Este artículo presenta a Weber y Habermas como los umbrales o polos de una modernidad que tiene al progreso como horizonte teórico-práctico. El diagnóstico weberiano sobre la modernidad y su proceso de desencantamiento del mundo y la injustificada reducción de la actividad racional a una actividad utilitario-estratégica desprovista de su carácter veritativo y de su orientación valórica, Habermas la utiliza para justificar su propuesta teórico-crítica respecto a la modernidad y la "paradoja de la racionalización", distinguiendo "sistema" y "mundo vital". Aquí (...) "desencantamiento del mundo" y "consenso del proyecto de lamodernidad", se encuentranThis article presents Weber and Habermas like the thresholds or poles of a modernity that has to the progress as theoretical- practical horizon. The diagnosis weberiano on the modernity and his process of disenchantment of the world and the unjustified reduction of the rational activity to a utilitarian-strategic activity devoid of his character of truth, Habermas uses to justify his theoretical-critical offerwith regard to themodernity and the "paradox of the rationalization", distinguishing "system" and "vital world". Here "disenchantment of the world" and "consensus of the project of the modernity", they are. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide (...) understanding misguided? In this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

If understanding is factive, the propositions that express an understanding are true. I argue that a factive conception of understanding is unduly restrictive. It neither reflects our practices in ascribing understanding nor does justice to contemporary science. For science uses idealizations and models that do not mirror the facts. Strictly speaking, they are false. By appeal to exemplification, I devise a more generous, flexible conception of understanding that accommodates science, reflects our practices, and shows a (...) sufficient but not slavish sensitivity to the facts. (shrink)

Scientific understanding, this paper argues, can be analyzed entirely in terms of a mental act of “grasping” and a notion of explanation. To understand why a phenomenon occurs is to grasp a correct explanation of the phenomenon. To understand a scientific theory is to be able to construct, or at least to grasp, a range of potential explanations in which that theory accounts for other phenomena. There is no route to scientific understanding, then, that does not go by (...) way of scientific explanation. (shrink)

Moral understanding is a valuable epistemic and moral good. I argue that moral understanding is the ability to know right from wrong. I defend the account against challenges from nonreductionists, such as Alison Hills, who argue that moral understanding is distinct from moral knowledge. Moral understanding, she suggests, is constituted by a set of abilities: to give and follow moral explanations and to draw moral conclusions. I argue that Hills’s account rests on too narrow a conception (...) of moral understanding. Among other things, it cannot account for the importance of first-personal experience for achieving moral understanding. (shrink)

Moral understanding is a species of knowledge. Understanding why an action is wrong, for example, amounts to knowing why the action is wrong. The claim that moral understanding is immune to luck while moral knowledge is not does not withstand scrutiny; nor does the idea that there is something deep about understanding for there are different degrees of understanding. It is also mistaken to suppose that grasping is a distinct psychological state that accompanies understanding. (...) To understand why something is the case is to grasp or see why something is the case and grasping and seeing are ways of knowing. (shrink)

What is the primary intellectual aim of philosophy? The standard view is that philosophy aims to provide true answers to philosophical questions. But if our aim is to settle controversy by answering such questions, our discipline is an embarrassing failure. Moreover, taking philosophy to aim at providing true answers to these questions leads to a variety of puzzles: How do we account for philosophical expertise? How is philosophical progress possible? Why do job search committees not care about the truth or (...) falsity of a candidate’s philosophical views? We argue that philosophy does not aim at discovering true answers to philosophical questions. Instead, its primary intellectual aim is understanding. We argue that many familiar aspects of philosophy become intelligible once we accept this hypothesis. (shrink)

Understanding is a central aim of science and highly important in present-day society. But what precisely is scientific understanding and how can it be achieved? This book answers these questions, through philosophical analysis and historical case studies, and presents a philosophical theory of scientific understanding that highlights its contextual nature.

