What is the difference between explanation and understanding in science

These principles give rise to measures that can be used to judge the resemblance between a person's understanding and the scientific knowledge: 1 the number of plausible alternative explanations the person has considered; 2 the number of explanations that have been compared employing scientific criteria; 3 the scientific status of criteria used in the comparison, 4 the safety of the person's beliefs about explanations; 5 the accuracy of the person's beliefs about explanations, and 6 the variety of ways in which the person can employ explanatory information to achieve scientific goals.

The book has eight chapters. The basic ideas of the ESK model are presented in Chapter 1. Chapter 2 illustrates the model using a discussion of Bjorken scaling in Physics and comparing the ESK model to Henk de Regt's well-known account of understanding. Chapter 3 takes up the relation between understanding and ability.

Khalifa defends the position according to which both understanding and knowledge require the same abilities, thus blocking a popular strategy used to separate understanding and knowing explanatory information.

His argumentative strategy is two-fold. He begins by arguing that knowing an explanation requires some abilities, and then proceeds to show that these are the same as required for understanding in the ESK model. Chapter 4 discusses the awkwardly named issue of objectual understanding. This notion refers basically to mastery of some subject matter. Khalifa argues that objectual understanding does not require more than explanatory understanding, but simply an abundance of explanatory understanding.

Accordingly, the ESK model can cope with intuitions rising from objectual understanding. Peter Lipton's provocative claim that there can be understanding without explanation is the topic of Chapter 5.

Khalifa reconstructs Lipton's defense of this claim in great detail and argues that none of the considerations he raises poses a challenge for the ESK model.

To deal with intuitions that make Lipton's argument appealing, he introduces the notion of proto-understanding. A person has proto-understanding when she does not yet have proper understanding, but does have some grasp of the explanatory role of some piece of explanatory information.

Furthermore, he argues, contrary to Lipton, that explanations do not have to be linguistic. This makes room for "tacit" understanding that still counts as explanatory understanding.

Khalifa's critical discussion is valuable, as it has become a commonplace to take Lipton's arguments at face value. Chapter 6 tackles the relation between understanding and true belief.

Non-factivists, according to whom understanding why p does not require belief in true or approximately true explanations of p , pose a challenge.

Their arguments come in two forms. First, there is the historical argument that points to examples of past scientists who believed in false theories but nevertheless seemed to have some understanding of the phenomenon. Second, there are arguments that suggest that while idealized theories are literally untrue, they are still important source of understanding in science. In both cases, Khalifa argues that it is possible to treat these cases selectively, or to appeal to proto-understanding, so that the ESK model is saved.

Chapter 7 discusses the compatibility of luck and understanding. Khalifa argues that while some understanding might be lucky, this does not constitute a problem for the ESK model, because SEE principles guarantee that luck diminishes understanding.

I conclude by showing how the answers developed to i-iii interface in an interesting way with Virtue Perspectivism as an anti-sceptical strategy. Cartesian Skepticism in Epistemology. Skepticism, Misc in Epistemology.

Virtue Epistemology in Epistemology. Remove from this list Direct download 6 more. Science has not only produced a vast amount of knowledge about a wide range of phenomena, it has also enhanced our understanding of these phenomena.

Indeed, understanding can be regarded as one of the central aims of science. But what exactly is it to understand phenomena scientifically, and how can scientific understanding be achieved? What is the difference between scientific knowledge and scientific understanding? These questions are hotly debated in contemporary epistemology and philosophy of science. While philosophers have long regarded This chapter reviews the current debate on scientific understanding.

It presents the main philosophical accounts of scientific understanding and discusses topical issues such as the relation between understanding, truth and knowledge, the phenomenology of understanding, and the role of understanding in scientific progress.

Theoretical Virtues in General Philosophy of Science. To understand something involves some sort of commitment to a set of propositions comprising an account of the understood phenomenon. Some take this commitment to be a species of belief; others, such as Elgin and I, take it to be a kind of cognitive policy. In particular, appealing to lessons from the This strongly suggests that the relevant type of commitment is sometimes acceptable in the absence of epistemic justification for belief, which in turn implies that understanding does not require justification in the traditional sense.

