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)

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)

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)

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.

Recently, unrestrained consequentialism has been defended against the charge that it leads to unacceptable trade-offs by showing a tradeoff accepted by many of us is not justified by any of the usual nonconsequenlist arguments. The particular trade-off involves raising the speed limit on the Interstate Highway System. As a society, we seemingly accept a trade-off of lives for convenience. This defense of consequentialism may be a tu quoque, but it does challenge nonconsequentialists to adequately justify a multitude of social decisions. (...) Work by the deontologist Frances Kamm, conjoined with a perspective deployed by several economists on the relation between social costs and lives lost, is relevant. It provides a starting point by justifying decisions which involve trading lives only for other lives. But the perspective also recognizes that using resources in excess of some figure to save a life causes us to forego other live-saving activities, thus causing a net loss of life. Setting a speed limit as low as 35 miles per hour might indeed save some lives, but the loss of productivity due to the increased time spent in travel would cost an even greater number of lives. Therefore, many trade-offs do not simply involve trading lives for some lesser value, but are justified as allowing some to die in order to save a greater number. (shrink)

As I read Ben Hamby’s piece, I found it hard to disagree with what he was saying. Certainly the willingness to inquire strikes me as extremely important. If that willingness was completely absent in someone, I find it hard to imagine how that person could amount to much as a critical thinker. Still, the pleasant complacency of collegial agreement is itself a cue that perhaps should trigger greater exertion to think critically. So I will adopt a deliberately oppositional stance, one (...) that searches for flaws in the proposal that Ben is asking us to adopt. I will try to present a variety of provocations in this regard, and, if my efforts seem on occasion to be stretches, that’s OK so long as they stimulate further thinking—in this case further thinking about critical thinking and its pedagogy. (shrink)

This article is a response to J. J. Katz's chapter "The Logic of Questions" in Logic, Methodology, and Philosophy of Science III, Des. B. van Rootselaar and J. F. Staal, North Holland, Amsterdam, 1968. One of Katz's purposes was to "to provide a foundation for the logic of questions," and I argue that the stance Katz takes is both mistaken in itself, yet suggestive of a point that had not been touched on by his predecessors in their attempts to develop (...) the logic of questions. (shrink)

This is a review of a book by Belnap and Steel The Logic of Questions and Answers from Yale University Press (1976).

Statistical fairness criteria are widely used for diagnosing and ameliorating algorithmic bias. However, these fairness criteria are controversial as their use raises several difficult questions. I argue that the major problems for statistical algorithmic fairness criteria stem from an incorrect understanding of their nature. These criteria are primarily used for two purposes: first, evaluating AI systems for bias, and second constraining machine learning optimization problems in order to ameliorate such bias. The first purpose typically involves treating each (...) criterion as a necessary condition for fairness. The second use involves treating criteria as sufficient conditions for fairness. Since the criteria are used for both roles, some researchers have treated them as both necessary and sufficient conditions, i.e., as definitions of algorithmic fairness. However, serious problems have been raised for the use of these fairness criteria. Under ordinary circumstances, it is impossible to satisfy multiple criteria at the same time. Moreover, there are counterexamples to both the sufficiency and necessity for fairness of each criterion. I argue that we should instead understand fairness criteria as merely providing evidence of fairness. In other words, satisfaction (or violation) of these criteria should be understood as potential evidence of fairness (or bias). Whether a criterion counts as evidence in a particular case will depend on stakeholders' background knowledge and the specific features of the system's task. This evidence account of fairness conditions provides guidance for recognizing both the appropriate uses and the limitations of fairness criteria. (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)

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)

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)

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)

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)

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)

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.

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)

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)

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)

The main body of this paper assesses a leading recent theory of fairness, a theory put forward by John Broome. I discuss Broome's theory partly because of its prominence and partly because I think it points us in the right direction, even if it takes some missteps. In the course of discussing Broome's theory, I aim to cast light on the relation of fairness to consistency, equality, impartiality, desert, rights, and agreements. Indeed, before I start assessing Broome's theory, (...) I discuss two very popular conceptions of fairness that contrast with his. One of these very popular conceptions identifies fairness with the equal and impartial application of rules. The other identifies fairness with all-things-considered moral rightness. (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)

This paper introduces a new variant of a hop Roman dominating function in graphs called the fair hop Roman dominating function. Moreover, several important combinatorial properties and characterizations of fair hop Roman dominating functions in various graph classes were investigated.

