William D'Alessandro

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict — perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that end, I develop two simple models for comparing ‘longtermist’ and ‘neartermist’ interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don’t mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these ‘Pascalian’ probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism.

Many people hold the constraint against doing harm, the view that the reason against doing harm is stronger than the reason against merely allowing harm, everything else being equal. Mogensen and MacAskill (2021) have recently argued that when considering indirect long-term consequences of our everyday behavior, the constraint against doing harm faces a problem: it has the absurd implication that we should do as little as possible in our lives. In this paper, I explore the view that, for behavior that does not increase anyone’s ex ante risk of suffering harm, the reason against doing harm is not stronger than the reason against merely allowing harm, everything else being equal. I argue that this view is plausible, show how it solves the paralysis problem, and defend it against objections.

This paper considers the potentially wrongful discriminatory nature of certain of our dating preferences. It argues that the wrongfulness of such preferences lies primarily in the simple lookism they involve. While it is ultimately permissible for us to date people partly because of how they look, I argue that we have a duty to ‘look behind’ people’s appearance, which I take to mean that we ought not, on the basis of their appearance, to regard them as absolutely out of the question for us to engage with in a romantic setting. Further, constraints similar to those suggested by a duty to look behind people’s appearance gain support from another duty we have, namely, a duty to counteract, also in our daily lives, the fact that people are undeservedly disadvantaged in various ways.

Longtermists claim that what we ought to do is mainly determined by how our actions might affect the very long-run future. A natural objection to longtermism is that these effects may be nearly impossible to predict -- perhaps so close to impossible that, despite the astronomical importance of the far future, the expected value of our present actions is mainly determined by near-term considerations. This paper aims to precisify and evaluate one version of this epistemic objection to longtermism. To that end, I develop two simple models for comparing "longtermist" and "neartermist" interventions, incorporating the idea that it is harder to make a predictable difference to the further future. These models yield mixed conclusions: if we simply aim to maximize expected value, and don't mind premising our choices on minuscule probabilities of astronomical payoffs, the case for longtermism looks robust. But on some prima facie plausible empirical worldviews, the expectational superiority of longtermist interventions depends heavily on these "Pascalian" probabilities. So the case for longtermism may depend either on plausible but non-obvious empirical claims or on a tolerance for Pascalian fanaticism.

Open texture is a kind of semantic indeterminacy first systematically studied by Waismann. In this paper, extant definitions of open texture will be compared and contrasted, with a view towards the consequences of open-textured concepts in mathematics. It has been suggested that these would threaten the traditional virtues of proof, primarily the certainty bestowed by proof-possession, and this suggestion will be critically investigated using recent work on informal proof. It will be argued that informal proofs have virtues that mitigate the danger posed by open texture. Moreover, it will be argued that while rigor in the guise of formalisation and axiomatisation might banish open texture from mathematical theories through implicit definition, it can do so only at the cost of restricting the tamed concepts in certain ways.

This article argues that political injustices can arise from the distribution and character of our sexual desires and that we can be held responsible for correcting these injustices. It draws on a conception of structural injustice to diagnose unjust patterns of sexual attraction, which are taken to arise when socio-structural processes shaping the formation of sexual desire compound systemic domination and capacity-deprivation for the occupants of a social position. Individualistic and structural solutions to the problem of unjust patterns of sexual attraction are assessed in the context of racialised sexual aversion, racial fetishism, and the desexualisation of people with disabilities. While both forms of intervention can help in principle, some of the advantages of structural approaches are laid out. A schema for assigning political responsibilities for addressing this injustice is proposed, with some limits identified to the kinds of state and social responses that are justified. Finally, the status of the merely aesthetically unappealing is considered, with a relational egalitarian approach concluding that they are subject to structurally unjust patterns of sexual desire only when exposed to oppression or second-class citizenship as a result.

This paper examines the role of prestige bias in shaping academic philosophy, with a focus on its demographics. I argue that prestige bias exacerbates the structural underrepresentation of minorities in philosophy. It works as a filter against (among others) philosophers of color, women philosophers, and philosophers of low socio-economic status. As a consequence of prestige bias our judgments of philosophical quality become distorted. I outline ways in which prestige bias in philosophy can be mitigated.

Defenders of the enhanced indispensability argument argue that the most effective route to platonism is via the explanatory role of mathematical posits in science. Various compelling cases of mathematical explanation in science have been proposed, but a satisfactory general philosophical account of such explanations is lacking. In this paper, I lay out the framework for such an account based on the notion of “the mathematical stance.” This is developed by analogy with Dennett’s well-known concept of “the intentional stance.” Roughly, adopting the mathematical stance towards a particular physical phenomenon involves treating it as an abstract mathematical structure for the purposes of prediction and explanation. Interestingly, Dennett himself frequently draws analogies between his intentional stance towards beliefs and desires and scientists’ stance towards centers of gravity. I explore the theoretical role played by centers of gravity within science and discuss how an indispensabilist platonist ought to categorize the ontological status of this type of posit. I conclude with some thoughts on how an approach based on the mathematical stance might be developed into a more general philosophical account of the application of mathematics in science.