In recent years there has been a resurgence of interest among epistemologists in the nature of understanding, with some authors arguing that understanding should replace knowledge as the primary focus of epistemology. But what is understanding? According to what is often called the standard view, understanding is a species of knowledge. Although this view has recently been challenged in various ways, even the critics of the standard view have assumed that understanding requires justification and belief. (...) I argue that it requires neither. If sound, these arguments have important upshots not only for the nature of understanding, but also for its distinctive epistemic value and its role in contemporary epistemology. (shrink)

Claims pertaining to understanding are made in a variety of contexts and ways. As a result, few in the philosophical literature have made an attempt to precisely characterize the state that is y understanding x. This paper builds an account that does just that. The account is motivated by two main observations. First, understanding x is somehow related to being able to manipulate x. Second, understanding is a mental phenomenon, and so what manipulations are required to (...) be an understander must only be mental manipulations. Combining these two insights, the paper builds an account (URM) of understanding as a certain representational capacity—specifically, understanding x involves possessing a representation of x that could be manipulated in useful ways. By tying understanding to representation, the account correctly identifies that understanding is a fundamentally cognitive achievement. However, by also demanding that which representations count as understanding-conferring be determined by their practical effects, URM captures the insight that understanding is vitally connected to practice. URM is fully general, and can apply equally well to understanding states of affairs, understanding events, and even understanding people and works of art. The ultimate test of URM is its applicability in actual scientific and philosophical discourse. To that end the paper discusses the importance of understanding in the philosophy of science, psychology, and computer science. (shrink)

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. This paper takes a step back from debates about the nature of understanding and asks when this commitment involved in understanding is epistemically appropriate, or ‘acceptable’ in Elgin’s terminology. In particular, appealing to lessons (...) from the lottery and preface paradoxes, it is argued that this type of commitment is sometimes acceptable even when it would be rational to assign arbitrarily low probabilities to the relevant propositions. 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. Interestingly, this probabilistic model ends up being similar in important ways to Elgin’s proposal to analyze the acceptability of such commitments in terms of ‘reflective equilibrium’. (shrink)

The literature on the nature of understanding can be divided into two broad camps. Explanationists believe that it is knowledge of explanations that is key to understanding. In contrast, their manipulationist rivals maintain that understanding essentially involves an ability to manipulate certain representations. The aim of this paper is to provide a novel knowledge based account of understanding. More specifically, it proposes an account of maximal understanding of a given phenomenon in terms of fully comprehensive (...) and maximally well-connected knowledge of it and of degrees of understanding in terms of approximations to such knowledge. It is completed by a contextualist semantics for outright attributions of understanding according to which an attribution of understanding is true of one just in case one knows enough about it to perform some contextually determined task. It is argued that this account has an edge over both its explanationist and manipulationist competitors. (shrink)

Science is replete with falsehoods that epistemically facilitate understanding by virtue of being the very falsehoods they are. In view of this puzzling fact, some have relaxed the truth requirement on understanding. I offer a factive view of understanding that fully accommodates the puzzling fact in four steps: (i) I argue that the question how these falsehoods are related to the phenomenon to be understood and the question how they figure into the content of understanding it (...) are independent. (ii) I argue that the falsehoods do not figure into the understanding’s content by being elements of its periphery or core. (iii) Drawing lessons from case studies, I argue that the falsehoods merely enable understanding. When working with such falsehoods, only the truths we extract from them are elements of the content of our understanding. (iv) I argue that the extraction view is compatible with the thesis that falsehoods can have an epistemic value by virtue of being the very falsehoods they are. (shrink)

What is the relationship between understanding and knowing? This paper offers a defence of reductionism about understanding: the view that instances of understanding reduce to instances of knowing. I argue that knowing is both necessary and sufficient for understanding. I then outline some advantages of reductionism.

