Randomization procedures are used in legal and statistical applications, aiming to shield important decisions from spurious influences. This article gives an intuitive introduction to randomization and examines some intended consequences of its use related to truthful statistical inference and fair legal judgment. This article also presents an open-code Java implementation for a cryptographically secure, statistically reliable, transparent, traceable, and fully auditable randomization tool.

Government agencies and nonprofit organizations have increasingly turned to randomized controlled trials (RCTs) to evaluate public policy interventions. Random assignment is widely understood to be fair when there is equipoise; however, some scholars and practitioners argue that random assignment is also permissible when an intervention is reasonably expected to be superior to other trial arms. For example, some argue that random assignment to such an intervention is fair when the intervention is scarce, for it is sometimes fair (...) to use a lottery to allocate scarce goods. We investigate the permissibility of randomization in public policy RCTs when there is no equipoise, identifying two sets of conditions under which it is fair to allocate access to a superior intervention via random assignment. We also reject oft-made claims that alternative study designs, including stepped-wedge designs and uneven randomization, offer fair ways to allocate beneficial interventions. (shrink)

Randomization is an integral part of well-designed statistical trials, and is also a required procedure in legal systems. Implementation of honest, unbiased, understandable, secure, traceable, auditable and collusion resistant randomization procedures is a mater of great legal, social and political importance. Given the juridical and social importance of randomization, it is important to develop procedures in full compliance with the following desiderata: (a) Statistical soundness and computational efficiency; (b) Procedural, cryptographical and computational security; (c) Complete auditability and (...) traceability; (d) Any attempt by participating parties or coalitions to spuriously influence the procedure should be either unsuccessful or be detected; (e) Open-source programming; (f) Multiple hardware platform and operating system implementation; (g) User friendliness and transparency; (h) Flexibility and adaptability for the needs and requirements of multiple application areas (like, for example, clinical trials, selection of jury or judges in legal proceedings, and draft lotteries). This paper presents a simple and easy to implement randomization protocol that assures, in a formal mathematical setting, full compliance to the aforementioned desiderata for randomization procedures. (shrink)

In this article I explore two accounts of the Fallacy of Many Questions made famous by the question "Have you stopped beating your wife?" The accounts are from the works of Lennart Aqvist and Noel Belnap, and the two authors differ in their accounts of the fallacy. Then I give my own account based on understanding a facet of erotetic logic, i. e., the logic of questions.

Three recent research reports by Topping and Trickey, by Fair and colleagues, and by Gorard, Siddiqui and Huat See have produced data that support the conclusion that a Philosophy for Children program of one-hour-per-week structured discussions has a marked positive impact on students. This article presents data from a follow up study done three years after the completion of the study reported in Fair et al.. The data show that the positive gains in scores on the Cognitive Abilities (...) Test were still present and had not faded after three years. Given the strength of these confirmations of the positive durable impact of the P4C program of structured discussions and given the relatively low cost of implementing the P4C program, it is recommended that it become a standard part of the school curriculum. (shrink)

The principal goal of Alex John London's For the Common Good is to "articulate a new vision for the philosophical foundations of research ethics" which "moves issues of justice from the periphery of the field to the very center." At the core of this new vision is an understanding of research as a "collaborative social activity between free and equal persons," which aims to develop the knowledge public institutions require to establish and maintain a social order in which people may (...) set and pursue their plans of life. Clinical and social scientific research are not therefore morally optional activities, in London's view, but rather the way public institutions acquire the knowledge they... (shrink)

Did the impartiality of clinical trials play any role in their acceptance as regulatory standards for the safety and efficacy of drugs? According to the standard account of early British trials in the 1930s and 1940s, their impartiality was just rhetorical: the public demanded fair tests and statistical devices such as randomization created an appearance of neutrality. In fact, the design of the experiment was difficult to understand and the British authorities took advantage of it to promote their (...) own particular interests. I claim that this account is based on a poorly defined concept of experimental fairness . I present an alternative approach in which a test would be impartial if it incorporates warrants of non-manipulability. With this concept, I reconstruct the history of British trials showing that they were indeed fair and this fairness played a role in their acceptance as regulatory yardsticks. (shrink)