Recent discussions of how axioms are extrinsically justified have appealed to abductive considerations: on such accounts, axioms are adopted on the basis that they constitute the best explanation of some mathematical data, or phenomena. In the first part of this paper, I set out a potential problem caused by the appeal made to the notion of mathematical explanation and suggest that it can be remedied once it is noted that all the justificatory work is done by appeal to the theoretical virtues. In the second part of the paper, I appeal to the theoretical virtues account of axiom justification to provide an argument that judgements of theoretical virtuousness, and therefore of extrinsic justification, are subjective in a substantive sense. This tells against a recent claim by Penelope Maddy that such justification is “wholly objective”.

In this paper we apply social epistemology to mathematical proofs and their role in mathematical knowledge. The most famous modern collaborative mathematical proof effort is the Classification of Finite Simple Groups. The history and sociology of this proof have been well-documented by Alma Steingart (2012), who highlights a number of surprising and unusual features of this collaborative endeavour that set it apart from smaller-scale pieces of mathematics. These features raise a number of interesting philosophical issues, but have received very little attention. In this paper, we will consider the philosophical tensions that Steingart uncovers, and use them to argue that the best account of the epistemic status of the Classification Theorem will be essentially and ineliminably social. This forms part of the broader argument that in order to understand mathematical proofs, we must appreciate their social aspects.

In mathematics, any form of probabilistic proof obtained through the application of a probabilistic method is not considered as a legitimate way of gaining mathematical knowledge. In a series of papers, Don Fallis has defended the thesis that there are no epistemic reasons justifying mathematicians’ rejection of probabilistic proofs. This paper identifies such an epistemic reason. More specifically, it is argued here that if one adopts a conception of mathematical knowledge in which an epistemic subject can know a mathematical proposition based solely on a probabilistic proof, one is then forced to admit that such an epistemic subject can know several lottery propositions based solely on probabilistic evidence. Insofar as knowledge of lottery propositions on the basis of probabilistic evidence alone is denied by the vast majority of epistemologists, it is concluded that this constitutes an epistemic reason for rejecting probabilistic proofs as a means of acquiring mathematical knowledge.

The connection between understanding and explanation has recently been of interest to philosophers. Inglis and Mejía-Ramos (Synthese, 2019) propose that within mathematics, we should accept a functional account of explanation that characterizes explanations as those things that produce understanding. In this paper, I start with the assumption that this view of mathematical explanation is correct and consider what we can consequently learn about mathematical explanation. I argue that this view of explanation suggests that we should shift the question of explanation away from why-questions and towards a “what’s going on here” question. Additionally, I argue that when we recognize the connection between understanding and explanation we naturally see how more than just proof can be explanatory. I expand this point by detailing how definitions and diagrams can be explanatory. In all, we see that when we take seriously the connection between understanding and explanation, we get a better sense of how explanation arises within mathematics.

I explore the motivation and logical consequences of the idea that we have some (limited) ability to know contingent facts about the future, even in presence of the assumption that the future is objectively unsettled or indeterminate. I start by formally characterizing skepticism about the future. This analysis nudges the anti-skeptic towards the idea that if some propositions about the future are objectively indeterminate, then it may be indeterminate whether a suitably positioned agent knows them. Philosophical Perspectives, Volume 35, Issue 1, Page 50-69, December 2021.

The periodic table represents and organizes all known chemical elements on the basis of their properties. While the importance of this table in chemistry is uncontroversial, the role that it plays in scientific reasoning remains heavily disputed. Many philosophers deny the explanatory role of the table and insist that it is “merely” classificatory (Shapere, in F. Suppe (Ed.) The structure of scientific theories, University of Illinois Press, Illinois, 1977; Scerri in Erkenntnis 47:229–243, 1997). In particular, it has been claimed that the table does not figure in causal explanation because it “does not reveal causal structure” (Woody in Science after the practice turn in the philosophy, history, and social studies of science, Routledge Taylor & Francis Group, New York, 2014). This paper provides an analysis of what it means to say that a scientific figure reveals causal structure and it argues that the modern periodic table does just this. It also clarifies why these “merely” classificatory claims have seemed so compelling–this is because these claims often focus on the earliest periodic tables, which lack the causal structure present in modern versions.