A model of writing in cognitive development, Understanding the Representational Mind synthesizes the burgeoning literature on the child’s theory of mind to provide an integrated account of children’s understanding of representational and mental processes, which is crucial in their acquisition of our commonsense psychology. Perner describes experimental work on children’s acquisition of a theory of mind and representation, offers a theoretical account of this acquisition, and gives examples of how the increased sophistication in children’s theory of mind improves (...) their understanding of social interaction and how, in the case of autistic children, an impairment results in social ineptitude. He analyzes the concepts of representation and metarepresentation as they appear in current discussion in the philosophy of cognitive science and explains how the unfolding of mental representation enables infants to comprehend change over time, engage in pretence, and use representational systems like pictures and language. Perner goes on to show that around age four children become able to understand the representational nature of pictures and language and to distinguish appearance from reality. Introducing basic distinctions in philosophy of mind for characterizing the mental, Perner discusses differences in how commonsense and cognitive psychology view the mind. Tracing the onset of a commonsense psychology in the social and emotional awareness of early infancy, he reveals how the child begins to take a cognitive, representational view of the mind with repercussions for children’s episodic memory, self control, and their ability to engage in deception. Perner concludes by describing the observed developmental changes as a case of theory change And contrasts his thesis with competing proposals. Josef Perner is Lecturer in Experimental Psychology at Sussex University, Brighton, England. (shrink)

Understanding enjoys a special kind of value, one not held by lesser epistemic states such as knowledge and true belief. I explain the value of understanding via a seemingly unrelated topic, the implausibility of veritism. Veritism holds that true belief is the sole ultimate epistemic good and all other epistemic goods derive their value from the epistemic value of true belief. Veritism entails that if you have a true belief that p, you have all the epistemic good qua (...) p. Veritism is a plausible and widely held view; I argue that it is untenable. I argue that integration among beliefs possesses epistemic value independent from the good of true belief, and so has value veritism cannot account for. I argue further that this integration among beliefs comprises the distinctive epistemic value of understanding. (shrink)

This entry offers a critical overview of the contemporary literature on understanding, especially in epistemology and the philosophy of science.

Although several accounts of scientific understanding exist, the concept of understanding in relation to technology remains underexplored. This paper addresses this gap by proposing a philosophical account of technological understanding—the type of understanding that is required for and reflected by successfully designing and using technological artefacts. We develop this notion by building on the concept of scientific understanding. Drawing on parallels between science and technology, and specifically between scientific theories and technological artefacts, we extend the (...) idea of scientific understanding into the realm of technology. We argue that, just as scientific understanding involves the ability to explain a phenomenon using a theory, technological understanding involves the ability to use a technological artefact to realise a practical aim. Technological understanding can thus be considered a specific application of knowledge: it encompasses the cognitive skill of recognising how a practical aim can be achieved by using a technological artefact. In a context of design, this general notion of technological understanding is specified as the ability to design an artefact that, by producing a phenomenon through its physical structure, achieves the intended aim. We illustrate our concept of technological understanding through two running examples: magnetic resonance imaging (MRI) and superconducting quantum computers. Our account highlights the epistemic dimension of engaging with technology and, by allowing for context-dependent specifications, provides guidance for testing and improving technological understanding in specific contexts. (shrink)

What is understanding? My goal in this paper is to lay out a new approach to this question and clarify how that approach deals with certain issues. The claim is that understanding is a matter of compressing information about the understood so that it can be mentally useful. On this account, understanding amounts to having a representational kernel and the ability to use it to generate the information one needs regarding the target phenomenon. I argue that this (...) ambitious new account can accommodate much of the data that has motivated theories of understanding in philosophy of science, and can also be generally applicable in epistemology and daily life as well. (shrink)

How can we understand people—ourselves and others? Does this require a special form of understanding, different from how we understand non-human phenomena? In this paper, I develop a Beauvoirian-inspired proposal for answering these questions. This proposed account of understanding people lends some support to a long tradition, according to which, we don't understand people in the same way that we understand non-human natural phenomena insofar as understanding people (like literary works) requires an empathic, imaginative, simulationist, or interpretive (...) form. Yet, the Beauvoirian view complicates and challenges this tradition by bringing out the irreducibly second-personal structure of understanding people. It also highlights its embodied and ethical character. In emphasizing these, the Beauvoirian account offers a welcome alternative to empathic views of understanding people (and of relating to literature) and contributes to our understanding of the second-person nexus. It also proposes a refreshing way of thinking about the ethical dimensions of epistemology. (shrink)

