A primary goal of quantum computer science is to find an explanation for the fact that quantum computers are more powerful than classical computers. In this paper I argue that to answer this question is to compare algorithmic processes of various kinds and to describe the possibility spaces associated with these processes. By doing this, we explain how it is possible for one process to outperform its rival. Further, in this and similar examples little is gained in subsequently asking (...) a how-actually question. Once one has explained how-possibly, there is little left to do. (shrink)

A common view of how-possibly explanations in biology treats them as explanatorily incomplete. In addition to this interpretation of how-possibly explanation, I argue that there is another interpretation, one which features what I term “explanatory strategies.” This strategy-centered interpretation of how-possibly explanation centers on there being a different explanatory context within which how-possibly explanations are offered. I contend that, in conditions where this strategy context is recognized, how-possibly explanations can be understood as complete (...) explanations. I defend this alternative interpretation by analyzing the explanatory value of simple physical models the nineteenth century developmental biologist Wilhelm His constructed for animal development. (shrink)

Biologists in many different fields of research give how-possibly explanations of the phenomena they study. Although such explanations lack empirical support, and might be regarded by some as unscientific, they play an important heuristic role in biology by helping biologists develop theories and concepts and suggesting new areas of research. How-possibly explanations serve as a useful framework for conducting research in the absence of adequate empiri cal data, and they can even become how-actually explanations if they gain enough (...) empirical support. (shrink)

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly (...) and how-actually explanations. Whereas how-possibly explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims. (shrink)

In the current debate on the relation between how-possibly explanations (HPEs) and understanding, two seemingly irreconcilable positions have emerged, which either deny or assert HPEs’ contribution to understanding. We argue, in contrast, that there is substantial room for reconciliation between these positions. First, we show that a shared assumption is unfounded: HPEs can be interpreted as being correct explanations. Second, we argue that what we call the standard account is actually compatible with the claim that HPEs may improve understanding. (...) Our analysis not only indicates that there is room for reconciliation, but also specifies the potential remaining disagreements. (shrink)

In the current debate on the relation between how-possibly explanations (HPEs) and understanding, two seemingly irreconcilable positions have emerged, which either deny or assert HPEs’ contribution to understanding. We argue, in contrast, that there is substantial room for reconciliation between these positions. First, we show that a shared assumption is unfounded: HPEs can be interpreted as being correct explanations. Second, we argue that what we call the standard account is actually compatible with the claim that HPEs may improve understanding. (...) Our analysis not only indicates that there is room for reconciliation, but also specifies the potential remaining disagreements. (shrink)

Philosophers of science have variously tried to characterize how-possibly explanations (HPEs) and distinguish them from how-actually explanations (HAEs). I argue that existing contributions to this debate have failed to pay attention to the different, but complementary, functions possibilities play in scientific explanations. To bring these functions to the fore, I introduce a distinction between what I call elucidating and embedding HPEs. While elucidating HPEs specify and demonstrate possible processes for a given research target, embedding HPEs demonstrate how the research (...) target fits into a space of suitably constrained possibilities. I specify both functions of HPE with reference to two case studies from origins-of-life research. I contrast my distinction with an alternative proposal by Wirling and Grüne-Yanoff (2024) to highlight that focusing on the functions, rather than types, of possibilities in explanation is better suited to account for key scientific practices. (shrink)

Abstract‘Possibilist Explanation’ is a promising account of scientific explanation which avoids the familiar problems of “how-possibly explanations”. It explains an event by showing how-actually it was epistemically possible, instead of why it was epistemically necessary. Its explanandum is the epistemic possibility of an actual event previously considered epistemically impossible. To define PE, two new concepts are introduced: ‘permissive condition’ and ‘possibilist law’. A permissive condition for an event is something that does not entail the event itself, but (...) a necessary condition for it. A ‘Possibilist Law’ is a kind of scientific law that predicts that in the absence of a necessary condition N, the event E is not possible. Both PE and PL are legitimate and neglected parts of scientific knowledge and are especially suitable for human sciences. (shrink)

Simulations using idealized numerical models can often generate behaviors or patterns that are visually very similar to the natural phenomenon being investigated and to be explained. The question arises, when should these model simulations be taken to provide an explanation for why the natural phenomena exhibit the patterns that they do? An important distinction for answering this question is that between ‘how-possibly’ explanations and ‘how-actually’ explanations. Despite the importance of this distinction there has been surprisingly little agreement over (...) how exactly this distinction should bedrawn. I shall argue that inadequate attention has been paid to the different contexts in which an explanation can be given and the different levels of abstraction at which the explanandum phenomenon can be framed. By tracing how scientists are using model simulations to explain a striking periodic banding of vegetation known as tiger bush, I will show how our understanding of the distinction between how-possibly and how-actually model explanations needs to be revised. (shrink)

