid and self-critical hindsight, Larry Alexander, who contributed his fair share to this tide, thus remarked: “All cases of discrimination, if wrongful, are wrongful either because of their quite contingent consequences or perhaps because they are breaches of promises or fiduciary duties.” If this is true it (...) raises serious doubts as to how wrongful discrimination can be a moral wrong in itself. Also, the question comes up as to who it is who breaches a promise or a fiduciary duty. This paper defends the view that the substance of these remarks is better understood by couching them in a political approach towards discrimination. Against this background, they give rise to real and pressing concerns. Once we conceptualise the realm political along Hobbesian lines as the battleground comprising both the private sphere of the individual and the public sphere of the commonwealth it emerges that discrimination has different significance with regard to these respective spheres. In order to illustrate this, I adopt Kasper Lippert-Rasmussen’s descriptive account of discrimination as „differential treatment on the basis of membership of a socially salient group“ and the common view that wrongful discrimination is wrong because it is harmful, disrespectful, or both. In the private sphere the case can be made for morally permissible cases of discrimination. Sexual discrimination due to sexual self-determination with consequently freely choosing your sexual or romantic partner is the central case in point. Where somebody feels unfairly rejected and consequently hurt neither the charge of harm inflicted nor that of disrespect endured need be justified. No “breach of promises or fiduciary duties” is involved. The case is different, however, when it comes to the fiduciary of power. In discriminating, he who exercises the power of the commonwealth necessarily breaches a promise and a fiduciary duty. Discrimination thus appears to be more of a problem of political philosophy than one of applied ethics. [in German] **************************************************************************************************** ******************** Was ist Diskriminierung und warum ist Diskriminierung verwerflich, wenn sie es denn ist? Dies bleibt ungeachtet der seit fünfundzwanzig Jahren anschwellenden Forschungsliteratur unverändert eine harte Nuss. Larry Alexander, der selbst maßgeblich zu dieser Forschungsliteratur beigetragen hat, merkt daher selbstkritisch an: „All cases of discrimination, if wrongful, are wrongful either because of their quite contingent consequences or perhaps because they are breaches of promises or fiduciary duties.“ Wenn dies der Fall ist, stellt sich die Frage, wie moralisch verwerfliche Diskriminierung dann noch an sich verwerflich sein kann. Es stellt sich dann auch die Frage, wer hier ein Versprechen bricht und seine Treuepflichten verletzt. Die leitende Annahme dieses Aufsatzes ist es, dass man dem sachlichen Kern dieser Bedenken Rechnung tragen kann, indem man eine politische Perspektive auf das Phänomen der Diskriminierung einnimmt. Die Bedenken erweisen sich dann als substanziell und zutreffend. Konzeptualisieren wir den Bereich des Politischen mit Thomas Hobbes als das Spannungsfeld, das die private Sphäre des Individuums und die öffentliche Sphäre des Gemeinwesens gegeneinander abgrenzt, wird sichtbar, dass Diskriminierung in diesen Sphären jeweils unterschiedlich zu bewerten ist. Um dies zu verdeutlichen, lege ich Kasper Lippert-Rasmussens deskriptives Verständnis von Diskriminierung als „differential treatment on the basis of membership of a socially salient group“ zugrunde und mache von der in der Diskussion verbreiteten Ansicht Gebrauch, dass das Zufügen von Schaden oder die Verweigerung von Respekt Diskriminierung verwerflich macht. In der privaten Sphäre kann es nun Fälle moralisch zulässiger Diskriminierung geben. Zentral ist die sexuelle Diskriminierung aufgrund der Ausübung einer freien Wahl des eigenen Sexual- oder Liebespartners. Auch wenn sich der Abgewiesene womöglich geschädigt sieht, wird unbilliger Schaden nicht zugefügt und geschul- deter Respekt nicht verweigert. Den Grund finden wir in Alexanders Formel: Ein „breach of promises“ oder eine Verletzung „fiduciary duties“ liegt nicht vor. Anders im Fall staatlicher Diskriminierung: Ein „breach of promises“ oder eine Verletzung „fiduciary duties“ liegt hier stets vor, da Fälle staatlicher Diskriminierung regelmäßig Machtmissbrauch darstellen: Der Inhaber staatlicher Gewalt verletzt die Treuepflicht, das Mandat unparteilich auszuüben, das getreulich auszuführen er gelobt hat. Diskriminierung erscheint also weniger als ein Problem der angewandten Ethik denn als eines der politischen Philosophie. (shrink)