According to a long philosophical tradition and a potent kernel of common sense, loving partnerships are governed by affection and care, and so not properly evaluated by standards of justice or fairness. In this paper I precisify and challenge this idea. I argue that love and fairness are unified in the sense that some partners are only able to perform particular act-types (loving and expressing love) if their actions are sensitive to considerations of fairness. When loving acts (...) are aimed at “sharing a life”, we properly evaluate more-basic acts of sharing – where this concerns their adherence to standards of fairness – as a way of evaluating them as complex acts of loving. Life-sharing offers an attractive feminist ideal of love, immune to concerns about the alleged imposition of fairness-related considerations where they don’t belong. (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)

Questions of fair allocation arise regularly throughout our lives, ranging from the trivial to the significant, for governments, private companies, associations, families, and friends. This article discusses the nature of allocative fairness, which is focused on the fair distribution of divisible and indivisible goods. The recent literature on allocative fairness takes John Broome's discussion of fairness as the proportional treatment of claims as its starting point. On this view, a claim is a reason why an individual ought (...) to receive a good. This article discusses the nature of allocative fairness, claims, and goods. The most prominent allocative procedures in the literature are discussed, including equal allocation, equitable allocation, markets, lotteries, and queues. (shrink)

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)

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)

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)

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)

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)

The fair use doctrine has been tech companies’ most valuable legal justification for systematically extracting and scraping content from the internet to train their generative artificial intelligence tools. Although fair use has historically protected the public from the monopolization of creative expression and intellectual property, in its current state, the doctrine enables powerful tech companies and movie studios alike to hoard copyrighted content while disenfranchising individual artists and creators. In May 2023, the United States Supreme Court ruled on Andy Warhol (...) Foundation for the Visual Arts, Inc. v. Goldsmith, a dispute about whether Andy Warhol’s use of Lynn Goldsmith’s original photo of Prince is a fair use. The Court concluded that a copy is not transformative under fair use when it is used commercially for a substantially similar purpose as the original. The decision affirms that the fair use inquiry must look beyond mere similarities and differences between a copy and the original. Instead, courts must grapple with how a copy is used. -/- This Article examines the Supreme Court’s reinterpretation of the fair use doctrine in the Warhol decision in the context of creative expression and generative AI. More specifically, the majority’s emphasis on purpose and market competition tips the scale in favor of artists and creators concerned about generative AI models trained on copyrighted work. This Article also argues that the fair use analysis in Warhol recontextualizes Authors Guild v. Google, weakening a defense tech companies have relied on for ingesting copyrighted material to train AI models. Lastly, this Article considers the entertainment industry’s response to generative AI, including the WGA and SAG-AFTRA strikes, and proposes changes to the fair use doctrine to avoid a bleak future for art and creative expression. -/- Ultimately, the Warhol ruling introduces some refreshing complexity back to the issue of fair use, particularly in context of generative AI and AI image generators. Still, many legal and existential questions remain. For instance, given the potential of AI to relieve society of dangerous and unfulfilling labor, why have tech companies opted to devalue labor that is abundant, meaningful, and undervalued? (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)

The initial idea of fair equality of opportunity is that if two people are both capable of doing a job and would be equally good at it, then they should stand an equal chance of getting it, whereas if one is less capable then they should stand a less chance. Fair equality is recommended (mostly famously by John Rawls) with the hope of overcoming situations in which certain jobs are dominated by people of a certain social class. But it faces (...) what I call the problem of generational jobs: for a member of your family (or social network) to get one of these jobs normally requires adaptation by them for that end over generations: a clever child cannot do it without this preparatory work from previous generations, modifying the background of assumptions say. With this in mind, I discuss Diane Keaton, who recently died. Diane Keaton was known as an actress at the core of the world-famous American film industry and a stylish dresser, but she also directed films, for which she has no impressive reputation. She has a surprising image of herself in the role, looking to me like a military man’s housewife, and I think she is suggesting that this is a generational job and while she has built impressively upon the background of her ancestors as actress and style icon, she is no better than them here. I also comment on the relationship between the newspapers and the academic world. (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)

In Maskivker’s recent “Justice and Contribution,” she argues that, under normal circumstances, the failure to guarantee that life-sustaining workers are above the non-struggle point is not merely disrespectful and a failure of beneficence, but a violation of the norms of fair play and, as such, a “low blow.” In this article, I offer a critical reply to Maskivker. I begin by explaining her reasoning. Then I turn to critique, focusing on two key weaknesses and, in so doing, drawing out two (...) larger lessons. -/- Dans son récent article « Justice and Contribution », Julia Maskivker soutient que, dans des circonstances normales, le fait de ne pas garantir que les travailleurs essentiels à la vie reçoivent une compensation suffisante pour ne pas avoir à lutter pour leur subsistance (« non-struggle point ») constitue non seulement un manque de respect et un manque de bienfaisance, mais aussi une violation des normes du franc jeu et, par conséquent, un « coup bas ». Dans cet article, j’offre une réponse critique à Maskivker. Je commence par expliquer son raisonnement. Puis, je passe à la critique, en me concentrant sur deux faiblesses clés et, ce faisant, en tirant deux leçons plus importantes. (shrink)