Confirmation in evolutionary biology depends on what biologists take to be the genuine rivals. Investigating what constrains the scope of biological possibility provides part of the story: explaining how possible helps determine what counts as a genuine rival and thus informs confirmation. To clarify the criteria for genuine rivalry I distinguish between global and local constraints on biological possibility, and offer an account of how-possibly explanation. To sharpen the connection between confirmation and explaining how possible I discuss the (...) view that formal inquiry can provide a kind of confirmation-theoretic support for evolutionary models, and offer an example of how-possibly explanation interacting with testing practice. (shrink)

Explaining how something is possible is a familiar and epistemically important achievement in both science and ordinary life. But a satisfactory general account of how-possibly explanation has not yet been given. A crucial desideratum for a successful account is that it must differentiate a demonstration that something is possible from an explanation of how it is possible. In this paper, I offer an account of how-possibly explanation that fully captures this distinction. I motivate my account (...) using two cases, one from ordinary life and one from ornithology. On my account, a how-possibly explanation is a greater achievement than a mere description of how a state of affairs might possibly obtain. In addition to being a potential explanation of why some state of affairs actually obtains, a how-possibly explanation must involve the relief of an imaginative frustration on the part of its recipient. When a recipient’s imaginative frustration is relieved, she does not just know that the state of affairs in question is possible, but is also able to imagine how it could possibly obtain. (shrink)

Philosophers of science have often favoured reductive approaches to how-possibly explanation. This article identifies three alternative conceptions making how-possibly explanation an interesting phenomenon in its own right. The first variety approaches “how possibly X?” by showing that X is not epistemically impossible. This can sometimes be achieved by removing misunderstandings concerning the implications of one’s current belief system but involves characteristically a modification of this belief system so that acceptance of X does not result in (...) contradiction. The second variety offers a potential how-explanation of X. It is usually followed by a range of further potential how-explanations of the same phenomenon. In recent literature the factual claims implied by the second variety have been downplayed whereas the heuristic role of mapping the space of conceptual possibilities has been emphasized. I will focus especially on this truth-bracketing sense of potentiality when looking closer at the second variety in the paper. The third variety has attracted less interest. It presents a partial how-explanation of X. Typically it aims to establish the existence of a mechanism by which X could be and was generated. The third conception stands out as the natural alternative for the advocate of ontic how-possibly explanations. This article transfers Salmon’s view that explanation-concepts can be broadly divided into epistemic, modal, and ontic to the context of how-possibly explanations. Moreover, it is argued that each of the three above-mentioned varieties of how-possibly explanation occurs in science. To recognize this may be especially relevant for philosophers. We are often misled by the promises of various why-explanation accounts, and seem to have forgotten nearly everything about the diversity of how-possibly explanations. (shrink)

That biology provides explanations is not open to doubt. But how it does so must be a vexed question for those who deny that biology embodies laws or other generalizations with the sort of explanatory force that the philosophy of science recognizes. The most common response to this problem has involved redefining law so that those grammatically general statements which biologists invoke in explanations can be counted as laws. But this terminological innovation cannot identify the source of biology's explanatory power. (...) I argue that because biological science is historical, the problem of biological explanation can be assimilated to the parallel problem in the philosophy of history, and that the problem was solved by Carl Hempel. All we need to do is recognize that the only laws that biology—in all its compartments from the molecular onward—has or needs are the laws of natural selection. (shrink)

Considers the idea that, in addition to the ‘normative’ explanation of action as characterized in this book, there might not also be causal explanations that appeal to psychological states of the agent as causes. Argues that such causal explanations cannot be accounts of the reasons for which the agent acted; we cannot have two such accounts in play at once. But, if they are merely causal, they are no longer attractive. Ends by considering the possibility of other causal explanations (...) of action and their relation to normative explanations. (shrink)

Some years ago, in the course of a general critique of what has sometimes been referred to as the covering law theory of explanation, I made the claim that perfectly satisfactory explanations can often be provided by indicating only one or a few necessary conditions, where we remain ignorant of the sufficient conditions, of what we nevertheless claim to understand. What seemed to me one identifiable type of such explanations I called “explaining how-possibly,” because it was a type (...) more naturally given in response to the question how it could be that a certain thing happened than to the more familiar question why it did so. In the present paper I propose to review certain objections to this thesis which have come to my attention in the interval, and to make such concessions as these seem to require. In fact, the concessions will be minor, since the general thesis still seems to me quite defensible. (shrink)