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered (...) a variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

Decoupling is a general principle that allows us to separate simple components in a complex system. In statistics, decoupling is often expressed as independence, no association, or zero covariance relations. These relations are sharp statistical hypotheses, that can be tested using the FBST - Full Bayesian Significance Test. Decoupling relations can also be introduced by some techniques of Design of Statistical Experiments, DSEs, like randomization. This article discusses the concepts of decoupling, randomization and sparsely connected statistical models in (...) the epistemological framework of cognitive constructivism. (shrink)

This article presents a fairness principle for evaluating decision-making based on predictions: a decision rule is unfair when the individuals directly impacted by the decisions who are equal with respect to the features that justify inequalities in outcomes do not have the same statistical prospects of being benefited or harmed by them, irrespective of their socially salient morally arbitrary traits. The principle can be used to evaluate prediction-based decision-making from the point of view of a wide range of antecedently specified (...) substantive views about justice in outcome distributions. (shrink)

Some moral principles require agents to do more than their fair share of a common task, if others won’t do their fair share – each agent’s fair share being what they would be required to do if all contributed as they should. This seems to provide a strong basis for objecting to such principles. For it seems unfair to require agents who have already done their fair share to do more, just because other agents won’t do (...) their fair share. The philosopher who has written most about this issue, however, Liam Murphy, argues that it is not unfair to do so, at least in the standard sense of that term. In this paper, I give Murphy’s reasons for saying this, explain why I think he’s wrong, and then say a little about why this issue might be important. (shrink)

t Intentional sampling methods are non-randomized procedures that select a group of individuals for a sample with the purpose of meeting specific prescribed criteria. In this paper we extend previous works related to intentional sampling, and address the problem of sequential allocation for clinical trials with few patients. Roughly speaking, patients are enrolled sequentially, according to the order in which they start the treatment at the clinic or hospital. The allocation problem consists in assigning each new patient to one, and (...) only one, of the alternative treatment arms. The main requisite is that the profiles in the alternative arms remain similar with respect to some relevant patients’ attributes (age, gender, disease, symptom severity and others). We perform numerical experiments based on a real case study and discuss how to conveniently set up perturbation parameters, in order to yield a suitable balance between optimality – the similarity among the relative frequencies of patients in the several categories for both arms, and decoupling – the absence of a tendency to allocate each pair of patients consistently to the same arm. (shrink)

Holm (2022) argues that a class of algorithmic fairness measures, that he refers to as the ‘performance parity criteria’, can be understood as applications of John Broome’s Fairness Principle. We argue that the performance parity criteria cannot be read this way. This is because in the relevant context, the Fairness Principle requires the equalization of actual individuals’ individual-level chances of obtaining some good (such as an accurate prediction from a predictive system), but the performance parity criteria do not guarantee any (...) such thing: the measures merely ensure that certain population-level ratios hold. (shrink)

John Broome has proposed a theory of fairness according to which fairness requires that agents’ claims to goods be satisfied in proportion to the relative strength of those claims. In the case of competing claims for a single indivisible good, Broome argues that what fairness requires is the use of a weighted lottery as a surrogate to satisfying the competing claims: the relative chance of each claimant's winning the lottery should be set to the relative strength of each claimant's claim. (...) In this journal, James Kirkpatrick and Nick Eastwood have objected that the use of weighted lotteries in the case of indivisible goods is unacceptable. In this article, I explain why Kirkpatrick and Eastwood's objection misses its mark. (shrink)

Governments are increasingly using randomized controlled trials (RCTs) to evaluate policy interventions. RCTs are often understood to provide the highest quality evidence regarding the causal efficacy of an intervention. While randomization plays an essential epistemic role in the context of policy RCTs however, it also plays an important distributive role. By randomly assigning participants to either the intervention or control arm of an RCT, people are subject to different policies and so, often, to different types and levels of benefits. (...) In this paper, I identify one necessary condition as well as a set of sufficient conditions for the permissible use of random assignment by government agencies. I argue first that random assignment is permissible only if it is consistent with governments’ duty to realize morally important outcomes. I argue second that random assignment is permissible in cases where investigators are in a state of genuine equipoise regarding all arms of the experiment and the policy to which people have a claim of justice. Finally, I defend a set of conditions under which random assignment is permissible in cases where one or more arms of a policy RCT are reasonably expected to be either superior or inferior to this policy. (shrink)