The paper goes on to develop a new probabilistic model of acceptability, based on the idea that the maximally informative accounts of the understood phenomenon should be optimally probable. Formal Epistemology, Misc in Epistemology. Probabilistic Puzzles, Misc in Philosophy of Probability. Yet, these discussions have suffered from confusions about the relevant science, as well as conceptual confusions. Addressing this example, we shall argue that the ideal gas law is best Along the way, we indicate where earlier discussions have gone astray, and highlight how a naturalistic approach furnishes more nuanced normative theses about the interaction of rationality, understanding, and epistemic value.

I draw upon speech act theory to understand the speech acts appropriate to the multiple aims of scientific practice and the role of nonepistemic values in evaluating speech acts made relative to those aims.

First, I look at work that distinguishes explaining from describing within scientific practices. I then argue speech act theory provides a framework to make sense of how explaining, describing, and other acts have different felicity conditions. Finally, I argue that if explaining aims to convey understanding to Science and Values in General Philosophy of Science. Speech Acts in Philosophy of Language. It first outlines one way of interpreting the distinction, on which it is connected to the distinction between singular and general causal claims.

It then discusses one reason for thinking that understanding has an essential role to play in psychiatry: Not achieving at least some level of understanding in the context of dealing with psychiatric patients would constitute a particular kind of epistemic failure—a failure Drawing on some ideas recently put forward by Kenneth Kendler and John Campbell, it also illustrates the particular kind of understanding that is crucial in this context.

Many praise science for its systematic drive to objectivity. But scientific objectivity is in fact a species of objectivity in a broader sense, which extends to aesthetic experience and broadly artistic creativity. Objectivity should be understood as outwardness, or receptivity to basic features of the world.

Scientific objectivity is receptivity to basic features of the world specifically by adopting their 'point of view'. It is not a 'view from nowhere', in the sense of a globally- or universally-valid perspective. Nor is Scientific objectivity is a view from causally-basic phenomena that are often totally impersonal—like gravity, from whose standpoint we see objective spatiotemporal relations. By contrast to this objective scientific view from causally-basic forces onto the objects they impact, a broadly poetic kind of objectivity involves adopting a view directly onto basic forces, like loci of aesthetic impact, ethical value, or causal power.

Poetic understanding allows us to directly apprehend nature as impactful, whereas science only gives us unconscious insight into basic forces, by cognitively imitating their physical impact. This framework helps to explain modern 'disenchantment', as it bears on both the value and the limits of science.

At a metaphysical level, this approach also radically extends Nietzsche's view that theories and artworks are 'perspectival' expressions of their creators' drives.

Nietzsche is right to treat the outlet of strong human drives in acts of artistic or philosophical creativity as just one among many higher modes of 'will to power' in nature, many of which are totally impersonal.

But he is still too focused on self-expression, or willing one's own power. In fact, objective science and art involve external forces' expression in and through us, not just us expressing our own powers.

And Nietzsche's vitalistic 'will to power' must be replaced by a basic ontology that better accommodates inorganic phenomena, like the 'cold' order and precision of celestial motions. Thus I work to de-anthropomorphize and de-organicize post-Kantian notions of will and creative development, while preserving for force the primary ontological and evaluative status that theorists from Schiller and Goethe to Emerson and Nietzsche attributed to willful striving or to life.

Nature in Applied Ethics. Philosophy of Physical Science. Reality in Metaphysics. Subjectivity and Objectivity in Epistemology. Value in Value Theory, Miscellaneous. Remove from this list. This paper written as a dialogue between two interlocutors, Julie and a Student, deals with Understanding and its role in the social sciences. The fictional dialogue takes place in Hannover, Germany, and the interlocutors are exchanging arguments about Verstehen and how it should be conceptualized in the philosophy of the social sciences.

A range of different approaches is discussed and a naturalistic strategy emerges as a defensible alternative. Hermeneutics in Continental Philosophy. Interpretation in Philosophy of Language. Philosophy of Social Science. In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI.

Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it.

After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability.

This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature. Remove from this list Direct download 4 more. Because idealizations frequently advance scientific understanding, many claim that falsehoods play an epistemic role. In this paper, we argue that these positions greatly overstate idealiza 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 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. Mathematical Explanation in General Philosophy of Science. One puzzle concerning highly idealized models is whether they explain. 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 Models, in turn, simply provide evidence for these claims. Chrysostomos Mantzavinos , Explanatory Pluralism. Explanatory Pluralism in General Philosophy of Science. Social Sciences, Misc in Social Sciences. This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon.

I compare this account with accounts of scientific understanding that explicate understanding in terms of having an explanation of the understood phenomenon. I discuss three distinct types of cases in which scientific understanding does not amount to possessing an explanation of any kind, and argue that the proposed model-based account can accommodate these cases while still retaining a strong link between understanding and explanation.

Belief Revision, Misc in Epistemology. The tremendous philosophical focus on how to characterize explanatory metaphysical dependence has eclipsed a number of other unresolved issued about scientific explanation. The purpose of this paper is taxonomical. I will outline a number of other questions about the nature of explanation and its role in science—eight, to be precise—and argue that each is independent.

All of these topics have received some philosophical attention, but none nearly so much as it deserves. Furthermore, existing views on these topics have been obscured Philosophical analysis of scientific explanation would be much improved by attending more carefully to these, and probably still other, elements of an account of explanation.

Can mathematics contribute to our understanding of physical phenomena? One way to try to answer this question is by getting involved in the recent philosophical dispute about the existence of mathematical explanations of physical phenomena. If there is such a thing, given the relation between explanation and understanding, we can say that there is an affirmative answer to our question.

But what if we do not agree that mathematics can play an explanatory role in science? Can we still consider that My main aim here is to give an account that takes mathematics, in some of the cases discussed in the literature, as contributing to our understanding of physical phenomena despite not being explanatory. Indispensability Arguments in Mathematics in Philosophy of Mathematics. Mathematical Platonism in Philosophy of Mathematics. Factivism is the view that understanding why a natural phenomenon takes place must rest exclusively on truths.

One of the arguments for nonfactivism—the opposite view, that falsehoods can play principal roles in producing understanding—relies on our inclination to say that past, false, now superseded but still important scientific theories do provide understanding.

In this paper, my aim is to articulate what I take to be an interesting point that has yet to be discussed: the natural way in which nonfactivism fits I contend that unificationism gives non-factivists a better framework to uphold their position.

The articulation of an overarching account of scientific explanation has long been a central preoccupation for the philosophers of science. Although a while ago the literature was dominated by two approaches—a causal account and a unificationist account—today the consensus seems to be that the causal account has won. Since it is uncontroversial in the explanation and understanding literature that explanations afford understanding e. Even recent prominent accounts of causal explanation are now more liberal.

For example, despite the fact that their main focus is on causal explanation, Woodward , and Strevens , sec. Footnote 4. The second tenet of narrow KAU has been more resistant to change. However, I believe it ought, like the first tenet, to be rejected because it does not satisfy the second desideratum.

In the remainder of this paper, I first spell out in more details what the second tenet of narrow KAU amounts to. How-possibly explanations present a challenge to narrow KAU because they do not explain according to it, and yet appear to afford understanding.

I will then propose what I call the broad knowledge account of understanding broad KAU hereafter that builds on a framework developed by Reutlinger Broad KAU, I hold, satisfies the two desiderata stated earlier and hence provides a normatively and descriptively compelling account of understanding.

If the first tenet of narrow KAU is more controversial, if not debunked, the second is more widely held. Proponents of this view consider that explanations are the only legitimate source of understanding, for instance:.

The resulting objectivist, ontic, account, in generic form, states that scientific understanding is the state produced, and only produced, by grasping a true explanation Trout , An individual has scientific understanding of a phenomenon just in case they grasp a correct scientific explanation of that phenomenon Strevens , Footnote 5. According to Trout, it is important to separate the sense of understanding, which can be a misleading phenomenology, from the genuine understanding one can only obtain when being in possession of a true explanation.