One can find in the literature two sets of views concerning the relationship between understanding and explanation: that one understands only if 1) one has knowledge of causes and 2) that knowledge is provided by an explanation. Taken together, these tenets characterize what I call the narrow knowledge account of understanding. While the first tenet has recently come under severe attack, the second has been more resistant to change. I argue that we have good reasons to reject it (...) on the basis of theoretical models that provide how-possibly explanations. These models, while they do not explain in the strict sense, afford understanding. In response, I propose an alternative epistemology of understanding, broad KAU, that takes cases of theoretical modelling into account. (shrink)

Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One paradoxical implication of that proposal is that epistemic value may be obtained from mere ignorance. For the less we know, then the more is epistemically possible. This chapter examines a particular class of problematic epistemically possible how-possibly explanations, viz. *epistemically opaque* how-possibly explanations. Those are how-possibly explanations justified by an epistemically opaque process. How could epistemically opaque how-possibly (...) explanations have epistemic value if they result from a process about which we lack knowledge or understanding? This chapter proposes three different strategies to salvage epistemic value from epistemic opacity, namely salvaging value from 1) functional transparency, 2) modal operator interpretation, and 3) pursuitworthiness. It illustrates using cases from deep neural network modeling. (shrink)

Nancy Cartwright argues that so-called capacities, not universal laws of nature, best explain the often complex way events actually unfold. On this view, science would represent a world that is fundamentally "dappled", or disunified, and not, as orthodoxy would perhaps have it, a world unified by universal laws of nature. I argue, first, that the problem Cartwright raises for laws of nature seems to arise for capacities too, so why reject laws of nature? Second, that in so far as there (...) is a problem, it concerns the role of counterfactuals in explanation; I then briefly propose a simple model of counterfactual explanation. Finally, I investigate how a sophisticated version of the regularity theory of laws of nature (that of Ramsey-Lewis) can be neutral between the empirical hypotheses that the world is unified, and that the world is disunified. (shrink)

In this paper we examine the epistemic value of highly idealized agent-based models of social aspects of scientific inquiry. On the one hand, we argue that taking the results of such simulations as informative of actual scientific inquiry is unwarranted, at least for the class of models proposed in recent literature. Moreover, we argue that a weaker approach, which takes these models as providing only “how-possibly” explanations, does not help to improve their epistemic value. On the other hand, we (...) suggest that if ABMs of science underwent two types of robustness analysis, they could indeed have a clear epistemic function, namely by providing evidence for philosophical and historical hypotheses. In this sense, ABMs can obtain evidential and explanatory properties and thus be a useful tool for integrated history and philosophy of science. We illustrate our point with an example of a model—building on the work by Kevin Zollman—which we apply to a concrete historical case study. (shrink)

This paper presents a new approach to resolving an apparent tension in Descartes’ discussion of scientific theories and explanations in the Principles of Philosophy. On the one hand, Descartes repeatedly claims that any theories presented in science must be certain and indubitable. On the other hand, Descartes himself presents an astonishing number of speculative explanations of various scientific phenomena. In response to this tension, commentators have suggested that Descartes changed his mind about scientific theories having to be certain and indubitable, (...) that he lacked the conceptual resources to describe the appropriate epistemic attitude towards speculative theories, or that the presence of geometrical principles in these explanations guarantee their certainty. I argue that none of these responses is satisfactory and suggest a different resolution to the tension by examining Descartes’ notion of explanation. On Descartes’ view, providing an adequate explanation does not require being certain of the theories that constitute the explanans. Relatedly, the purpose of Cartesian explanations is not to discover the truth about the various underlying mechanisms that such explanations appeal to, but to support his general philosophical thesis that all natural phenomena can be explained by appealing to the extension of matter. (shrink)

In this paper, we explore different possible explanations for research misconduct (especially falsification and fabrication), and investigate whether they are compatible. We suggest that to explain research misconduct, we should pay attention to three factors: (1) the beliefs and desires of the misconductor, (2) contextual affordances, (3) and unconscious biases or influences. We draw on the three different narratives (individual, institutional, system of science) of research misconduct as proposed by Sovacool to review six different explanations. Four theories start from the (...) individual: Rational Choice theory, Bad Apple theory, General Strain Theory and Prospect Theory. Organizational Justice Theory focuses on institutional factors, while New Public Management targets the system of science. For each theory, we illustrate the kinds of facts that must be known in order for explanations based on them to have minimal plausibility. We suggest that none can constitute a full explanation. Finally, we explore how the different possible explanations interrelate. We find that they are compatible, with the exception of explanations based on Rational Choice Theory and Prospect Theory respectively, which are incompatible with one another. For illustrative purposes we examine the case of Diederik Stapel. (shrink)

