Trusting relationships are both valuable and risky. Where the risks are high and the fears of betrayal are also high, it might seem rational to try to mitigate the risks, while still enjoying the benefits of the trusting relationship, by forming a contingency plan. A contingency plan—in the sense I am interested in—involves contingent punishments for defection, which are primarily meant to encourage the trusted partner to act trustworthily. I argue, however, that such contingency plans suffer from an internal tension wherein the contingency planner both seeks and undermines a particular level (or kind) of trust. There are two problems in particular, either of which is sufficient to undermine trusting relationships: one, the planner fails to see the trusted partner as sincerely engaged in the trusting relationship, and two, the planner separates herself out from the trusting relationship by seeing her flourishing as separate from her partner’s (or, even worse, as dependent on her partner’s harm). Continency plans, then, are not just about the future; they cast a moral shadow on what we are doing now.

An indifference principle says that your credences should be distributed uniformly over each of the possibilities you recognise. A chance deference principle says that your credences should be aligned with the chances. My thesis is that if we are anti-Humeans about chance, then these two principles are incompatible. Anti-Humeans think that it is possible for the actual frequencies to depart from the chances. As long as you recognise possibilities like this, you cannot both spread your credences evenly and defer to the chances. I discuss some weaker forms of indifference which will allow anti-Humeans to defer to the chances.

Beliefs should conform to some norms. Epistemic instrumentalism holds that your beliefs should conform to these epistemic norms just because conforming is useful. But there seems to be cases where conforming to the epistemic norms isn’t useful at all, as in so-called “too-few-reasons” cases. In response to these cases, universal epistemic instrumentalists argue that despite first appearances, it is always useful to conform to the epistemic norms. I argue that all current versions of this universalist response are objectionable. I conclude with a conjecture about why no version of universalism will succeed.

I argue that legitimacy discourses serve a gatekeeping function. They give practitioners telic standards for riding herd on social practices, ensuring that minimally acceptable versions of the practice are implemented. Such a function is a necessary part of implementing formalized social practices, especially including law. This gatekeeping account shows that political philosophers have misunderstood legitimacy. It is not secondary to justice and only necessary because we cannot agree about justice; instead, it is a necessary feature of actual human social practices, which must be implemented via practitioners’ discretion in changing contexts.

I develop a challenge to reductive views of knowing that $ \phi $ that appeal to what I call a gradable property. Such appeal allows for properties that are intrinsically very similar to the property of knowing that $ \phi $, but differ significantly in their normative significance. This violates the independently plausible claim Pautz (2017) labels the ‘small difference principle.’

I argue for a novel interpretation of Leibniz’s conception of the kind of contingency that matters for freedom, which I label ‘agential contingency.’ In brief, an agent is free to the extent that she determines herself to do what she judges to be the best of several considered options that she could have brought about had she concluded that these options were best. I use this novel interpretation to make sense of Leibniz’s doctrine that the reasons that explain free actions are merely inclining and not necessitating.

We are increasingly subject to the power of technological systems relying on big data and AI. These systems are reshaping the welfare state and the administration of criminal justice. They are used to police tax evasion, track down child abusers, and model the spread of the pandemic. And they are used to weaponize vast surveillance networks through facial recognition technology. But algorithmic power extends far beyond the state: we spend ever more time working, socialising, and consuming within digital platforms. Our experiences are governed by algorithms that are constantly monitoring and shaping our behaviour and our attention, automatically selecting what we do and do not see. These online experiences have offline consequences, among them an unprecedented challenge to democratic processes worldwide.

Philosophical work on science and values has come to engage with the concerns of society and of stakeholders affected by science and policy, leading to socially relevant philosophy of science and socially engaged philosophy of science. This special issue showcases instances of socially relevant philosophy of science, featuring contributions on a diversity of topics by Janet Kourany, Andrew Schroeder, Alison Wylie, Kristen Intemann, Joyce Havstad, Justin Biddle, Kevin Elliott, and Ingo Brigandt.

I defend a new account of constitutive essence on which an entity’s constitutively essential properties are its most fundamental, nontrivial necessary properties. I argue that this account accommodates the Finean counterexamples to classic modalism about essence, provides an independently plausible account of constitutive essence, and does not run into clear counterexamples. I conclude that this theory provides a promising way forward for attempts to produce an adequate nonprimitivist, modalist account of essence. As both triviality and fundamentality in the account are understood in terms of grounding, the theory also potentially has important implications for the relation between essence and grounding.

This paper argues for the existence of a certain type of defeater for one’s belief that P—the presence of social incentives not to share evidence against P. Such pressure makes it relatively likely that there is unpossessed evidence that would provide defeaters for P because it makes it likely that the evidence we have is a lopsided subset. This offers, I suggest, a rational reconstruction of a core strand of argument in Mill’s On Liberty. A consequence of the argument is that on morally and politically laden issues in particular, a high degree of doxastic openness might be appropriate.