If someone says, “You’ve stereotyped me,” we hear the statement as an accusation. One way to interpret the accusation is as follows: you haven’t seen or treated me as an individual. In this essay, I interpret and evaluate a theory of wrongful stereotyping inspired by this thought, which I call the failure-to-individualize theory of wrongful stereotyping. According to this theory, stereotyping is wrong if and only if it involves failing to treat persons as individuals. I argue that the theory—however one (...) interprets it—is inadequate. Either the theory will not reliably identify all cases of wrongful stereotyping or it will fail to adequately explain why they are wrong. I conclude that it does not follow that we must entirely jettison the objection that stereotyping fails to treat persons as individuals. What follows is only that the objection must play a more circumscribed role in a theory of when and why stereotyping is wrong. (shrink)

In April 1962, white segregationists paid money to African Americans agreeing to leave New Orleans. In 2010, the British National Party proposed paying non-white migrants money to leave the UK. Five years later, a landlord in New York paid African American tenants to vacate their apartments. This article considers when, if ever, it is morally permissible to pay minorities to leave. I argue that paying minorities to leave is demeaning towards recipients and so wrong. Although the payments are wrong, it (...) is not clear if they are impermissible, given the benefits for the recipients. I argue that payments are impermissible if at least one of two conditions are met: The payments demean or harm other members of society, or the payments are provided to recipients who have failed to consent to the payments. (shrink)

There are many objections to statistical discrimination in general and racial profiling in particular. One objection appeals to the idea that people have a right to be treated as individuals. Statistical discrimination violates this right because, presumably, it involves treating people simply on the basis of statistical facts about groups to which they belong while ignoring non-statistical evidence about them. While there is something to this objection—there are objectionable ways of treating others that seem aptly described as failing to treat (...) them as individuals—it needs to be articulated carefully. First, most people accept that many forms of statistical discrimination are morally unproblematic, let alone morally justified all things considered. Second, even treating people on the basis of putative non-statistical evidence relies on generalizations. Once we construe treating someone as an individual in a way that respects this fact, it becomes apparent: (1) that statistical discrimination is compatible with treating people as individuals, and (2) that one may fail to treat people as individuals even without engaging in statistical discrimination. Finally, there are situations involving the expression of messages of inclusion where we think it is good, morally speaking, that we are not treated as individuals. (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)

Increasing empirical research on productivity supports the use of statistical or ‘rational’ discrimination in hiring. The practice is legal for features of job applicants not covered by human rights discrimination laws, such as being a smoker, residing in a particular neighbourhood or being a particular height. The practice appears largely morally innocuous under existing philosophical accounts of wrongful discrimination. This paper argues that lawful statistical discrimination treats job applicants in a way that may be considered degrading, and is likely to (...) constrain people’s freedoms in relation to employment, thus giving us reason for moral concern. (shrink)

In this article I critically examine a standard feature in conceptions of discrimination: the group-criterion, specifically the idea that there is a limited and definablegroup of traits that can form the basis of discrimination. I review two types of argument for the criterion. One focuses on inherently relevant groups and relies ultimately on luck-egalitarian principles; the other focuses on contextually relevant groups and relies ultimately on the badness of outcomes. I conclude that as neither type of argument is convincing, the (...) criterion is morally arbitrary, and as such untenable. Finally, I suggest both some of the conceptual and some of the practical implications of abandoning the criterion. (shrink)

Discrimination might be considered unjust on account of the comparative disadvantage it imposes, the absolute disadvantage it imposes, the disrespect it shows, or the prejudice it shows. This article argues that each of these accounts overlooks some cases of unjust discrimination. In response to this state of affairs we might combine two or more of these accounts. A promising approach combines the comparative disadvantage and absolute disadvantage accounts.

Liberal egalitarianism is commonly criticized for being insufficiently sensitive to status inequalities and the effects of misrecognition. I examine this criticism as it applies to Ronald Dworkin’s ‘equality of resources’ and argue that, in fact, liberal egalitarians possess the resources to deal effectively with recognition-type issues. More precisely, while conceding that the distributive principles required to realize equality of resources must apply against a particular institutional background, I point out, following Dworkin, that among the principles guiding this background is a (...) ‘principle of independence,’ and that this principle, properly interpreted, requires government to protect people against the disadvantageous effects of wrongful prejudicial discrimination. Moreover, I give an account of wrongful prejudice which is grounded in a particular interpretation of the abstract egalitarian principle Dworkin requires for a government to be legitimate and which goes a long way toward acknowledging status inequalities. Finally, I suggest other resources within the theory for responding to residual problems of recognition not addressed by the principle of independence. (shrink)