Recently, many philosophers have been inclined to ascribe mentality to animals on the main grounds that they possess certain complex computational abilities. In this paper I contend that this view is misleading, since it wrongly assumes that those computational abilities demand a psychological explanation. On the contrary, they can be just characterised from a computational level of explanation, which picks up a domain of computation and information processing that is common to many computing systems but is autonomous from (...) the domain of psychology. Thus, I propose that it is possible to conceive insects and other animals as mere computing agents, without having any commitment to ascribe mentality to them. I conclude by sketching a proposal about how to draw the line between mere computing and genuine mentality. (shrink)

Detailed examinations of scientific practice have revealed that the use of idealized models in the sciences is pervasive. These models play a central role in not only the investigation and prediction of phenomena, but in their received scientific explanations as well. This has led philosophers of science to begin revising the traditional philosophical accounts of scientific explanation in order to make sense of this practice. These new model-based accounts of scientific explanation, however, raise a number of key questions: (...) Can the fictions and falsehoods inherent in the modeling practice do real explanatory work? Do some highly abstract and mathematical models exhibit a noncausal form of scientific explanation? How can one distinguish an exploratory "how-possibly" model explanation from a genuine "how-actually" model explanation? Do modelers face tradeoffs such that a model that is optimized for yielding explanatory insight, for example, might fail to be the most predictively accurate, and vice versa? This chapter explores the various answers that have been given to these questions. (shrink)

Scientists regularly make possibility claims. While philosophers of science are well aware of the distinction between epistemic and objective notions of possibility, we believe that they often fail to apply this distinction in their analyses of scientific practices that employ modal concepts. We argue that heeding this distinction will help further progress in current debates in the philosophy of science, as it shows that the debaters talk about different things, rather than disagree on the same issue. We first discuss how (...) the two notions differ with respect to their epistemology and show that these differences are sometimes ignored in the philosophy of science. We then revisit four current philosophy of science debates about modelling, that are framed in modal terms, to showcase how the distinction significantly clarifies these debates and thereby helps advance them. (shrink)

According to a recent proposal, the epistemic aim of metaphysics as a discipline is to chart the different viable theories of metaphysical objects of inquiry (e.g. causation, persistence). This paper elaborates on and seeks to improve on that proposal in two related ways. First, drawing on an analogy with how-possibly explanation in science, I argue that we can usefully understand this aim of metaphysics as the charting of epistemically possible answers to metaphysical questions. Second, I argue that in (...) order to account for the epistemic goodness of this aim, one should appeal to the epistemic value it has in virtue of providing resources for non-factive understanding of the objects of metaphysical inquiry.**This paper is part of a special issue of Argumenta on the Epistemology of Metaphysics**. (shrink)

An epistemological how-possible question asks how knowledge, or knowledge of some specific kind, is possible. Familiar epistemological how-possible questions include ‘How is knowledge of the external world possible?’, ‘How is knowledge of other minds possible?’ and ‘How is a priori knowledge possible?’ These are the three questions that I tackle in my book. In each case, I explain how and why the question arises and propose a way of answering it. The main negative claim of the book is that transcendental (...) arguments are of little use in answering how-possible questions. A transcendental demonstration of the necessity of a certain kind of knowledge does not amount to an explanation of its possibility. The main positive claim is that such questions call for what I describe as a multi-levels response. I give an account of the multi-levels approach and put it to use in explaining how various kinds of knowledge are possible.Epistemological how-possible questions are not directly concerned with whether knowledge is possible, but if we cannot explain how a certain kind of knowledge is possible then the reality of that kind of knowledge is called into question. How-possible questions are obstacle-dependent. We ask how knowledge …. (shrink)

Why-questions and how-possibly-questions are two common forms of explanation request. Answers to the former ones require factual assertions, but the latter ones can be answered by displaying a representation of the targeted phenomenon. However, in an extreme case, a representation could come accompanied by the assertion that it displays the only possible way a phenomenon could develop. Using several historical controversies concerning statistical modeling, it is argued that such cases must inevitably involve tacit or explicit empirical assumptions.

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from "geometry of motion" with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.

Robustness analysis is widespread in science, but philosophers have struggled to justify its confirmatory power. We provide a positive account of robustness by analysing some explicit and implicit uses of within and across-model robustness in evolutionary theory. We argue that appeals to robustness are usually difficult to justify because they aim to increase the likeliness that a phenomenon obtains. However, we show that robust results are necessary for explanations of phenomena with specific properties. Across-model robustness is necessary for how-possibly (...) explanations of multiply instantiated phenomena, while within-model robustness is necessary for explanations of phenomena with multiple evolutionary starting points. In such cases, the appeal of robustness is explanatory rather than confirmatory. (shrink)

Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities (...) provide epistemically opaque how-possibly explanations. While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry. (shrink)