Many AI systems that make important decisions are black boxes: how they function is opaque even to their developers. This is due to their high complexity and to the fact that they are trained rather than programmed. Efforts to alleviate the opacity of black box systems are typically discussed in terms of transparency, interpretability, and explainability. However, there is little agreement about what these key concepts mean, which makes it difficult to adjudicate the success or promise of opacity alleviation methods. (...) I argue for a unified account of these key concepts that treats the concept of understanding as fundamental. This allows resources from the philosophy of science and the epistemology of understanding to help guide opacity alleviation efforts. A first significant benefit of this understanding account is that it defuses one of the primary, in-principle objections to post hoc explainable AI (XAI) methods. This “rationalization objection” argues that XAI methods provide mere rationalizations rather than genuine explanations. This is because XAI methods involve using a separate “explanation” system to approximate the original black box system. These explanation systems function in a completely different way than the original system, yet XAI methods make inferences about the original system based on the behavior of the explanation system. I argue that, if we conceive of XAI methods as idealized scientific models, this rationalization worry is dissolved. Idealized scientific models misrepresent their target phenomena, yet are capable of providing significant and genuine understanding of their targets. (shrink)

Jonathan Kvanvig has argued that “objectual” understanding, i.e. the understanding we have of a large body of information, cannot be reduced to explanatory concepts. In this paper, I show that Kvanvig fails to establish this point, and then propose a framework for reducing objectual understanding to explanatory understanding.

It is often claimed—especially by scientific realists—that science provides understanding of the world only if its theories are (at least approximately) true descriptions of reality, in its observable as well as unobservable aspects. This paper critically examines this ‘realist thesis’ concerning understanding. A crucial problem for the realist thesis is that (as study of the history and practice of science reveals) understanding is frequently obtained via theories and models that appear to be highly unrealistic or even completely (...) fictional. So we face the dilemma of either giving up the realist thesis that understanding requires truth, or allowing for the possibility that in many if not all practical cases we do not have scientific understanding. I will argue that the first horn is preferable: the link between understanding and truth can be severed. This becomes a live option if we abandon the traditional view that scientific understanding is a special type of knowledge. While this view implies that understanding must be factive, I avoid this implication by identifying understanding with a skill rather than with knowledge. I will develop the idea that understanding phenomena consists in the ability to use a theory to generate predictions of the target system’s behavior. This implies that the crucial condition for understanding is not truth but intelligibility of the theory, where intelligibility is defined as the value that scientists attribute to the theoretical virtues that facilitate the construction of models of the phenomena. I will show, first, that my account accords with the way practicing scientists conceive of understanding, and second, that it allows for the use of idealized or fictional models and theories in achieving understanding. (shrink)

I explore the extent to which the epistemic state of understanding is transparent to the one who understands. Against several contemporary epistemologists, I argue that it is not transparent in the way that many have claimed, drawing on results from developmental psychology, animal cognition, and other fields.

Recently, it has been debated as to whether understanding is a species of explanatory knowledge. Those who deny this claim frequently argue that understanding, unlike knowledge, can be lucky. In this paper I argue that current arguments do not support this alleged compatibility between understanding and epistemic luck. First, I argue that understanding requires reliable explanatory evaluation, yet the putative examples of lucky understanding underspecify the extent to which subjects possess this ability. In the course (...) of defending this claim, I also provide a new account of the kind of ‘grasping’ taken to be central to understanding. Second, I show that putative examples of lucky understanding unwittingly deploy a kind of luck that is compatible with knowledge. Finally, appealing to a number of works on explanation and its attendant epistemology, I argue that alleged instances of lucky understanding that overcome these two obstacles will invariably violate certain norms of explanatory inquiry – our paradigmatic understanding-oriented practice. By contrast, knowledge of the same information is immune to these criticisms. Consequently, if understanding is environmentally lucky, it is always inferior to the understanding that a corresponding case of knowledge would provide. (shrink)