When is it permissible to allow a newborn infant to die on the basis of their future quality of life? The prevailing official view is that treatment may be withdrawn only if the burdens in an infant's future life outweigh the benefits. In this paper I outline and defend an alternative view. On the Threshold View, treatment may be withdrawn from infants if their future well-being is below a threshold that is close to, but above the zero-point of well-being. I (...) present four arguments in favor of the Threshold View, and identify and respond to several counterarguments. I conclude that it is justifiable in some circumstances for parents and doctors to decide to allow an infant to die even though the infant's life would be worth living. The Threshold View provides a justification for treatment decisions that is more consistent, more robust, and potentially more practical than the standard view. (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)

People often discriminate based on negative or positive stereotypes about others. Important examples of this are highlighted by the theory of ambivalent sexism. This theory distinguishes sexist stereotypes that are negative (hostile sexism) from those that are positive (benevolent sexism). While both forms of sexism are considered wrong towards women, hostile sexism seems intuitively worse than benevolent sexism. In this article, we ask whether the difference between discriminating based on positive vs. negative stereotypes in itself makes a morally relevant difference. (...) We suggest that it does not. By examining a number of prominent accounts of what makes discrimination wrong, we defend the Moral Irrelevance View according to which stereotype valence is irrelevant to the moral evaluation of discrimination, all else equal. (shrink)

In this paper we make the case for the emergence of novel kind of bias with the use of algorithmic decision-making systems. We argue that the distinctive generative process of feature creation, characteristic of machine learning (ML), contorts feature parameters in ways that can lead to emerging feature spaces that encode novel algorithmic bias involving already marginalized groups. We term this bias _assembled bias._ Moreover, assembled biases are distinct from the much-discussed algorithmic bias, both in source (training data versus feature (...) creation) and in content (mimics of extant societal bias versus reconfigured categories). As such, this problem is distinct from issues arising from bias-encoding training feature sets or proxy features. Assembled bias is not epistemically transparent in source or content. Hence, when these ML models are used as a basis for decision-making in social contexts, algorithmic fairness concerns are compounded. (shrink)

This article shows that we can identify a subset of religious and cultural accommodation cases that follow the structure of a particular disability model: the Human Variation Model. According to this model, disadvantageous disability arises because most social arrangements are tailored to the needs of individuals with typical characteristics; people with atypical features are frequently left out from these arrangements. Hence, the latter need personalised resources tailored to them, or their social and/or material environment ought to change according to their (...) atypical characteristics. I argue, however, that not everyone's claim stemming from an atypical characteristic merits accommodation – it would be simply unreasonable to provide personalised resources to everyone or modify the environment to accommodate everyone's needs. In other words, these human variation claimants must be ‘reasonably accommodated’. Nevertheless, members of certain social groups have a justifiable claim to receive such accommodation and those in religious and cultural groups could be among them for two specific sociological reasons. (shrink)

Discrimination is a central moral and legal concept. However, it is also a contested one. Particularly, accounts of the wrongness of discrimination often rely on controversial and particular assumptions. In this paper, I argue that a theory of discrimination that relies on premises that are very general (rather than unique to the concept of discrimination) and widely accepted provides a plausible (exhaustive) account of the concept of wrongful discrimination. According to the combined theory, wrongful discrimination consists of allocating a benefit (...) that is not supported by a morally significant fact (a valid reason), or in a way that involves distributive injustice, or both. (shrink)

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 claim that the ideal of equality has a role to play in the critique of discrimination in employment and education has been rejected by a number of philosophers. Certain anti-egalitarians argue that the appeal to equality is redundant; others that egalitarianism misdirects us or fails to explain our special hostility towards discrimination. This article sketches an egalitarian conception of justice in selection and explains what is distinctive about such conceptions. Thereafter, it attempts to rebut the important objections that have (...) been raised against egalitarian accounts of discrimination. (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)

In standard cases of discrimination the interests of the discriminatees are considered comparatively worse than those of others. Accordingly, discrimination is often defined as some form of differential consideration or treatment which, among other features, entails a disadvantage for discriminatees. There are some apparent forms of nonstandard discrimination, however, in which it seems that this need not occur. This paper examines three of them: epistemic discrimination, discrimination against entities unable to be harmed by it and nonhierarchical segregation. If, as it (...) seems, these really are forms of discrimination that means standard definitions may fail or must be reinterpreted. There is a way to account for the mentioned nonstandard forms of discrimination by claiming that all forms of worse consideration or treatment can be considered discriminatory. This, however, entails interpreting the term “worse” in a very broad manner, and some may not find this solution intuitive. Despite this, the paper will argue that alternative accounts entail more serious problems. (shrink)