Philosophers of science have recently taken care to highlight different modeling practices where scientific models primarily contribute modal information, in the form of for example possibility claims, how-possibly explanations, or counterfactual conditionals. While examples abound, comparatively little attention is being paid to the question of under what conditions, and in virtue of what, models can perform this epistemic function. In this paper, we firstly delineate modal modeling from other modeling practices, and secondly reviewattempts to spell out and explain the (...) epistemic success conditions of modal modeling. The aim is to more clearly expose the respective justificatory strategies of these accounts, and secondly, to identify lacunae where further work is needed. (shrink)

Biological modalities, i.e., biologically possible, impossible, or necessary states of affairs have not received much attention from philosophers. Yet, it is widely agreed that there are biological constraints on physically possible states of affairs, such that not everything that is physically possible is also biologically possible, even if everything that is biologically possible is also physically possible. Furthermore, biologists use concepts that appear to be modal in nature, such as the concept of evolvability in evolutionary developmental biology, or “evo-devo.” The (...) present chapter investigates what kind of modality underlies the concept of evolvability. This concept tries to capture the capacity of an organism or a lineage to sustain genetic changes that enable it to evolve or to evolve adaptively. The basic idea of the proposed approach is to construe evolvability as a kind of accessibility in a modal space. The difficult part is to specify this modal space and the relevant accessibility relation. While there may not be a general way of defining such a relation, there exist model systems for which it is possible, e.g., evolving small RNAs. The modal space in such cases turns out to be quite distinct from those constructed by philosophers, e.g., David Lewis’s similarity metric for possible worlds. Even though the biological case examined here is quite special, attending to the way in which biological possibilities are modeled in this case harbors some general lessons about biological modalities, in particular their dependence on the explanatory goals of the models modeling modality. (shrink)

Evolutionary explanations are not only common in the biological sciences, but also widespread outside biology. But an account of how evolutionary explanations perform their explanatory work is still lacking. This paper develops such an account. I argue that available accounts of explanations in evolutionary science miss important parts of the role of history in evolutionary explanations. I argue that the historical part of evolutionary science should be taken as having genuine explanatory force, and that it provides how‐possibly explanations sensu (...) Dray. I propose an account of evolutionary explanations as comparative‐composite explanations consisting of two distinct kinds of explanations, one processual and one historical, that are connected via the explanandum's evolvability to show how the explanandum is the product of its evolutionary past. The account is both a reconstruction of how evolutionary explanations in biology work and a guideline specifying what kind of explanations evolutionary research programs should develop. (shrink)

Explanation in mathematics has recently attracted increased attention from philosophers. The central issue is taken to be how to distinguish between two types of mathematical proofs: those that explain why what they prove is true and those that merely prove theorems without explaining why they are true. This way of framing the issue neglects the possibility of mathematical explanations that are not proofs at all. This paper addresses what it would take for a non-proof to explain. The paper focuses (...) on a particular example of an explanatory non-proof: an argument that mathematicians regard as explaining why a given theorem holds regarding the derivative of an infinite sum of differentiable functions. The paper contrasts this explanatory non-proof with various non-explanatory proofs of the same theorem. The paper offers an account of what makes the given non-proof explanatory. This account is motivated by investigating the difficulties that arise when we try to extend Mark Steiner’s influential account of explanatory proofs to cover this explanatory non-proof. (shrink)

The concept of explanation is central to scientific practice. However, scientists explain phenomena in very different ways. That is, there are many different kinds of explanation; e.g. causal, mechanistic, statistical, or equilibrium explanations. In light of the myriad kinds of explanation identified in the literature, most philosophers of science have adopted some kind of explanatory pluralism. While pluralism about explanation seems plausible, it faces a dilemma Explanation beyond causation, Oxford University Press, Oxford, pp 39–56, 2018). (...) Either there is nothing that unifies all instances of scientific explanation that makes them count as explanations, or there is some set of unifying features, which seems incompatible with explanatory pluralism. Different philosophers have adopted different horns of this dilemma. Some argue that no unified account of explanation is possible. Others suggest that there is a set of necessary features that can unify all explanations under a single account Explanation beyond causation, Oxford University Press, Oxford, pp 74–95, 2018; Strevens in Depth: an account of scientific explanation, Harvard University Press, Cambridge, 2008). In this paper, we argue that none of the features identified by existing accounts of explanation are necessary for all explanations. However, we argue that a unified account can still be provided that accommodates pluralism. This can be accomplished, we argue, by reconceiving of scientific explanation as a cluster concept: there are multiple subsets of features that are sufficient for providing an explanation, but no single feature is necessary for all explanations. Reconceiving of explanation as a cluster concept not only accounts for the diversity of kinds of explanations, but also accounts for the widespread disagreement in the explanation literature and enables explanatory pluralism to avoid Pincock’s dilemma. (shrink)