This paper argues that fairness should be understood not only as a first-order norm governing procedures and outcomes, but as a structural meta-norm that determines which institutional architectures may legitimately exercise authority over moral equals. I develop the idea of a Meta-Right to Structural Fairness: a higher-order moral claim not merely to fair treatment within institutions, but to institutions whose justificatory design allows individuals to stand as equal contributors to, and evaluators of, the reasons that bind them. I (...) show how legitimacy can fail even in procedurally fair, rule-following systems when structural features generate epistemic asymmetry, asymmetrical risk exposure, and justificatory subordination. Using Article 70 of the Constitution of Bangladesh as an analytic case, I illustrate how a formally neutral rule can create catastrophic risk for dissent, epistemic dependency, and centralized justificatory power, thereby undermining legitimacy prior to any particular decision. The paper situates this account in relation to Rawls, Scanlon, Habermas, Raz, Fricker, Buchak, and Pettit, arguing that their frameworks implicitly rely on, but do not fully theorize, the concept of structural fairness. I address realist, proceduralist, Rawlsian, pragmatist, and “inevitability of asymmetry” objections, and argue that none succeeds in dislodging the meta-right. I conclude that political institutions must be evaluated as justificatory architectures, and that equal justificatory standing is a necessary condition for legitimate authority. (shrink)

Often, we should obey conventional, or socially constructed, norms. You should tip in America, queue up in England, take your hat off when you enter a church in Italy. But why? Laura Valentini has recently suggested that obeying conventional norms respects the agency of those who support such norms. In this article, I argue that this is not why we should obey conventional norms. Instead, we should think of the moral force of such norms in terms of doing our fair (...) share. This line of thought starts with the idea that we have many weighty collective obligations: obligations to fairly allocate goods, to help people author their own lives, to ensure workers are paid sufficiently for their work. It is very difficult to motivate and coordinate everyone so as to discharge these obligations. But human beings are norm-following creatures—we are strongly disposed to adopt and comply with social norms. So the most reliable means to discharging these collective obligations is to set up and maintain good social norms. Thus, we have a duty to do our fair share toward upholding such norms. Obeying social norms is doing our fair share in promoting the more fundamental moral goals. (shrink)

_ Source: _Page Count 20 According to the fair play defense of political obligations citizens have a reciprocity-based duty to share the costs involved in the production of public goods. But sometimes, states produce collective goods through wrongdoing. For example, sometimes states’ wrongful immigration policies can contribute to the welfare of their own populations. Do citizens have duties of reciprocity in light of such wrongful benefits? I argue that the answer to this question is negative. Drawing on the observation that (...) beneficiaries of wrongdoing incur compensatory duties to the victims of that wrongdoing, I argue that, rather than having a duty of reciprocity for wrongful benefits, citizens have a duty to disgorge the benefits in compensation. Furthermore, the fair play defense of political obligations entails that citizens can be justified in disobeying the law in order to comply with their compensatory duties to victims of their state’s wrongdoing. (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.

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)

Although equality of opportunity is a fundamental idea of the egalitarian project, there is a continuing controversy about the effective distributive implications of the notion. This paper focuses on this controversy, and maintains that when equality of opportunity is correctly understood, it entails strong distributive implications. In this way, this paper intends to reject the notion that equality of opportunity is associated with a non-institutional idea of meritocracy: an idea which is often used as an ideological tool to make unacceptable (...) inequalities seem acceptable. This paper defends the argument that only an ‘institution-dependent’ conception of equality of opportunity, such as Rawls’ fair equality opportunity, is the most adequate interpretation for a liberal democratic society. Nonetheless, it does not mean that individual merit has no place in liberal democratic societies. Fair equality of opportunity - if correctly understood - is deeply relevant and might contribute to a significant reduction of economic inequality, much more so than is currently perceived in the public debate. (shrink)