In his paper “Fairness, Political Obligation, and the Justificatory Gap” (published in the Journal of Moral Philosophy), Jiafeng Zhu argues that the principle of fair play cannot require submission to the rules of a cooperative scheme, and that when such submission is required, the requirement is grounded in consent. I propose a better argument for the claim that fair play requires submission to the rules than the one Zhu considers. I also argue that Zhu’s attribution of consent to (...) people commonly thought to be bound to follow the rules by a duty of fair play is implausible. (shrink)

This research investigates 3- and 5-year-olds' relative fairness in distributing small collections of even or odd numbers of more or less desirable candies, either with an adult experimenter or between two dolls. The authors compare more than 200 children from around the world, growing up in seven highly contrasted cultural and economic contexts, from rich and poor urban areas, to small-scale traditional and rural communities. Across cultures, young children tend to optimize their own gain, not showing many signs of self-sacrifice (...) or generosity. Already by 3 years of age, self-optimizing in distributive justice is based on perspective taking and rudiments of mind reading. By 5 years, overall, children tend to show more fairness in sharing. What varies across cultures is the magnitude of young children's self-interest. More fairness (less self-interest) in distributive justice is evident by children growing up in small-scale urban and traditional societies thought to promote more collective values. (shrink)

Typically, fair machine learning research focuses on a single decision maker and assumes that the underlying population is stationary. However, many of the critical domains motivating this work are characterized by competitive marketplaces with many decision makers. Realistically, we might expect only a subset of them to adopt any non-compulsory fairness-conscious policy, a situation that political philosophers call partial compliance. This possibility raises important questions: how does partial compliance and the consequent strategic behavior of decision subjects affect the allocation (...) outcomes? If k% of employers were to voluntarily adopt a fairness-promoting intervention, should we expect k% progress (in aggregate) towards the benefits of universal adoption, or will the dynamics of partial compliance wash out the hoped-for benefits? How might adopting a global (versus local) perspective impact the conclusions of an auditor? In this paper, we propose a simple model of an employment market, leveraging simulation as a tool to explore the impact of both interaction effects and incentive effects on outcomes and auditing metrics. Our key findings are that at equilibrium: (1) partial compliance by k% of employers can result in far less than proportional (k%) progress towards the full compliance outcomes; (2) the gap is more severe when fair employers match global (vs local) statistics; (3) choices of local vs global statistics can paint dramatically different pictures of the performance vis-a-vis fairness desiderata of compliant versus non-compliant employers; (4) partial compliance based on local parity measures can induce extreme segregation. Finally, we discuss implications for auditors and insights concerning the design of regulatory frameworks. (shrink)

This report by the WHO Consultative Group on Equity and Universal Health Coverage addresses how countries can make fair progress towards the goal of universal coverage. It explains the relevant tradeoffs between different desirable ends and offers guidance on how to make these tradeoffs.

This essay explores a conception of responsibility at work in moral and criminal responsibility. Our conception draws on work in the compatibilist tradition that focuses on the choices of agents who are reasons-responsive and work in criminal jurisprudence that understands responsibility in terms of the choices of agents who have capacities for practical reason and whose situation affords them the fair opportunity to avoid wrongdoing. Our conception brings together the dimensions of normative competence and situational control, and we factor (...) normative competence into cognitive and volitional capacities, which we treat as equally important to normative competence and responsibility. Normative competence and situational control can and should be understood as expressing a common concern that blame and punishment presuppose that the agent had a fair opportunity to avoid wrongdoing. This fair opportunity is the umbrella concept in our understanding of responsibility, one that explains it distinctive architecture. (shrink)