Several argue that truth cannot be science’s sole epistemic goal, for it would fail to do justice to several scientific practices that advance understanding. I challenge these arguments, but only after making a small concession: science’s sole epistemic goal is not truth as such; rather, its goal is finding true answers to relevant questions. Using examples from the natural and social sciences, I then show that scientific understanding’s epistemically valuable features are either true answers to relevant questions or (...) a means thereof. (shrink)

Epistemic democracy is standardly characterized in terms of “aiming at truth”. This presupposes a veritistic conception of epistemic value, according to which truth is the fundamental epistemic goal. I will raise an objection to the standard (veritistic) account of epistemic democracy, focusing specifically on deliberative democracy. I then propose a version of deliberative democracy that is grounded in non-veritistic epistemic goals. In particular, I argue that deliberation is valuable because it facilitates empathetic understanding. I claim that empathetic understanding (...) is an epistemic good that doesn’t have truth as its primary goal. (shrink)

Does utterance understanding require reliable (i.e. non-lucky) recovery of the speaker’s intended proposition? There are good reasons to answer in the affirmative: the role of understanding in supporting testimonial knowledge seemingly requires such reliability. Moreover, there seem to be communicative analogues of Gettier cases in which luck precludes the audience’s understanding an utterance despite recovering the intended proposition. Yet, there are some major problems with the view that understanding requires such reliability. Firstly, there are a number (...) of cases in which understanding seems to occur in a lucky way. In light of these cases I argue that we need to narrow down the precise sense in which understanding precludes luck – the anti-luck condition attached to linguistic understanding is importantly different to anti-luck conditions typically applied to knowledge. Secondly, Megan Hyska has recently argued that, assuming understanding precludes luck, we get a communicative analogue of the value problem for knowledge. i.e. why is it better to meet the other conditions for understanding in a reliable way than in a lucky way? It is natural to assume that we can simply port over our favoured responses to the epistemic value problem in response to Hyska’s challenge. I argue that, due to the difference between epistemic and communicative luck (discussed in response to the first problem), this cannot be done. The epistemic and communicative value problems will require different solutions. I close by sketching the beginnings of an alternative answer to the value problem for communication. (shrink)

Is linguistic understanding a form of knowledge? I clarify the question and then consider two natural forms a positive answer might take. I argue that, although some recent arguments fail to decide the issue, neither positive answer should be accepted. The aim is not yet to foreclose on the view that linguistic understanding is a form of knowledge, but to develop desiderata on a satisfactory successor to the two natural views rejected here.

What is scientific progress? This paper advances an interpretation of this question, and an account that serves to answer it. Roughly, the question is here understood to concern what type of cognitive change with respect to a topic X constitutes a scientific improvement with respect to X. The answer explored in the paper is that the requisite type of cognitive change occurs when scientific results are made publicly available so as to make it possible for anyone to increase their (...) class='Hi'>understanding of X. This account is briefly compared to two rival accounts of scientific progress, based respectively on increasing truthlikeness and accumulating knowledge, and is argued to be preferable to both. (shrink)

While possessing moral understanding is agreed to be a core epistemic and moral value, it remains a matter of dispute whether it can be acquired via testimony and whether it involves an ability to engage in moral reasoning. This paper addresses both issues with the aim of contributing to the current debates on moral understanding in moral epistemology and virtue ethics. It is argued that moral epistemologists should stop appealing to the argument from the transmissibility of moral (...) class='Hi'>understanding to make a case for their favorite view of moral understanding. It is also argued that proponents of exemplarist moral theories cannot remain neutral on whether the ability to engage in moral reasoning is a necessary component of moral understanding. (shrink)