This paper reconstructs and critically evaluates John Rawls’s argument that social and economic inequalities are justifiable only when they arise within a scheme of fair cooperation among free and equal persons. Focusing on Rawls’s rejection of desert-based justifications for inequality, the paper examines how the original position and the veil of ignorance function to exclude morally arbitrary advantages from the justification of political principles. Rawls’s two principles of justice are interpreted not as distributive rules grounded in merit or efficiency, but (...) as institutional constraints designed to secure reciprocity and public legitimacy. The analysis argues that Rawls offers a compelling account of why natural talents and social starting points cannot ground moral entitlement to greater reward, and why inequalities must be justified to those who are least advantaged. At the same time, the paper critically assesses persistent objections concerning effort, responsibility, motivation, and the limits of ideal theory. While Rawls’s framework faces challenges in accounting for intuitions about individual responsibility and in addressing non-ideal conditions of structural injustice, the paper contends that these difficulties do not undermine his core insight. Justice as fairness is best understood as a normative standard for evaluating the moral legitimacy of social institutions rather than as a comprehensive theory of personal desert. By situating distributive justice within the context of social cooperation and institutional design, the paper defends Rawls’s approach as a powerful alternative to moralized and entitlement-based accounts of inequality. (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)

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)

This paper proposes a three-variable framework for fairness capacity in humans and artificial systems: F(t) = I(t) × D(t) × S(t) where I represents intelligence and prosocial reasoning capacity, D represents informational accuracy and reliability, and S represents perceived survival safety. The framework formalizes fairness as a dynamically constrained process rather than a fixed innate trait. A time-evolution formulation is introduced to model recursive feedback effects, including scarcity-driven fairness cascades. The paper synthesizes findings from behavioral economics, social (...) psychology, neuroscience, primate fairness research, and AI alignment literature into a unified formal structure. Several testable predictions are derived and compared with prior empirical findings. Exploratory analyses using Global Preferences Survey (GPS), European Social Survey (ESS), and EVS/WVS longitudinal panel data provide partial support for the framework and for a proposed social-bond extension (B_social). Cross-validation and train-test analyses indicate stable out-of-sample performance, while Random-Intercept Cross-Lagged Panel Models (RI-CLPMs) provide more conservative longitudinal estimates. The framework is presented as a formal synthesis and exploratory modeling approach rather than a claim of definitive causal proof. Implications are discussed for human moral behavior, social trust, institutional stability, poverty dynamics, and AI alignment under conditions of informational distortion and perceived threat. (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 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)

Recently, there has been much discussion of ‘fair machine learning’: fairness in data‐driven decision‐making systems (which are often, though not always, made with assistance from machine learning systems). Notorious impossibility results show that we cannot have everything we want here. Such problems call for careful thinking about the foundations of fair machine learning. Sune Holm has identified one promising way forward, which involves applying John Broome's theory of fairness to the puzzles of fair machine learning. Unfortunately, his application (...) of Broome's theory appears to be fatally flawed. This article attempts to rescue Holm's central insight – namely, that Broome's theory can be useful to the study of fair machine learning – by giving an alternative application of Broome's theory, which involves thinking about fair machine learning in counterfactual (as opposed to merely statistical) terms. (shrink)

The “impossibility results” in algorithmic fairness suggest that a predictive model cannot fully meet two common fairness criteria – sufficiency and separation – except under extraordinary circumstances. These findings have sparked a discussion on fairness in algorithms, prompting debates over whether predictive models can avoid unfair discrimination based on protected attributes, such as ethnicity or gender. As shown by Otto Sahlgren, however, the discussion of the impossibility results would gain from importing some of the tools developed in (...) the philosophical literature on feasibility. Utilizing these tools, Sahlgren sketches a cautiously optimistic view of how algorithmic fairness can be made feasible in restricted local decision-making. While we think it is a welcome move to inject the literature on feasibility into the debate on algorithmic fairness, Sahlgren says very little about what are the general gains of bringing in feasibility considerations in theorizing algorithmic fairness. How, more precisely, does it help us make assessments about fairness in algorithmic decision-making? This is what is addressed in this Reply. More specifically, our two-fold argument is that feasibility plays an important but limited role for algorithmic fairness. We end by offering a sketch of a framework, which may be useful for theorizing feasibility in algorithmic fairness. (shrink)

Considerations of dynamic inconsistency have figured prominently in debates over the rationality of preferences that violate the separability conditions characteristic of expected utility theory. These debates have mostly focused on risk- and ambiguity averse preferences, but analogous considerations apply to preferences for fairness. We revisit these debates in the context of a specific hypothesis regarding the violations of separability by such preferences, namely that they are potentially both explained and rationalised by attitudes to the chances of goods that motivate (...) a preference for equality in the distribution of chances across people and possible events. Our main aim is to argue that, first, when these violations of static separability are motivated by such attitudes to chances, then they need not result in dynamically inconsistent behaviour. Second, and more generally, considerations of dynamic consistency do not, we argue, undermine the rationality of such attitudes towards the distribution of chances, despite the fact that such attitudes give rise to violations of the static separability assumptions of expected utility theory. (shrink)