From the school yard to the workplace, there’s no charge more damning than “you’re being unfair!” Born out of democracy and raised in open markets, fairness has become our de facto modern creed. The very symbol of American ethics—Lady Justice—wears a blindfold as she weighs the law on her impartial scale. In our zealous pursuit of fairness, we have banished our urges to like one person more than another, one thing over another, hiding them away as dirty secrets of our (...) humanity. In Against Fairness, polymath philosopher Stephen T. Asma drags them triumphantly back into the light. Through playful, witty, but always serious arguments and examples, he vindicates our unspoken and undeniable instinct to favor, making the case that we would all be better off if we showed our unfair tendencies a little more kindness—indeed, if we favored favoritism. Conscious of the egalitarian feathers his argument is sure to ruffle, Asma makes his point by synthesizing a startling array of scientific findings, historical philosophies, cultural practices, analytic arguments, and a variety of personal and literary narratives to give a remarkably nuanced and thorough understanding of how fairness and favoritism fit within our moral architecture. Examining everything from the survival-enhancing biochemistry that makes our mothers love us to the motivating properties of our “affective community,” he not only shows how we favor but the reasons we should. Drawing on thinkers from Confucius to Tocqueville to Nietzsche, he reveals how we have confused fairness with more noble traits, like compassion and open-mindedness. He dismantles a number of seemingly egalitarian pursuits, from classwide Valentine’s Day cards to civil rights, to reveal the envy that lies at their hearts, going on to prove that we can still be kind to strangers, have no prejudice, and fight for equal opportunity at the same time we reserve the best of what we can offer for those dearest to us. Fed up with the blue-ribbons-for-all absurdity of "fairness" today, and wary of the psychological paralysis it creates, Asma resets our moral compass with favoritism as its lodestar, providing a strikingly new and remarkably positive way to think through all our actions, big and small. (shrink)

This article discusses how the concept of a fair finite lottery can best be extended to denumerably infinite lotteries. Techniques and ideas from non-standard analysis are brought to bear on the problem.

If dangerous climate change is to be avoided, it is vital that carbon sinks such as tropical rainforests are protected. But protecting them has costs. These include opportunity costs: the potential economic benefits which those who currently control rainforests have to give up when they are protected. But who should bear those costs? Should countries which happen to have rainforests within their territories sacrifice their own economic development, because of our broader global interests in protecting key carbon sinks? This essay (...) develops an argument from the “principle of fairness,” which seeks to establish that outsiders should pay states with rainforests so as to share the costs of protection. If they do not, they can be condemned for free-riding on forest states. The argument is, I suggest, compelling and also capable of enjoying support from adherents of a wide variety of positions on global justice. (shrink)

The debate over whether ‘fair-play’ can serve as a justification for legal punishment has recently resumed with an exchange between Richard Dagger and Antony Duff. According to the fair-play theorist, criminals deserve punishment for breaking the law because in so doing the criminal upsets a fair distribution of benefits and burdens, and punishment rectifies this unfairness. Critics frequently level two charges against this idea. The first is that it often gives the wrong explanation of what makes crime (...) deserving of punishment, since the wrongfulness of murder is not primarily about unfairness. The second is that it implies that all crimes deserve the same degree of punishment, because all crimes create the same degree of unfairness. These objections are viewed as revealing fatal flaws in the theory. Although Dagger attempts to meet these objections by drawing on political theory, Duff responds that this still draws upon the wrong kind of resources for meeting these objections. This paper argues that these two objections rest on a crucial mistake that has been overlooked by both the defenders and critics of fair-play. This mistake results from failing to distinguish between what justifies punishment as a response to crime (which requires a common element to all crime) and what justifies attaching particular penalties to crimes (which requires making distinctions in the severity of crime). The arguments presented will give reasons to consider fair-play as a viable justification for legal punishment. (shrink)