For Khalifa, having scientific understanding is a matter of having explanatory knowledge, i. For him, the epistemology of explanation precedes and guides the epistemology of understanding. One understands why something is the case, according to Strevens, when one not only grasps a state of affairs, but also its correct explanation.

It is important to bear in mind that Strevens and Trout, in particular, do not claim that knowing an explanation is sufficient for understanding. This is why Strevens , does not reduce understanding to explanation. However, grasping can be related to knowing. Indeed, as Strevens , , fn. In short, perhaps knowing an explanation is not sufficient—one may need to grasp it—, but to grasp a true explanation one may need to know it.

Footnote 7 That said, the important point is that one needs to stand in the appropriate epistemic relation—e. Explanations are the bearer of the information that affords understanding and without an explanation there is no understanding. One consequence of these views is to downplay the import of understanding as a separate and useful notion.

If this is correct, then it indeed makes little sense to spell out the epistemic contribution of theoretical models in terms of understanding since explanation is in fact the key concept.

It also means the epistemology of explanation may not provide all the normative and descriptive criteria we need when analysing science. An explanation is essentially just a set of propositions that connects an explanans to an explanandum in the right way Strevens It is uncontroversial that explanations provide the right kind of propositions and structure. Put differently, are there sets of propositions that convey information conducive to understanding, but that do not satisfy the conditions for explanation?

Footnote 8 His strategy is to point out ways we can obtain the same cognitive benefits e. According to him, understanding should therefore be identified with the benefits explanations provide rather than with the explanations themselves. How-possibly explanations HPEs hereafter are to be contrasted with how-actually explanations HAEs hereafter , or explanations simpliciter.

A terminological disclaimer is now essential. Were it the case, then arguing as I shall do that having an explanation is not necessary because HPEs may afford understanding would be beside the point. For if having an HPE would amount to having an explanation, then it would say nothing about the necessity of explanation for understanding. Contemporary characterizations of HPEs are very similar to what Hempel called potential explanations Bokulich In HPEs, what constitutes the explanans is not true or not known to be true.

HAEs, on the other hand, give a correct explanatory account of the explanandum. Footnote 10 For instance, I could, using phlogiston theory, provide an internally correct explanation of the phenomenon of combustion. However, the theory does not actually explain combustion because there is no such entity as phlogiston. The explanation is false and does not meet the external conditions of adequacy.

Footnote 11 To give another example, Ptolemaic astronomy provided an internally correct explanation of the motion of the planets using a geocentric cosmology and epicycles. But since the theory is false because it depicts, among other things, the earth at the centre of the solar system and planets as moving along epicycles, it is not externally correct and thus not a HAE. HAEs may also be approximately true. Or HAEs can also vary in their explanatory power, scope, or breadth see, e.

Strevens , , in his defence of the necessity of explanation, also acknowledges that explanatory correctness comes in degree. These are the cases that are of special interest for our consideration of the necessity of explanation. The textual evidence of the previous section makes this plain. Strevens explicitly denies that potential explanations—or HPEs—afford understanding of phenomena. This requirement is clearly not satisfied by most cases of HPEs discussed in the literature since they depict either false—or not known to be true—explanantia or explananda.

The issue therefore does not hinge on whether HPEs are a species of explanation. The issue is rather whether a HAE is necessary for understanding. According to proponents of the second tenet of narrow KAU, it is. Yet, that HAEs are not necessary for understanding is precisely what some practitioners maintain and what contemporary philosophical discussions of theoretical modelling show. I examine here cases where HPEs provide understanding without actually explaining.

Prior to the checkerboard model, social scientists believed that only strong discriminatory preferences—i. The model showed that it was possible that preferences for not being in a minority status could also produce the same pattern of segregation. This result has proven to be very robust across changes of assumptions Muldoon et al. The checkerboard model is usually interpreted as having provided a HPE of residential segregation e. The model does not make any specific claim about the actual mechanism producing instances of residential segregation.