While it is widely acknowledged that knowledge can be acquired via testimony, it has been argued that understanding cannot. While there is no consensus about what the epistemic relationship of understanding consists in, I argue here that regardless of how understanding is conceived there are kinds of understanding that can be acquired through testimony: easy understanding and easy-s understanding. I address a number of aspects of understanding that might stand in the way of (...) being able to acquire understanding through testimony, focusing on understanding ’s paradigmatic form and what it means to say that in order to understand something you need to “grasp” some information or the relationship between bits of information. I argue that in cases of both easy and easy-s understanding, no aspect of understanding stands in the way of it being able to acquire it through testimony. As a result, while not all understanding be acquired through testimony in all instances and for all subjects, this failure of acquisition is only a product of the complexity of the relevant information or one’s unfamiliarity with it, and not a product of the epistemic relationship of understanding. (shrink)

Testimony spreads information. It is also commonly agreed that it can transfer knowledge. Whether it can work as an epistemic source of understanding is a matter of dispute. However, testimony certainly plays a pivotal role in the proliferation of understanding in the epistemic community. But how exactly do we learn, and how do we make advancements in understanding on the basis of one another’s words? And what can we do to maximize the probability that the process of (...) acquiring understanding from one another succeeds? These are very important questions in our current epistemological landscape, especially in light of the attention that has been paid to understanding as an epistemic achievement of purely epistemic value. Somewhat surprisingly, the recent literature in social epistemology does not offer much on the topic. The overarching aim of this paper is to provide a tentative model of understanding that goes in-depth enough to safely address the question of how understanding and testimony are related to one another. The hope is to contribute, in some measure, to the effort to understand understanding, and to explain two facts about our epistemic practices: the fact that knowledge and understanding relate differently to testimony, and the fact that some pieces of testimonial information are better than others for the sake of providing one with understanding and of yielding advancements in one’s epistemic standing. (shrink)

Recently, several authors have argued that scientific understanding should be a new topic of philosophical research. In this article, I argue that the three most developed accounts of understanding--Grimm's, de Regt's, and de Regt and Dieks's--can be replaced by earlier accounts of scientific explanation without loss. Indeed, in some cases, such replacements have clear benefits.

We argue that Ian Hacking’s work on experimentation and styles of reasoning offers valuable insights for the current debate on the nature of scientific understanding, which so far has largely been focused on the role of theories and explanations. Hacking’s suggestion that reasoning not only involves thinking but also doing helps to recognise the role of experimentation and manipulation in scientific understanding. We apply this idea by relating Hacking’s views on explanation and theorising to the contextual theory of (...) scientific understanding developed by one of us (De Regt 2017). We then take a constructive approach by developing an account of pragmatic understanding that accommodates styles of reasoning and the centrality of manipulation and intervention in Hacking’s philosophy of science. Our overall aim in the paper is to bring the neglected role of experimentation in producing scientific understanding to the fore. We conclude by suggesting that scientific understanding involves both representing and intervening. (shrink)

Knowledge can be transmitted through testimony. What about understanding? In this paper I argue against the possibility of testimonial understanding by giving an account of understanding in terms of ‘mental structures’. Then I argue while we cannot integrate communicating understanding into a propositional model of epistemic communication, we can do so on a perspectival model. I highlight the importance of this to the epistemology of education throughout.

Understanding Computers and Cognition presents an important and controversial new approach to understanding what computers do and how their functioning is related to human language, thought, and action. While it is a book about computers, Understanding Computers and Cognition goes beyond the specific issues of what computers can or can't do. It is a broad-ranging discussion exploring the background of understanding in which the discourse about computers and technology takes place. Understanding Computers and Cognition is (...) written for a wide audience, not just those professionals involved in computer design or artificial intelligence. It represents an important contribution to the ongoing discussion about what it means to be a machine, and what it means to be human. Book jacket. (shrink)

I present a puzzle – the “puzzle of aesthetic testimony” – along with a solution to it that appeals to the impossibility of testimonial understanding. I'll criticize this solution by defending the possibility of testimonial understanding, including testimonial aesthetic understanding.