Among the most popular strategies for justifying political obligations are those that appeal to the principle of fairness. These theories face the challenge, canonically articulated by Robert Nozick, of explaining how it is that persons are obligated to schemes when they receive goods that they do not ask for but cannot reject. John Simmons offers one defense of the principle of fairness, arguing that people could be bound by obligations of fairness if they voluntarily accept goods produced by a cooperative (...) scheme. Simmons, however, thinks that such a theory will do little work in justifying political obligations, since virtually no one voluntarily accepts state goods. This paper attempts to advance just such a theory by arguing that states are in fact genuine cooperative schemes and that Simmons is overly pessimistic in his appraisal of whether the majority of citizens accept the goods provided by their states. (shrink)

Severe poverty is a major global problem about risk and inequality. What, if any, is the relationship between equality, fairness and responsibility in an unequal world? I argue for four conclusions. The first is the moral urgency of severe poverty. We have too many global neighbours that exist in a state of emergency and whose suffering is intolerable. The second is that severe poverty is a problem concerning global injustice that is relevant, but not restricted, to questions about responsibility. If (...) none were responsible, this does not eliminate all compelling claims to provide assistance. The third is that severe poverty represents an inequality too far; it is a condition of extremity with denial of basic needs. The fourth is that there is a need for an approach that captures all relevant cases – and the capabilities approach and the connection theory of remedial responsibilities are highlighted as having special promise. (shrink)

Although existing work draws attention to a range of obstacles in realizing fair AI, the field lacks an account that emphasizes how these worries hang together in a systematic way. Furthermore, a review of the fair AI and philosophical literature demonstrates the unsuitability of ‘treat like cases alike’ and other intuitive notions as conceptions of fairness. That review then generates three desiderata for a replacement conception of fairness valuable to AI research: (1) It must provide a meta-theory for (...) understanding tradeoffs, entailing that it must be flexible enough to capture diverse species of objection to decisions. (2) It must not appeal to an impartial perspective (neutral data, objective data, or final arbiter.) (3) It must foreground the way in which judgments of fairness are sensitive to context, i.e., to historical and institutional states of affairs. We argue that a conception of fairness as appropriate concession in the historical iteration of institutional decisions meets these three desiderata. On the basis of this definition, we organize the insights of commentators into a process-structure map of the ethical territory that we hope will bring clarity to computer scientists and ethicists analyzing Fair AI while clearing some ground for further technical and philosophical work. (shrink)

Rawlsian justice as fairness is neither fundamentally luck egalitarian nor relational egalitarian. Rather, the most fundamental idea is that of society as a fair system of cooperation. Collective pensions provide a case study which illustrates the fruitfulness of conceiving justice in these latter terms. Those who have recently reached the age of majority do not now know how long they will live in retirement or how well any investments they try to save up for their retirement would fare. From (...) the perspective of the beginning of their working lives, it is therefore rational for each to enter into an agreement with others, who also do not yet know their fates, that, if one turns out to be among the unfortunate whose private pension pots would not have yielded enough for one’s retirement, one will receive much more in retirement, whereas those whose pension pots would have overflowed their retirements will receive somewhat less. These terms are to each person’s expected advantage, which is made possible by a fair sharing of the fruits of social cooperation which arise through the efficiencies reaped by the pooling of the risk of outliving what one could save for one’s retirement on one’s own. It is rational for each to agree to share one another’s fates by pooling risks across both space and time, on fair terms of social cooperation for mutual advantage. Even when collective pensions arise from, and are proportional to, a baseline of unequal income, they can be defended on grounds of reciprocity involving regard for one another as equals. (shrink)

There is an emerging consensus among political philosophers that state legitimacy involves something more than—or perhaps other than—political obligation. Yet the principle of fair play, which many take to be a promising basis for political obligation, has been largely absent from discussions of the revised conception of legitimacy. This paper shows how the principle of fair play can generate legitimate political authority by drawing on a neglected feature of the principle—its stipulation that members of a cooperative scheme must (...) reciprocate specifically by submitting to the scheme's rules. (shrink)