More precisely, it is not a HAE of segregation since we do not know whether it explains any actual instance of that phenomenon. Even though the model represents phenomena in a highly stylized manner and despite that the mechanism it depicts is not known to be actual, it still appears to provide causal knowledge about the phenomenon. Using the model, we know that if the mechanism were true, under suitable conditions residential segregation could be brought about. Knowing that some causal factors may bring about residential segregation improves our understanding of the phenomenon even though we do not know what actually causes it.

It may do it in various ways. All these accounts suggest the checkerboard model, interpreted as providing a HPE, can afford understanding of real-world phenomena. Another widely discussed example in the literature on HPEs e.

The Hawk-Dove is a game-theoretic model to study behaviour in situation of conflicts over a shareable resource. The model shows that restraint in contest between individuals of the same species benefit not only the species as a whole the group , but also the individuals.

It is not necessary to resort to group selection to explain that behaviour, individual selection is sufficient. In the eyes of practitioners, the Hawk-Dove model contributed to our understanding of animal competition.

Like the checkerboard model, it also should not be viewed as a HAE. Their goal was not to provide a HAE of animal contest, but to study whether it could have evolved via individual selection. It does not answer a how-actually question, but instead aims to answer a how-possibly one, namely how individual selection could bring about restraint in combat see also Rice ; Rohwer and Rice That this phenomenon may be the result of individual selection does not imply it is actually the case.

Nonetheless, Rohwer and Rice argue that it affords understanding because it justifies the true belief that the restraint phenomenon is compatible with individual selection. According to them, this belief is relevant to answer the question why this phenomenon occurs. Even though they do not satisfy the typical empirical external conditions associated with HAEs, both the judgement of practitioners and philosophical analyses of specific cases of theoretical modelling lead to the conclusion that HPEs can provide understanding.

Proponents of the second tenet of narrow KAU could dispute this conclusion on two grounds. Or, they could deny that HPEs can afford understanding. However, neither horn of the dilemma is readily available to them. Reydon , for instance, argues that what Forber calls global HPEs are actually genuine explanations of type-level phenomena. Footnote 13 Since the point of narrow KAU is precisely that only HAEs can provide understanding, this would be a successful way of defusing the claim that HPEs can afford understanding.

As I already pointed out, Strevens stresses that an explanation must be externally correct, that is, it must contain a true explanans, in order to afford understanding. HPEs, by definition, do not satisfy these criteria because either the explanans or the explanandum is false or not known to be true.

Furthermore, there are clearly cases—e. Secondly, rejecting the claim that some HPEs afford understanding implies that exemplary cases of theoretical modelling are epistemically suspect. The checkerboard and Hawk-Dove models have been very influential and, most importantly, have been considered to afford cognitive benefits in the form of understanding. That many contemporary philosophical accounts as well as practitioners consider some HPEs afford understanding is strong evidence that they actually do so.

As far as practice is correctly described, the burden of proof should be on those philosophical accounts that want to deny HPEs can afford understanding, not on practitioners. The checkerboard model, for instance, affects our confidence in the thesis that only strong discriminatory preferences can bring about residential segregation. Fumagalli may be right as far as minimal models thus defined are concerned.

But this does not imply that HPEs need be minimal models. Actually, the mistake seems to rest in regarding the checkerboard and the Hawk-Dove models as minimal.

The checkerboard model may afford understanding precisely in virtue of some similarity or resemblance between the world and the model Sugden ; Ylikoski and Aydinonat To consider that the mechanism depicted by the checkerboard model is causally possible indeed appears to require at least a minimal assessment of its similarity with the actual world. But what is at stake is not whether HPEs are a species of explanations or not, but whether they afford understanding.

Reydon, for instance, does not specifically address this issue. HPEs may sometimes serve heuristic purposes, but other times they may also afford understanding. The checkerboard model does both. It suggests a novel empirical hypothesis that can orient future research, while also allowing to answer various questions about residential segregation.