In this paper I elucidate various ways in which understanding can be seen as an excellence of the mind or intellectual virtue. Along the way, I take up the neglected issue of what it might mean to be an “understanding person”—by which I mean not a person who understands a number of things about the natural world, but a person who steers clear of things like judgmentalism in her evaluation of other people, and thus is better able to (...) take up different perspectives and view them with a sympathetic eye. Being an understanding person in this sense seems to be a character-level virtue that interestingly combines moral and epistemic elements; it also seems to be a virtue particularly needed in our age of deep political division, where it is commonly said that failures of mutual understanding are partly to blame for this problem. (shrink)

Much attention has been paid to moral understanding as an individual achievement, when a single agent gains insight into distinctly moral matters. Crucially overlooked, I argue, is the phenomenon of shared moral understanding, when you and I understand moral matters together, in a way that can’t be reduced to each of us having moral understanding on our own. My argument pays close attention to two central moral practices: justifying our actions to others, and apologizing for wrongdoing. I (...) argue that, whenever I owe you a justification or an apology, I thereby owe it to you to aim at our coming to a shared moral understanding. My argument has two upshots. The first is a novel explanation of the importance of moral understanding in our lives, one that emphasizes the importance of understanding moral reasons together. The second is a better understanding of the very obligations involved in two of our most central interpersonal moral practices. (shrink)

The sciences improve by extending our sensory and cognitive abilities through extrapolation, conversion, and augmentation, as Paul Humphreys has argued. While the opacity of some epistemic enhancers may challenge certain kinds of scientific understanding, I argue that such enhancement is compatible with and extends pragmatic understanding. Drawing on and developing aspects of an epistemology for instruments, I suggest that instrumental functions provide the grounds for extending pragmatic understanding when an inquiry procedure can rely on the instrument’s function (...) to achieve some aim. By continually improving and extending our abilities by relying on instruments, the sciences improve our understanding of the world by extending and enhancing our practical and instrumental facility with it. (shrink)

Among contemporary epistemologists and scholars of ancient philosophy, one often hears that transmitting propositional knowledge by testimony is usually easy and straightforward, but transmitting understanding and know-how by testimony is usually difficult or simply impossible. Further provocative conclusions are then sometimes drawn from these claims: for instance, that know-how and understanding are not types of propositional knowledge. In contrast, I argue that transmitting propositional knowledge is sometimes easy and sometimes hard, just as transmitting know how and understanding (...) is sometimes easy and sometimes hard. No general lessons can be drawn about the relationships among propositional knowledge, know how, and understanding by considering the case of testimony alone. (shrink)

I want to combine two hitherto largely independent research projects, scientific understanding and mechanistic explanations. Understanding is not only achieved by answering why-questions, that is, by providing scientific explanations, but also by answering what-questions, that is, by providing what I call scientific descriptions. Based on this distinction, I develop three forms of understanding: understanding-what, understanding-why, and understanding-how. I argue that understanding-how is a particularly deep form of understanding, because it is based on (...) mechanistic explanations, which answer why something happens in virtue of what it is made of. I apply the three forms of understanding to two case studies: first, to the historical development of thermodynamics and, second, to the differences between the Clausius and the Boltzmann entropy in explaining thermodynamic processes. (shrink)

In this article I argue that there are two different types of understanding: the understanding we get from explanations, and the understanding we get from unification. This claim is defended by first showing that explanation and unification are not as closely related as has sometimes been thought. A critical appraisal of recent proposals for understanding without explanation leads us to discuss the example of a purely classificatory biology: it turns out that such a science can give (...) us understanding of the world through unification of the phenomena, even though it does not give us any explanations. The two types of understanding identified in this paper, while strictly separate, do have in common that both consist in seeing how the individual phenomena of the universe hang together. Explanations give us connections between the phenomena through the asymmetric, ‘vertical’ relation of determination; unifications give us connections through the symmetric, ‘horizontal’ relation of kinship. We then arrive at a general definition of understanding as knowledge of connections between the phenomena, and indicate that there might be more than two types of understanding. (shrink)