Distribution of responsibility is one of the main focus areas in discussions about climate change ethics. Most of these discussions deal with the distribution of responsibility for climate change mitigation at the international level. The aim of this paper is to investigate if and how these principles can be used to inform the search for a fair distribution of responsibility for climate change adaptation on the local level. We found that the most influential distribution principles on the international level (...) were in turn built on one or more of seven basic principles: (P1) equal shares, (P2) desert, (P3) beneficiary pays, (P4) ability, (P5) self-help, (P6) limited responsibility for the worst off, and (P7) status quo preservation. It was found that all the basic principles, but P1, P3, and P7, are to some extent translatable to local climate adaptation. Two major problems hamper their usefulness on the local level: (1) several categories of agents need to take on responsibility; and (2) emissions do not work as a base for all principles. P4, P5, and P6 are applicable to local adaptation without changes. P4 is of particular importance as it seems to solve the first problem. P2 is applicable only if the second problem is solved, which can be achieved by using risk of harm instead of emissions as the basis for desert. (shrink)

Universal health coverage (UHC) is at the center of current efforts to strengthen health systems and improve the level and distribution of health and health services. This document is the final report of the WHO Consultative Group on Equity and Universal Health Coverage. The report addresses the key issues of fairness and equity that arise on the path to UHC. As such, the report is relevant for every actor that affects that path and governments in particular, as they are in (...) charge of overseeing and guiding the progress toward UHC. (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)

Several philosophers who argue that forgiveness is an important virtue also wish to maintain the moral value of retributive emotions that forgiveness is meant to overcome. As such, these accounts explicate forgiveness as an Aristotelian mean between too much resentment and too little resentment. I argue that such an account ends up making forgiveness superfluous: it turns out that the forgiving person is not praised for a greater willingness to let go of her resentment, but rather for her fairness or (...) good judgment. I conclude by arguing that the virtue of fair-mindedness is more compatible with maintaining the value of the retributive emotions than the virtue of forgiveness. (shrink)

Although the principle of fair subject selection is a widely recognized requirement of ethical clinical research, it often yields conflicting imperatives, thus raising major ethical dilemmas regarding participant selection. In this paper, we diagnose the source of this problem, arguing that the principle of fair subject selection is best understood as a bundle of four distinct sub-principles, each with normative force and each yielding distinct imperatives: (1) fair inclusion; (2) fair burden sharing; (3) fair opportunity; (...) and (4) fair distribution of third-party risks. We first map out these distinct sub-principles, and then identify the ways in which they yield conflicting imperatives for the design of inclusion and exclusion criteria, and the recruitment of participants. We then offer guidance for how decision makers should navigate these conflicting imperatives to ensure that participants are selected fairly. (shrink)

Garrett Cullity contends that fairness is appropriate impartiality (See Cullity (2004) Chapters 8 and 10 and Cullity (2008)). Cullity deploys his account of fairness as a means of limiting the extreme moral demand to make sacrifices in order to aid others that was posed by Peter Singer in his seminal article ‘Famine, Affluence and Morality’. My paper is founded upon the combination of (1) the observation that the idea that fairness consists in appropriate impartiality is very vague and (2) the (...) fact that psychological studies show the self-serving bias is especially likely to infect one’s judgements when the ideas involved are vague. I argue that Cullity’s solution to extreme moral demandingness is threatened by these findings. I then comment on whether some other theories of fairness are vulnerable to the same objection. (shrink)

Social movements often impose nontrivial costs on others against their wills. Civil disobedience is no exception. How can social movements in general, and civil disobedience in particular, be justifiable despite this apparent wrong-making feature? We examine an intuitively plausible account—it is fair that everyone should bear the burdens of tackling injustice. We extend this fairness-based argument for civil disobedience to defend some acts of uncivil disobedience. Focusing on uncivil environmental activism—such as ecotage (sabotage with the aim of protecting the (...) environment)—we argue that some acts of uncivil disobedience can be morally superior to their civil counterparts, when and because such acts target people who are responsible for environmental threats. Indeed, insofar as some acts of uncivil disobedience can more accurately target responsible people, they can better satisfy the demands of fairness compared to their civil counterparts. In some circumstances, our argument may require activists to engage in uncivil disobedienceeven whencivil disobedience is available. (shrink)

Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While researchers have (...) taken the problem of algorithmic bias seriously, but the current discussion on algorithmic fairness tends to conceptualize ‘fairness’ in algorithmic fairness primarily as a technical issue and attempts to implement pre-existing ideas of ‘fairness’ into algorithms. In this paper, I show that such a view of algorithmic fairness as technical issue is unsatisfactory for the type of problem algorithmic fairness presents. Since decisions on fairness measure and the related techniques for algorithms essentially involve choices between competing values, ‘fairness’ in algorithmic fairness should be conceptualized first and foremost as a political issue, and it should be (re)solved by democratic communication. The aim of this paper, therefore, is to explicitly reconceptualize algorithmic fairness as a political question and suggest the current discussion of algorithmic fairness can be strengthened by adopting the accountability for reasonableness framework. (shrink)

In a paper recently published in this journal, Navin and Largent argue in favour of a type of policy to regulate non-medical exemptions from childhood vaccination which they call ‘Inconvenience’. This policy makes it burdensome for parents to obtain an exemption to child vaccination, for example, by requiring parents to attend immunization education sessions and to complete an application form to receive a waiver. Navin and Largent argue that this policy is preferable to ‘Eliminationism’, i.e. to policies that do not (...) allow non-medical exemptions, because Inconvenience has been shown to maintain exemption rates low while not harming parents by forcing them to do something that goes against their beliefs. We argue that it is at least doubtful that Inconvenience is ethically preferable to Eliminationism: while the latter disregards the value of liberty, Inconvenience disregards the value of fairness in the distribution of the burdens entailed by the preservation of a public good like herd immunity. We propose a variant of Inconvenience, which we call ‘Contribution’, which we think is preferable to the versions of Inconvenience discussed by Navin and Largent in that it successfully strikes a balance between the values of parents’ liberty, fairness and expected utility. (shrink)

This chapter argues that governments have a duty to take reasonably effective and humane steps to minimize the occurrence of unauthorized migration and stay. While the effects of unauthorized migration on a country’s citizens and institutions have been vigorously debated, the literature has largely ignored duties of fairness to would-be immigrants. It is argued here that failing to take reasonable steps to prevent unauthorized migration and stay is deeply unfair to would-be immigrants who are not in a position to bypass (...) visa regulations. Importantly, the argument here is orthogonal to the debate as to how much and what kinds of immigration ought to be allowed. (shrink)

Every year, hundreds of patients in England die whilst waiting for a kidney transplant, and this is evidence that the current system of altruistic-based donation is not sufficient to address the shortage of kidneys available for transplant. To address this problem, we propose a monopsony system whereby kidney donors can opt-in to receive financial compensation, whilst still preserving the right of individuals to donate without receiving any compensation. A monopsony system describes a market structure where there is only one ‘buyer’—in (...) this case the National Health Service. By doing so, several hundred lives could be saved each year in England, wait times for a kidney transplant could be significantly reduced, and it would lessen the burden on dialysis services. Furthermore, compensation would help alleviate the common disincentives to living kidney donation, such as its potential associated health and psychological costs, and it would also help to increase awareness of living kidney donation. The proposed system would also result in significant cost savings that could then be redirected towards preventing kidney disease and reducing health disparities. While concerns about exploitation, coercion, and the ‘crowding out’ of altruistic donors exist, we believe that careful implementation can mitigate these issues. Therefore, we recommend piloting financial compensation for living kidney donors at a transplant centre in England. (shrink)

Greg Bognar has recently offered a prioritarian justification for ‘fair innings’ distributive principles that would ration access to healthcare on the basis of patients' age. In this article, I agree that Bognar's principle is among the strongest arguments for age-based rationing. However, I argue that this position is incomplete because of the possibility of ‘time-relative' egalitarian principles that could complement the kind of lifetime egalitarianism that Bognar adopts. After outlining Bognar's position, and explaining the attraction of time-relative egalitarianism, I (...) suggest various ways in which these two kinds of principle could interact. Since various options have very different implications for age-based rationing, proponents of such a rationing scheme must take a position on time-relative egalitarianism to complement a lifetime prioritarian view like Bognar's. (shrink)