The two functions are not necessarily mutually exclusive. There might thus be cases of HPEs that do not improve our understanding. Descriptively, denying this capacity to HPEs is infelicitous as actual practitioners consider they afford understanding. However, the normative point may still hold, viz. That said, proponents of narrow KAU would need to offer a plausible argument for why we should consider they are indeed mistaken. Arguments of that kind are currently lacking.

If HPEs may afford understanding, as it is plausible they sometimes do, then narrow KAU faces a serious objection: it appears that having an explanation, in the sense of a HAE, is not necessary for understanding.

The two tenets of narrow KAU are untenable. First, the literature on non-causal explanations provides good reasons to believe that causal knowledge is not necessary for understanding. Second, as I have argued, there are cases of theoretical modelling that do not provide explanations and yet, according to practitioners and philosophers, afford understanding.

This indicates that having an explanation is also not necessary for understanding. Therefore, if we want our epistemology of understanding to apply to cases of theoretical modelling, then we need an alternative to narrow KAU, in general, and to its second tenet, in particular. Broad KAU, I contend, provides an alternative epistemology of understanding that fulfils the desiderata set forth in the introduction. In particular, accounting for scientific practice should not come at the cost of blurring the difference between illusory and genuine understanding.

It should also make salient the relationship between explanation and understanding. Broad KAU 1 broadens the knowledge—i. Broad KAU thus challenges that causal knowledge and that having an explanation are necessary for understanding. This is because it already embraces one element of broad KAU, namely it welcomes non-causal knowledge. According to Reutlinger, a relation between an explanans and an explanandum is explanatory iff it satisfies the following conditions , :.

Veridicality condition : Generalizations G 1 ,…, G m , the auxiliary statements S 1 ,…, S n , and the explanandum statement E must all be approximately true or be well confirmed.

G 1 ,…, G m support at least one counterfactual between S 1 ,…, S n and E. The conditions he states are those that explanations i. Accordingly, his theory leaves out the second tenet of broad KAU, viz. The first step that will allow us to filter out understanding from explanation is by identifying in virtue of what explanations provide understanding. One understands when one obtains information about counterfactual dependence that allows to answer these questions. We thus see that what is key to understanding is the information some propositions provide, information that is closely related to the satisfaction of the dependency condition.

Broad KAU expands on the idea that it is essentially information about counterfactual dependence that contributes to understanding, regardless of whether it is causal or not, and, crucially, regardless of whether it is obtained through an explanation or not. Having an explanation implies that certain relations of dependence actually obtain. The challenge for broad KAU, therefore, is to show that having an explanation is not necessary for satisfying the dependency condition. Put differently, how could the dependency condition, which appears to be essential for understanding, be satisfied without the veridicality condition?

Reutlinger proposes an account of explanation and explanations are usually taken to be factive, i. The function of the veridicality condition is precisely to ensure the factivity of explanation. False generalizations would not explain an explanandum and true generalizations would not explain an explanandum that is known to be false. For a set of propositions to count as an explanation, both the explanans and the explanandum must be true.

But what if the veridicality condition is not satisfied? What if the generalizations are false or not known to be true? What if the explanans or explanandum are merely possible? Put differently, what if we have a HPE? However, if we accept the compelling evidence that HPEs may provide understanding despite the fact that they contain false explanantia or explananda, then this suggests that the veridicality condition is not necessary for understanding.

Since we can obtain understanding from false explanantia or explananda, the veridicality condition may be necessary for explanation, but not for understanding. This indicates that we can disentangle the condition for actual explanation in Reutlinger from the core constituents that specifically concern understanding.

We can achieve this result, I submit, simply by amending the veridicality condition. Accordingly, we can modify the theory of explanation to achieve a theory of understanding. I propose that the relationship between an explanans and an explanandum affords understanding iff:. Possibility condition : The generalizations G 1 ,…, G m , the auxiliary statements S 1 ,…, S n , or the explanandum statement E are im possible according to the relevant modal interpretation and epistemic goal.

In other words, I propose to amend the veridicality condition for what I call the possibility condition. Footnote 14 Essentially, it relaxes the explanatory requirement that the explanans and explanandum be actual. What is actual is possible, but what is possible is not necessarily actual. Explanations require that all its constituents are actual, but not understanding.