Saul Kripke did more than anyone else to bring possible worlds into the contemporary philosophical discourse, first with his more formal work on the model theory for modal logic in the 1960s, and then with his more philosophical lectures on reference and modality, delivered in January 1970, that used the possible worlds apparatus informally to clarify the relations between semantic issues about names and metaphysical issues about individuals and kinds. Possible worlds semantics have been widely applied since then, both in (...) philosophy and in other fields such as linguistic semantics and pragmatics, theoretical computer science, and game theory. Kripke’s work, along with that of David Lewis, stimulated an ongoing debate about the nature and metaphysical status of possible worlds. Kripke himself has had little to say about the issues raised in this debate, in print, beyond what he said in Naming and Necessity and in brief remarks in a preface to a later edition of the lectures, published in 1980. But there is a clear view of the nature of possible worlds, and of the status of an explanation of modality in terms of possible worlds, implicit in the lectures and the preface. -/- The central focus of the post–Naming and Necessity debate about possible worlds has been a contrast between David Lewis’s modal realism and various versions of actualism. On this general issue, it is clear enough where Kripke stands: His criticisms of what he describes as the “other countries” picture of possible worlds are an explicit rejection of Lewis’s realism about possible worlds. But the rejection of modal realism raises a range of further questions: What exactly are possible worlds (or possible states of the world, which Kripke suggests would be less misleading terminology)? What contribution do they make to the explanation of modal discourse, and of the distinctive facts that modal discourse is used to state? Does the slogan “necessity is truth in all possible worlds” provide, or point to, a reductive analysis of necessity? Are possible worlds, in some sense, prior to modal operators and modal auxiliaries? If not, in what sense are they explanatory? How are possible worlds, or counterfactual situations, specified? How do they contribute to our understanding of specific meta- physical questions about the relations between particular individuals and their qualitative characteristics, the kinds to which they belong, and the matter of which they are constituted? How are we to understand the possible existence of individuals that do not actually exist? What is the status of the domains of individuals in merely possible worlds? -/- My aim in this chapter is to spell out the views about some of these foundational questions that are expressed or at least implicit in Kripke’s lectures. In Section 2, I discuss the general contrast between modal realism and actualism and questions about the kind of explanation that possible worlds provide for modal discourse and modal facts. In Section 3, I look at Kripke’s views about how possible worlds are specified, in particular at the role of individuals in specifying possible worlds. In Section 4, I consider the problems about merely possible individuals. (shrink)

This book critically examines philosophical naturalism, evaluates the prospects for naturalizing such normative properties as being a reason, and proposes a theory of action-explanation. This theory accommodates an explanatory role for both psychological properties, such as intention, and normative properties, such as having an obligation or being intrinsically good. The overall project requires distinguishing philosophical from methodological naturalism, arguing for the possibility of a scientifically informed epistemology that is not committed to the former, and freeing the theory of action- (...) class='Hi'>explanation from dependence on the reducibility of the mental to the physical. The project also requires distinguishing explanatory power from causal power. Explanations - at least of the kinds central in both science and everyday life - are conceived as constitutively aimed at yielding understanding. The book sketches a view of understanding that clarifies the nature of explanation, and, partly in the light of this relation, it provides a broad account of causal power on which psychological properties can possess it without being reducible to physical properties. The book concludes with an account of how, especially in the normative domain, explanations can be a priori. They may use a priori generalizations to provide understanding of what they explain, and they may clarify a priori propositions, or both. They may achieve these aims not only in logic and pure mathematics, but also in the realm of moral and other normative phenomena. The overall result is to show how philosophical understanding of both natural and normative phenomena is possible through integration with a scientific habit of mind that does not require a narrow empiricism in epistemology or a reductive naturalism in metaphysics or the theory of explanation. [Subject: Philosophy, Epistemology, Metaphysics, Action Theory, Psychology]. (shrink)

