How do we acquire moral obligations to others? The most straightforward cases are those where we acquire obligations as the result of particular actions which we voluntarily perform. If I promise you that I will trim your hedge, I face a moral Obligation to uphold my promise, and in the absence of some morally significant countervailing reason, I should indeed cut your hedge. Moral obligations which arise as a result of wrongdoing, as a function of corrective justice, are typically thought (...) to be of a similar nature. (shrink)

Journal of Political Philosophy, Volume 30, Issue 3, Page 395-408, September 2022.

Predictive algorithms are playing an increasingly prominent role in society, being used to predict recidivism, loan repayment, job performance, and so on. With this increasing influence has come an increasing concern with the ways in which they might be unfair or biased against individuals in virtue of their race, gender, or, more generally, their group membership. Many purported criteria of algorithmic fairness concern statistical relationships between the algorithm’s predictions and the actual outcomes, for instance requiring that the rate of false (...) positives be equal across the relevant groups. We might seek to ensure that algorithms satisfy all of these purported fairness criteria. But a series of impossibility results shows that this is impossible, unless base rates are equal across the relevant groups. What are we to make of these pessimistic results? I argue that none of the purported criteria, except for a calibration criterion, are necessary conditions for fairness, on the grounds that they can all be simultaneously violated by a manifestly fair and uniquely optimal predictive algorithm, even when base rates are equal. I conclude with some general reflections on algorithmic fairness. (shrink)

To address the rising concern that algorithmic decision-making may reinforce discriminatory biases, researchers have proposed many notions of fairness and corresponding mathematical formalizations. Each of these notions is often presented as a one-size-fits-all, absolute condition; however, in reality, the practical and ethical trade-offs are unavoidable and more complex. We introduce a new approach that considers fairness—not as a binary, absolute mathematical condition—but rather, as a relational notion in comparison to alternative decisionmaking processes. Using US mortgage lending as an example use (...) case, we discuss the ethical foundations of each definition of fairness and demonstrate that our proposed methodology more closely captures the ethical trade-offs of the decision-maker, as well as forcing a more explicit representation of which values and objectives are prioritised. (shrink)

Often machine learning programs inherit social patterns reflected in their training data without any directed effort by programmers to include such biases. Computer scientists call this algorithmic bias. This paper explores the relationship between machine bias and human cognitive bias. In it, I argue similarities between algorithmic and cognitive biases indicate a disconcerting sense in which sources of bias emerge out of seemingly innocuous patterns of information processing. The emergent nature of this bias obscures the existence of the bias itself, (...) making it difficult to identify, mitigate, or evaluate using standard resources in epistemology and ethics. I demonstrate these points in the case of mitigation techniques by presenting what I call ‘the Proxy Problem’. One reason biases resist revision is that they rely on proxy attributes, seemingly innocuous attributes that correlate with socially-sensitive attributes, serving as proxies for the socially-sensitive attributes themselves. I argue that in both human and algorithmic domains, this problem presents a common dilemma for mitigation: attempts to discourage reliance on proxy attributes risk a tradeoff with judgement accuracy. This problem, I contend, admits of no purely algorithmic solution. (shrink)

According to the Beneficiary Pays Principle, innocent beneficiaries of an injustice stand in a special moral relationship with the victims of the same injustice. Critics have argued that it is normatively irrelevant that a beneficiary and a victim are connected in virtue of the same unjust 'source'. The aim of this paper is to defend the Beneficiary Pays Principle against this criticism. Locating the principle against the backdrop of corrective justice, it argues that the principle is correct in saying that (...) innocent beneficiaries of an injustice may have an extra reason to assist the victims of that injustice. This is because it may be necessary to defeat the immoral plan of the perpetrator of the injustice and because it may satisfy weak restitution. The conclusion is that the principle is distinctive from related views, such as that property should be returned to its rightful owner or that tainted benefits should be given up for general use. (shrink)

This chapter outlines the main ideas of my book National responsibility and global justice. It begins with two widely held but conflicting intuitions about what global justice might mean on the one hand, and what it means to be a member of a national community on the other. The first intuition tells us that global inequalities of the magnitude that currently exist are radically unjust, while the second intuition tells us that inequalities are both unavoidable and fair once national responsibility (...) is allowed to operate. This conflict might be resolved either by adopting a cosmopolitan theory of justice (which leaves no room for national responsibility) or by adopting a ‘political’ theory of justice (which denies that questions of distributive justice can arise beyond the walls of the sovereign state). Since neither resolution is satisfactory, the chapter defends the idea of national responsibility and proposes a new theory of global justice, whose main elements are the protection of basic human rights worldwide, and fair terms of interaction between independent political communities. (shrink)