Philosophers often aim to demonstrate that the things we ordinarily think and say can be reconciled with our considered beliefs about the world. To this end, many philosophers try to paraphrase ordinary language claims by finding equivalent sentences that are less misleading. For instance, though we know that there is no British family that is the average one, we want to say that the average British family has 1.8 children, and we might do that by paraphrasing this claim as: there are nearly twice as many British children as British families. This article aims to introduce and distinguish different paraphrase strategies, sketch their role in metaphysical debates and highlight some crucial questions that proponents of such strategies face

We want to know what gender is. But metaphysical approaches to this question solely have focused on the binary gender kinds men and women. By overlooking those who identify outside of the binary–the group I call ‘genderqueer’–we are left without tools for understanding these new and quickly growing gender identifications. This metaphysical gap in turn creates a conceptual lacuna that contributes to systematic misunderstanding of genderqueer persons. In this paper, I argue that to better understand genderqueer identities, we must recognize a new type of gender kind: critical gender kinds, or kinds whose members collectively destabilize one or more pieces of dominant gender ideology. After developing a model of critical gender kinds, I suggest that genderqueer is best modeled as a critical gender kind that destabilizes the ‘binary axis’, or the piece of dominant gender ideology that says that the only possible genders are the binary, discrete, exclusive, and exhaustive kinds men and women.

Although there is a consensus among philosophers of mathematics and mathematicians that mathematical explanations exist, only a few authors have proposed accounts of explanation in mathematics. These accounts fit into the unificationist or top-down approach to explanation. We argue that these models can be complemented by a bottom-up approach to explanation in mathematics. We introduce the mechanistic model of explanation in science and discuss the possibility of using this model in mathematics, arguing that using it does not presuppose a Platonist view of mathematics and allows one to gain insight into why a theorem is true by answering what-if-things-had-been-different questions

Model-data symbiosis is the view that there is an interdependent and mutually beneficial relationship between data and models, whereby models are not only data-laden, but data are also model-laden or model filtered. In this paper I elaborate and defend the second, more controversial, component of the symbiosis view. In particular, I construct a preliminary taxonomy of the different ways in which theoretical and simulation models are used in the production of data sets. These include data conversion, data correction, data interpolation, data scaling, data fusion, data assimilation, and synthetic data. Each is defined and briefly illustrated with an example from the geosciences. I argue that model-filtered data are typically more accurate and reliable than the so-called raw data, and hence beneficially serve the epistemic aims of science. By illuminating the methods by which raw data are turned into scientifically useful data sets, this taxonomy provides a foundation for developing a more adequate philosophy of data.

This paper explores whether there is any relation between mathematical proofs that specify the grounds of the theorem being proved and mathematical proofs that explain why the theorem obtains. The paper argues that a mathematical fact’s grounds do not, simply by virtue of grounding it, thereby explain why that fact obtains. It argues that oftentimes, a proof specifying a mathematical fact’s grounds fails to explain why that fact obtains whereas any explanation of the fact does not specify its ground. The paper offers several examples from mathematical practice to illustrate these points. These examples suggest several reasons why explaining and grounding tend to come apart, including that explanatory proofs need not exhibit purity, tend not to be brute force, and often unify separate cases by identifying common reasons behind them even when those cases have distinct grounds. The paper sketches an account of what makes a proof explanatory and uses that account to defend the morals drawn from the examples already given.

Mathematical explanations are poorly understood. Although mathematicians seem to regularly suggest that some proofs are explanatory whereas others are not, none of the philosophical accounts of what such claims mean has become widely accepted. In this paper we explore Wilkenfeld’s suggestion that explanations are those sorts of things that generate understanding. By considering a basic model of human cognitive architecture, we suggest that existing accounts of mathematical explanation are all derivable consequences of Wilkenfeld’s ‘functional explanation’ proposal. We therefore argue that the explanatory criteria offered by earlier accounts can all be thought of as features that make it more likely that a mathematical proof will generate understanding. On the functional account, features such as characterising properties, unification, and salience correlate with explanatoriness, but they do not define explanatoriness.

The ontic conception of explanation, according to which explanations are "full-bodied things in the world," is fundamentally misguided. I argue instead for what I call the eikonic conception, according to which explanations are the product of an epistemic activity involving representations of the phenomena to be explained. What is explained in the first instance is a particular conceptualization of the explanandum phenomenon, contextualized within a given research program or explanatory project. I conclude that this eikonic conception has a number of benefits, including making better sense of scientific practice and allowing for the full range of normative constraints on explanation.

In this paper, I identify a form of epistemic insensitivity that occurs when someone fails to make proper use of the epistemic tools at their disposal in order to bring their beliefs in line with epistemically relevant evidence that is available to them. I call this kind of insensitivity agential insensitivity because it stems from the epistemic behavior of an individual agent. Agential insensitivity can manifest as a failure to either attend to relevant and available evidence, or appropriately interpret evidence that is attended to. The concept of agential insensitivity allows us to conceptualize the kind of not-knowing involved in forms of ignorance that are cultivated and maintained by individual agents, especially when this ignorance is enabled or encouraged by social structures. I use the skepticism about racial disparities in policing practices that is displayed by many white Americans as a lens for exploring this connection. Understanding agential insensitivity thus provides insight into both social and epistemic phenomena.