Given the pervasiveness of AI systems and their potential negative effects on people’s lives (especially among already marginalised groups), it becomes imperative to comprehend what goes on when an AI system generates a result, and based on what reasons, it is achieved. There are consistent technical efforts for making systems more “explainable” by reducing their opaqueness and increasing their interpretability and explainability. In this paper, we explore an alternative non-technical approach towards explainability that complement existing ones. Leaving aside technical, statistical, (...) or data-related issues, we focus on the very conceptual underpinnings of the design decisions made by developers and other stakeholders during the lifecycle of a machine learning project. For instance, the design and development of an app to track snoring to detect possible health risks presuppose some picture or another of “health”, which is a key notion that conceptually underpins the project. We take it as a premise that these key concepts are necessarily present during design and development, albeit perhaps tacitly. We argue that by providing “justificatory explanations” about how the team understands the relevant key concepts behind its design decisions, interested parties could gain valuable insights and make better sense of the workings and outcomes of systems. Using the concept of “health”, we illustrate how a particular understanding of it might influence decisions during the design and development stages of a machine learning project, and how making this explicit by incorporating it into ex-post explanations might increase the explanatory and justificatory power of these explanations. We posit that a greater conceptual awareness of the key concepts that underpin design and development decisions may be beneficial to any attempt to develop explainability methods. We recommend that “justificatory explanations” are provided as technical documentation. These are declarative statements that contain at its simplest: (1) a high-level account of the understanding of the relevant key concepts a team possess related to a project’s main domain, (2) how these understandings drive decision-making during the life-cycle stages, and (3) it gives reasons (which could be implicit in the account) that the person or persons doing the explanation consider to have plausible justificatory power for the decisions that were made during the project. (shrink)

Philosophers have cataloged a range of genealogical methods by which different sorts of normative conclusions can be established. Although such methods provide diverging ways of pursuing genealogical inquiry, they typically converge in eschewing historiographic methodology, in favor of a uniquely philosophical approach. In contrast, one genealogist who drew on historiographic methodology is Michel Foucault. This article presents the motivations and advantages of Foucault's genealogical use of such a methodology. It advances two mains claims. First, that Foucault's early 1970s work employs (...) a distinct genealogical method, which borrows from contemporary historiographic models of explanation to expand the range of objects that are proper to genealogical accounts of historical change. I demonstrate how Foucault modifies two central commitments of Nietzsche by broadening the dimensions of genealogical inquiry and explanation. Second, that historical method has normative relevance for genealogy, insofar as different historiographic choices can lead to different normative conclusions. I motivate this second claim by explaining how Foucault's multidimensional genealogical method expands both (a) the range of objects that are subject to evaluative assessment, and (b) the set of possible prescriptive recommendations that follow from such assessment. (shrink)

This paper is concerned with reasonings that purport to explain why certain organisms have certain traits by showing that their actual design is better than contrasting designs. Biologists call such reasonings 'functional explanations'. To avoid confusion with other uses of that phrase, I call them 'design explanations'. This paper discusses the structure of design explanations and how they contribute to scientific understanding. Design explanations are contrastive and often compare real organisms to hypothetical organisms that cannot possibly exist. They are (...) not causal but appeal to functional dependencies between an organism's different traits. These explanations point out that because an organism has certain traits, it cannot be alive if the trait to be explained were replaced by a specified alternative. They can be understood from a mechanistic point of view as revealing the constraints on what mechanisms can be alive. (shrink)

In this article (1) I extract from Brentano’s works (three) formal arguments against “genealogical explanations” of ethical claims. Such explanation can also be designated as “naturalism” (not his appellation); (2) I counter these arguments, by showing how genealogical explanations of even apodictic moral claims are logically possible (albeit only if certain unlikely, stringent conditions are met); (3) I show how Nietzsche’s ethics meets these stringent conditions, but evolutionary ethics does not. My more general thesis is that naturalism and intuitionism (...) in ethics need not be mutually incompatible. (shrink)

During the 1930s and 1940s, American physical organic chemists employed electronic theories of reaction mechanisms to construct models offering explanations of organic reactions. But two molecular rearrangements presented enormous challenges to model construction. The Claisen and Cope rearrangements were predominantly inaccessible to experimental investigation and they confounded explanation in theoretical terms. Drawing on the idea that models can be autonomous agents in the production of scientific knowledge, I argue that one group of models in particular were functionally autonomous from (...) the Hughes–Ingold theory. Cope and Hardy’s models of the Claisen and Cope rearrangements were resources for the exploration of the Hughes–Ingold theory that otherwise lacked explanatory power. By generating ‘how-possibly’ explanations, these models explained how these rearrangements could happen rather than why they did happen. Furthermore, although these models were apparently closely connected to theory in terms of their construction, I argue that partial autonomy issued in extra-logical factors concerning the attitudes of American chemists to the Hughes–Ingold theory. And in the absence of a complete theoretical hegemony, a degree of consensus was reached concerning modelling the Claisen rearrangement mechanism.Keywords: Models; Explanation; Physical organic chemistry; Rearrangements. (shrink)