They show how an event could possibly occur or how known processes can lead to different outcomes. This, in turn, affords understanding of real-world phenomena.

For instance, the checkerboard model exhibits a possible causal mechanism—possible causal generalization—that can bring about residential segregation, which is an actual phenomenon.

However, the model itself does not explain residential segregation because we do not know whether it is actually that mechanism that produces segregation.

Yet, the checkerboard model affords understanding by virtue of showing how it could be brought about. More generally, it allows to make various counterfactual inferences about the phenomenon of residential segregation Kuorikoski and Ylikoski ; Ylikoski and Aydinonat Despite the fact that it does not satisfy the veridicality condition, it does satisfy the possibility and the dependency conditions.

If it were the case that preferences for not living in a minority status cause the phenomenon, then we would have an explanation. We would also of course understand. But we can also understand even when we lack an explanation insofar as the dependency condition is satisfied. Many HPEs, for instance the checkerboard model, display possible causal dependence. However, other cases may appeal to different modalities e.

In mathematical explanations, the relevant modality is mathematical or logical. The truth or falsehood of possibility claims is reached on the background of the suitable facts, depending both on the modality and on the epistemic goal. To say that something is logically possible does not imply that it is also causally possible. The same constraints do not apply. For the purpose of scientific understanding, causal, epistemic, or nomic possibility are perhaps the most relevant types.

Broad KAU, however, does not rule out a priori the sorts of possibilities or relations of dependence that may afford understanding. To make this clearer, let us use an example discussed by Strevens , that of the young earth creationists.

They purportedly explain the formation of the Grand Canyon by citing one massive flood occurring over a short period of time. The flood would have laid down most of the different rock layers and the flood would have dug the canyon itself. The great flood explanation is false, i. The Grand Canyon was actually formed by other geological processes, namely by sediment accumulation, plate movement, and slow erosion.

Footnote But does relaxing the veridicality condition imply that comparable cases may satisfy the possibility condition and thus afford understanding? If so, it may imply that the possibility condition is too liberal since utterly wrong-headed HPEs could afford understanding. Since one desideratum of an account of understanding is to allow demarcation of illusory from genuine understanding, this would be an unwelcome implication of broad KAU. Again, offering a descriptively adequate epistemology of understanding should not make it too easy to obtain.

Here, it is important to take into consideration what is the relevant modal interpretation for a given epistemic purpose. This allows to clarify how exactly a HPE contributes, or not, to understanding. One wants to know how the Grand Canyon could have possibly been causally formed. In other words, the great flood explanation does not qualify as being a HPE and is not an appropriate answer to the how-possible question above. By that, I mean that the causal generalization linking the flood to the canyon is not only inconsistent with what we know about the causal history of this specific case, but also with other more general causal facts.

It conflicts with the fact that geological processes forming canyons operate over long periods of time, not during one year. And while floods may produce certain geological formations e. It also contradicts scientific facts about the age of the earth and of the Grand Canyon. Or it can hardly account for the presence of fossils in the different rock layers. In a nutshell, it just could not have happened the way the young earth creationists claim.

The great flood explanation thus does not fulfil the possibility condition since the how-possibly request calls for information about causal possibility, which the young earth creationists do not provide. It also does not satisfy the dependency condition because the generalization linking floods and the Grand Canyon does not support the right kind of true counterfactuals. However, that counterfactual is false.

Absent changes to these other processes, the flood would not have brought about the Grand Canyon. All that said, since the possibility condition allows for im possible explanantia and explananda, does this mean the great flood generalization would, on reflection, afford understanding?

It could, but only in a specific set of circumstances. Let us suppose that we did not know that a flood during a very short period of time could have dug the canyon and laid down the rock layers, but that we did know that the actual explanation involved erosion, sediment accumulation, and plate movement.

One question we may ask ourselves is whether other causes, like the flood, could have brought it about. We may thus build a model or simulation in which we try to generate the Grand Canyon with an intense flood as the main causal driving force.