It is common to focus on the duties of the wrongdoer in cases that involve injustice. Presumably, the wrongdoer owes her victim an apology for having wronged her and perhaps compensation for having harmed her. But, these are not the only duties that may arise. Are other beneficiaries of an injustice permitted to retain the fruits of the injustice? If not, who becomes entitled to those funds? In recent years, the Connection Account has emerged as an influential account that purports (...) to explain cases such as Embezzlement. This account holds that benefiting from injustice can give rise to a corrective duty - that is, a duty of compensation - owed specifically to the victim of the injustice from which the recipient benefits. This duty is grounded in the connection between the victim and the beneficiary of a given injustice. This paper has two aims. First, I show that we must reject the Connection Account on the grounds that it risks failing correctly to identify those who become entitled to the fruits of injustice. I achieve this by developing and defending the fairness objection. Second, I offer an alternative account: the Moral Taintedness Account. This account states that, when identifying who is entitled to the fruits of injustice, the cause and the degree of the harm suffered by a victim are both relevant considerations, though it does not matter whether the victim is the victim of the injustice that gave rise to the fruits in question. This account avoids the problem associated with the Connection Account, and yields intuitive conclusions in an important range of test cases. (shrink)

The most blatant forms of discrimination are morally outrageous and very obviously so; but the nature and boundaries of discrimination are more controversial, and it is not clear whether all forms of discrimination are morally bad; nor is it clear why objectionable cases of discrimination are bad. In this paper I address these issues. First, I offer a taxonomy of discrimination. I then argue that discrimination is bad, when it is, because it harms people. Finally, I criticize a rival, disrespect-based (...) account according to which discrimination is bad regardless of whether it causes harm. (shrink)

Here, we provide an ethical analysis of discrimination in private insurance to guide the application of non-discriminatory algorithms for risk prediction in the insurance context. This addresses the need for ethical guidance of data-science experts, business managers, and regulators, proposing a framework of moral reasoning behind the choice of fairness goals for prediction-based decisions in the insurance domain. The reference to private insurance as a business practice is essential in our approach, because the consequences of discrimination and predictive inaccuracy in (...) underwriting are different from those of using predictive algorithms in other sectors. Here we focus on the trade-off in the extent to which one can pursue indirect non-discrimination versus predictive accuracy. The moral assessment of this trade-off is related to the context of application—to the consequences of inaccurate risk predictions in the insurance domain. (shrink)

This paper tries to explain why racial profiling involves a serious injustice and to do so in a way that avoids the problems of existing philosophical accounts. An initially plausible view maintains that racial profiling is pro tanto wrong in and of itself by violating a constraint on fair treatment that is generally violated by acts of statistical discrimination based on ascribed characteristics. However, consideration of other cases involving statistical discrimination suggests that violating a constraint of this kind may not (...) be an especially serious wrong in and of itself. To fully capture the significant wrong that occurs when racial profiling is targeted at black Americans or other similarly situated groups, it is argued that we should appeal to the idea that this basic injustice is exacerbated when it forms part of a larger pattern of similar actions that collectively realize a state of cumulative injustice. (shrink)

Many moral and political theorists have recently argued that the fact that an agent has innocently benefited from wrongdoing or injustice can ground special moral duties to help out the victims or simply give up the benefits. This idea is often referred to as the ‘Beneficiary Pays Principle’. This article critically assesses three recent attempts at providing a rationale for the BPP and argues that there are profound problems with each of them. It argues that even if we accept plausible (...) versions of the different normative ideas these accounts appeal to, we have no reason to accept the BPP. (shrink)

The Belief‐Desire model (the B‐D model) of reasons for action has been subject to much criticism lately. Two of the most elaborate and trenchant expositions of such criticisms are found in recent works by Jonathan Dancy (2000) and Fred Stoutland (2002). In this paper we set out to respond to the central pieces of their criticisms. For this purpose it is essential to sort out and regiment different senses in which the term ‘reason’ may be used. It is necessary to (...) go beyond common philosophical practice and distinguish not merely between two such different uses but to make a tripartite distinction. Our aim is largely conciliatory: we grant the main parts of the points made by Stoutland and Dancy but argue that once the B‐D model has been properly stated, and different uses of the term ‘reason’ sufficiently regimented, the B‐D proponent is able to accommodate their respective criticisms within the framework of the B‐D model and thereby undermine their case against the model. (shrink)

Journal of Political Philosophy, Volume 30, Issue 3, Page 395-408, September 2022.