Besides mechanistic explanations of phenomena, which have been seriously investigated in the last decade, biology and ecology also include explanations that pinpoint specific mathematical properties as explanatory of the explanandum under focus. Among these structural explanations, one finds topological explanations, and recent science pervasively relies on them. This reliance is especially due to the necessity to model large sets of data with no practical possibility to track the proper activities of all the numerous entities. The paper first defines topological explanations (...) and then explains why topological explanations and mechanisms are different in principle. Then it shows that they are pervasive both in the study of networks—whose importance has been increasingly acknowledged at each level of the biological hierarchy—and in contexts where the notion of selective neutrality is crucial; this allows me to capture the difference between mechanisms and topological explanations in terms of practical modelling practices. The rest of the paper investigates how in practice mechanisms and topologies are combined. They may be articulated in theoretical structures and explanatory strategies, first through a relation of constraint, second in interlevel theories, or they may condition each other. Finally, I explore how a particular model can integrate mechanistic informations, by focusing on the recent practice of merging networks in ecology and its consequences upon multiscale modelling. (shrink)

This paper examines explanations that turn on non-local geometrical facts about the space of possible configurations a system can occupy. I argue that it makes sense to contrast such explanations from “geometry of motion” with causal explanations. I also explore how my analysis of these explanations cuts across the distinction between kinematics and dynamics.

The idea at the core of the New Mechanical account of explanation can be summarized in the claim that explaining means showing ‘how things work’. This simple motto hints at three basic features of Mechanistic Explanation (ME): ME is an explanation-how, that implies the description of the processes underlying the phenomenon to be explained and of the entities that engage in such processes. These three elements trace a fundamental contrast with the view inherited from Hume and later (...) from strict logical empiricism (see Creath 2017), focused on epistemic and formal features of science and according to which issues concerning the kind of entities and processes that lie within a theory’s domain are extraneous to science and belong instead to ontology or metaphysics. Philosophers belonging to the new mechanical philosophy believe that the received view of scientific explanation (Hempel 2001), pivoting on the notion of law of nature, overshadows this insight. Since its origin in the 17th century, mechanical philosophy aimed to explain natural phenomena by reducing them to mechanisms. Traditional attempts to define the concept of mechanism involved the identification of a limited set of fundamental elements as, for instance, contact action, action at a distance, inertial motion (see e.g. Hesse 2005), and, more recently, transmission of a mark, or of a conserved quantity (see Frisch, this volume). The new mechanical philosophy rejects this austere characterization of mechanisms and mechanistic explanation and aim at providing a novel, philosophically rigorous explication of the concept of mechanism and of its role in scientific explanation and practice. ME has been adopted with profit in philosophy of special sciences (for instance in biomedical sciences, e.g. in the explanation of chemical transmission at synapses ((Machamer, Darden and Craver 2000), MDC henceforth); but also in social sciences, e.g. the three kinds of social mechanisms in Coleman’s analysis of Max Weber’s account of the role of the Protestant ethic in the growth of capitalism (Hedström and Swedberg 1998)), where exceptionless regularities are rarely ever found. In physics, it is generally possible to formulate explanations in law-based form, with the result that the plurality of explanatory forms might be overlooked. This should not come as a surprise, given that physics was the main inspiration for logical empiricists, and, in particular, Newtonian physics was a template for Hempel’s formulation of the covering law model. However, this situation is unfortunate, since, we will argue, knowing how things work is often part of the explanation of physical phenomena. In this chapter, we provide an introduction to the basic features of ME, with specific focus on its application to physics (section 1). The main part of the chapter is devoted to the defence of two theses: on the one hand, some domains of physics are not compatible with mechanistic reasoning and explanation (section 2); on the other hand, a comprehensive account of explanation in physics can’t dispense with ME (section 3). (shrink)

In this paper I shall adopt a possible reading of the notions of ‘explanatory indispensability’ and ‘genuine mathematical explanation in science’ on which the Enhanced Indispensability Argument proposed by Alan Baker is based. Furthermore, I shall propose two examples of mathematical explanation in science and I shall show that, whether the EIA-partisans accept the reading I suggest, they are easily caught in a dilemma. To escape this dilemma they need to adopt some account of explanation and offer (...) a plausible answer to the following ‘question of evidence’: What is a genuine mathematical explanation in empirical science and on what basis do we consider it as such? Finally, I shall suggest how a possible answer to the question of evidence might be given through a specific account of mathematical explanation in science. Nevertheless, the price of adopting this standpoint is that the genuineness of mathematical explanations of scientific facts turns out to be dependent on pragmatic constraints and therefore cannot be plugged in EIA and used to establish existential claims about mathematical objects. (shrink)

In this paper we argue that structural explanations are an effective way of explaining well known relativistic phenomena like length contraction and time dilation, and then try to understand how this can be possible by looking at the literature on scientific models. In particular, we ask whether and how a model like that provided by Minkowski spacetime can be said to represent the physical world, in such a way that it can successfully explain physical phenomena structurally. We conclude by claiming (...) that a partial isomorphic approach to scientific representation can supply an answer only if supplemented by a robust injection of pragmatic factors. (shrink)