Science is based on facts—facts that are systematically gathered by a community of enquirers through detailed observation and experiment. In the twentieth century, however, philosophers of science claimed that the facts that scientists “gather” in this way are shaped by the theories scientists accept, and this seemed to threaten the authority of science. Call this the old worries about science. By contrast, what seemed not to threaten that authority were other factors that shaped the facts that scientists gather—for example, the mere questions scientists pursue. Call this the old nonworries about science. What I suggest is that the old nonworries are turning out to be far more worrisome than the old worries, and I use recent goings-on such as the “Death of Evidence” protests in Canada, the “replication crisis,” and the ongoing feminist critiques of science to illustrate my case. All this raises interesting new questions for philosophers of science to tackle.

It is becoming more common that the decision-makers in private and public institutions are predictive algorithmic systems, not humans. This article argues that relying on algorithmic systems is procedurally unjust in contexts involving background conditions of structural injustice. Under such nonideal conditions, algorithmic systems, if left to their own devices, cannot meet a necessary condition of procedural justice, because they fail to provide a sufficiently nuanced model of which cases count as relevantly similar. Resolving this problem requires deliberative capacities uniquely available to human agents. After exploring the limitations of existing formal algorithmic fairness strategies, the article argues that procedural justice requires that human agents relying wholly or in part on algorithmic systems proceed with caution: by avoiding doxastic negligence about algorithmic outputs, by exercising deliberative capacities when making similarity judgments, and by suspending belief and gathering additional information in light of higher-order uncertainty.

Subjectivism about wellbeing rests on the idea that what is good for a person must ‘fit’ her, ‘resonate’ with her, not be ‘alien’ to her, etc. This idea has been called the ‘beating heart’ of subjectivism. In this article, I present the No-Beating-Heart Challenge for subjectivism, which holds that there is no satisfactory statement of this idea. I proceed by first identifying three criteria that any statement of the idea must meet if it is to provide support for subjectivism: Distinctness, Exclusiveness, and Explicitness. I then argue that no statement of this idea meets these criteria.

Part of T. M. Scanlon’s project in What We Owe to Each Other (1998) is to explain the importance and priority of moral reasons. But Scanlon also argues that this priority of moral reasons is compatible with the pursuit of other things we value, such as friendship. To this end, Scanlon claims that contractualist moral reasons internally accommodate our interests in such values. In this paper, I argue that Scanlon is unsuccessful in showing the compatibility of morality and the pursuit of our other values. The contractualist may not be able to be a good friend.

As it is presently employed, grounding permits grounding many things from one ground. In this paper, I show why this is a mistake by pushing for a uniqueness principle on grounding. After arguing in favor of this principle, I say something about it and kinds of grounding, discuss a similar principle, and consider its import on a formal feature of grounding, ontology, and ontological simplicity.

David Chalmers advocates the view that the phenomenon of consciousness is fundamentally different from all other phenomena studied in the life sciences, positing a uniquely hard problem that precludes the possibility of a mechanistic explanation. In this paper, I evaluate three demarcation criteria for dividing phenomena into hard and easy problems: functional definability, the puzzle of the accompanying phenomenon, and the first-person data of subjective experience. I argue that none of the proposed criteria can accurately discriminate between the phenomenon of consciousness and mechanistically explainable phenomena.

The eighteenth-century German rationalist tradition is, broadly speaking, committed to (what I call) ‘the principle of rational cognition’: the grounded must be rationally cognizable from its sufficient ground. Whereas the prevailing view takes the fundamental challenge to rationalist paradise to stem from the principle of sufficient reason, I argue that it instead stems from this principle: How is it possible to rationally cognize anything at all from its ground? By investigating the opposing responses of two of Leibniz’s most influential immediate successors, Christian Wolff and Christian Crusius, we find no easy way to remain in rationalist paradise.

Ideology critics believe that many bad social practices persist because of ideology, and that critiquing ideology is an effective way to promote social reform. Skeptics draw on game theory to argue that the persistence of such practices is better explained by collective action problems, and that ideology critique is causally inefficacious. In this paper, I reconcile these camps. I show that while game theory can help us identify contexts where ideology critique makes no difference, it also reveals causal mechanisms by which ideology critique can have a significant effect. I then consider some objections and directions for further research.

In the last two decades, a robust consensus has emerged among philosophers of science, whereby political, ethical, or social values must play some role in scientific inquiry, and that the ‘value-free ideal’ is thus a misguided conception of science. However, the question of how to distinguish, in a principled way, which values may legitimately influence science remains. This question, which has been dubbed the ‘new demarcation problem,’ has until recently received comparatively less attention from philosophers of science. In this paper, I appeal to Rawls’s theory of justice (1971) on the basis of which I defend a Rawlsian solution to the new demarcation problem. As I argue, the Rawlsian solution places plausible constraints on which values ought to influence scientific inquiry, and, moreover, can be fruitfully applied to concrete cases to determine how the conflicting interests of stakeholders should be balanced. After considering and responding to the objection that Rawls’s theory of justice applies only to the “basic structure” of society, I compare the Rawlsian solution to some other approaches to the new demarcation problem, especially those that emphasize democratic criteria.

This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to explain why this systemic exclusion is of moral concern and to offer a solution to address it.