Data-driven predictive algorithms are widely used to automate and guide high-stake decision making such as bail and parole recommendation, medical resource distribution, and mortgage allocation. Nevertheless, harmful outcomes biased against vulnerable groups have been reported. The growing research field known as 'algorithmic fairness' aims to mitigate these harmful biases. Its primary methodology consists in proposing mathematical metrics to address the social harms resulting from an algorithm's biased outputs. The metrics are typically motivated by -- or substantively rooted in -- ideals (...) of distributive justice, as formulated by political and legal philosophers. The perspectives of feminist political philosophers on social justice, by contrast, have been largely neglected. Some feminist philosophers have criticized the local scope of the paradigm of distributive justice and have proposed corrective amendments to surmount its limitations. The present paper brings some key insights of feminist political philosophy to algorithmic fairness. The paper has three goals. First, I show that algorithmic fairness does not accommodate structural injustices in its current scope. Second, I defend the relevance of structural injustices -- as pioneered in the contemporary philosophical literature by Iris Marion Young -- to algorithmic fairness. Third, I take some steps in developing the paradigm of 'responsible algorithmic fairness' to correct for errors in the current scope and implementation of algorithmic fairness. I close by some reflections of directions for future research. (shrink)

The move from open outcry to electronic trading added another responsibility to futures exchanges—that of matching orders between buyers and sellers. Matching systems can affect the level and speed of price discovery, the distribution of revenue, as well as the level of price efficiency of a given market. Whether the matching system is procedurally fair is another important consideration. I argue that while FIFO (First In First Out) is a fair procedure in principle and is perceived as the (...) default matching system, it is not a fair procedure in practice. Likewise, while pro rata is a fair procedure in principle, it is not so in practice. Nevertheless, both FIFO and pro rata are relics of an open outcry system. Instead, I propose an alternative approach to matching systems that builds on the strengths of electronic trading—the ability to randomize in real time. I introduce random selection for service (RSS) as a matching system that is procedurally fair both in principle and in practice. (shrink)

This chapter provides a critical overview and interpretation of fair subject selection in clinical and social scientific research. It first provides an analytical framework for thinking about the problem of fair subject selection. It then argues that fair subject selection is best understood as a set of four subprinciples, each with normative force and each with distinct and often conflicting implications for the selection of participants: fair inclusion, fair burden sharing, fair opportunity, and (...) class='Hi'>fair distribution of third-party risks. It then defends an approach to navigating the conflicting imperatives of these subprinciples, one which privileges the need to include epistemically distinct groups in research, before concluding by considering the most pressing research questions regarding fair subject selection. (shrink)

In this essay, Johannes Giesinger comments on the current philosophical debate on educational justice. He observes that while authors like Elizabeth Anderson and Debra Satz develop a so-called adequacy view of educational justice, Harry Brighouse and Adam Swift defend an egalitarian principle. Giesinger focuses his analysis on the main objection that is formulated, from an egalitarian perspective, against the adequacy view: that it neglects the problem of securing fair opportunities in the competition for social rewards. Giesinger meets this objection (...) by expressing two basic theses: First, he argues that Brighouse and Swift themselves fail to give an adequate account of fair competition; and, second, he shows that the adequacy view provides the theoretical resources to face this problem. (shrink)

According to a common judgement, a social planner should often use a lottery to decide which of two people should receive a good. This judgement undermines one of the best-known arguments for utilitarianism, due to John C. Harsanyi, and more generally undermines axiomatic arguments for utilitarianism and similar views. In this paper we ask which combinations of views about (a) the social planner’s attitude to risk and inequality, and (b) the subjects’ attitudes to risk are consistent with the aforementioned judgement. (...) We find that the class of combinations of views that can plausibly accommodate this judgement is quite limited. But one theory does better than others: the theory of chance-sensitive utility. (shrink)

We offer a summary of the WHO Report "Making Fair Choices on the Path to Universal Health Coverage".