Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate what (...) it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)

People feel they understand complex phenomena with far greater precision, coherence, and depth than they really do; they are subject to an illusion—an illusion of explanatory depth. The illusion is far stronger for explanatory knowledge than many other kinds of knowledge, such as that for facts, procedures or narratives. The illusion for explanatory knowledge is most robust where the environment supports real‐time explanations with visible mechanisms. We demonstrate the illusion of depth with explanatory knowledge in Studies 1–6. Then we show (...) differences in overconfidence about knowledge across different knowledge domains in Studies 7–10. Finally, we explore the mechanisms behind the initial confidence and behind overconfidence in Studies 11 and 12, and discuss the implications of our findings for the roles of intuitive theories in concepts and cognition. (shrink)

In this paper, we aim to show that the framework of embedded, distributed, or extended cognition offers new perspectives on social cognition by applying it to one specific domain: the psychology of memory. In making our case, first we specify some key social dimensions of cognitive distribution and some basic distinctions between memory cases, and then describe stronger and weaker versions of distributed remembering in the general distributed cognition framework. Next, we examine studies of social influences on memory in cognitive (...) psychology, and identify the valuable concepts and methods to be extended and embedded in our framework; we focus in particular on three related paradigms: transactive memory, collaborative recall, and social contagion. Finally, we sketch our own early studies of individual and group memory developed within our framework of distributed cognition, on social contagion of autobiographical memories, collaborative flashbulb memories, and memories of high school at a high school reunion. We see two reciprocal benefits of this conceptual and empirical framework to social memory phenomena: that ideas about distributed cognition can be honed against and tested with the help of sophisticated methods in the social cognitive psychology of memory; and conversely, that a range of social memory phenomena that are as yet poorly understood can be approached afresh with theoretically motivated extensions of existing empirical paradigms. (shrink)

The social, behavioral, and a good chunk of the biological sciences concern the nature of individual agency, where our paradigm for an individual is a human being. Theories of economic behavior, of mental function and dysfunction, and of ontogenetic development, for example, are theories of how such individuals act, and of what internal and external factors are determinative of that action. Such theories construe individuals in distinctive ways.

We are constantly called upon to evaluate the evidential weight of testimony, and to balance its deliverances against our own independent thinking. ‘Intellectual autonomy’ is the virtue that is supposed to be displayed by those who engage in cognition in this domain well. I argue that this is at best a misleading label for the virtue, because virtuous cognition in this domain consists in thinking with others, and intelligently responding to testimony. I argue that the existing label supports an excessively (...) individualistic conception of good thinking, both within and outside philosophy. I propose replacing ‘intellectual autonomy’ with ‘intellectual interdependence’, which properly emphasises the depth of our reliance on one another, without suggesting we ought ever to be epistemically servile. (shrink)

Philosophers of neuroscience have traditionally described interfield integration using reduction models. Such models describe formal inferential relations between theories at different levels. I argue against reduction and for a mechanistic model of interfield integration. According to the mechanistic model, different fields integrate their research by adding constraints on a multilevel description of a mechanism. Mechanistic integration may occur at a given level or in the effort to build a theory that oscillates among several levels. I develop this alternative model using (...) a putative exemplar of reduction in contemporary neuroscience: the relationship between the psychological phenomena of learning and memory and the electrophysiological phenomenon known as Long-Term Potentiation. A new look at this historical episode reveals the relative virtues of the mechanistic model over reduction as an account of interfield integration. (shrink)

Does expertise within a domain of knowledge predict accurate self-assessment of the ability to explain topics in that domain? We find that expertise increases confidence in the ability to explain a wide variety of phenomena. However, this confidence is unwarranted; after actually offering full explanations, people are surprised by the limitations in their understanding. For passive expertise, miscalibration is moderated by education; those with more education are accurate in their self-assessments. But when those with more education consider topics related to (...) their area of concentrated study, they also display an illusion of understanding. This “curse of expertise” is explained by a failure to recognize the amount of detailed information that had been forgotten. While expertise can sometimes lead to accurate self-knowledge, it can also create illusions of competence. (shrink)

The Explanatory Model of Scientific Understanding is a deflationary thesis recently advocated by Kareem Khalifa. EMU is committed to two key ideas: all understanding-relevant knowledge is propositional in nature; and the abilities we use to generate understanding are merely our usual logical reasoning skills. In this paper I provide an argument against both ideas, suggesting that scientific understanding requires a significant amount of non-propositional knowledge not captured by logical relations. I use the Inferential Model of Scientific Understanding to reveal how (...) we can better represent what constitutes understanding a scientific event. In particular, this model accounts for not only logical and probabilistic inferences, but also those conceptual associations and categorizations we must make to comprehend an explanation. (shrink)

Moral psychologists have recently turned their attention to a phenomenon they call 'moral dumbfounding'. Moral dumbfounding occurs when someone confidently pronounces a moral judgment, then finds that he or she has little or nothing to say in defense of it. This paper addresses recent attempts by Jonathan Haidt and Marc Hauser to make sense of moral dumbfounding in terms of their respective theories of moral judgment; Haidt in terms of a 'social intuitionist' model of moral judgment, and Hauser in terms (...) of his 'Rawlsian creature' model of moral judgment. I show that Haidt and Hauser assume that moral dumbfounding is to be explained in terms of features of a.) moral judgment that are b.) construed in terms of the intrinsic features of individuals. By contrast, I hypothesize that moral dumbfounding is to be explained in terms of moral reasoning, more specifically in terms of the social dynamics of such reasoning. Finally, I argue that this hypothesis points towards an externalistic account of both moral reasoning and moral judgment. (shrink)

Debates about explanation in the social sciences often proceed without any clear idea what an 'account' of explanation should do. In this paper I take a stance - what I will call contextualism - that denies there are purely formal and conceptual constraints on explanation and takes standards of explanation to be substantive empirical claims, paradigmatically claims about causation. I then use this standpoint to argue for position on issues in the philosophy of social science concerning reduction, idealized models, social (...) mechanisms, functional explanations, inference to the best explanation and interpretive understanding. (shrink)

Generic language (e.g., “tigers have stripes”) leads children to assume that the referenced category (e.g., tigers) is inductively informative and provides a causal explanation for the behavior of individual members. In two preregistered studies with 4- to 7-year-old children (N = 497), we considered the mechanisms underlying these effects by testing how correcting generics might affect the development of these beliefs about novel social and animal kinds (Study 1) and about gender (Study 2). Correcting generics by narrowing their scope to (...) a single individual limited beliefs that the referenced categories could explain what their members would be like while broadening the scope to a superordinate category (Study 2) uniquely limited endorsement of gender norms. Across both studies, correcting generics did not alter beliefs about feature heritability and had mixed effects on inductive inferences, suggesting that additional mechanisms (e.g., causal reasoning about shared features) contribute to the development of full-blown essentialist beliefs. These results help illuminate the mechanisms by which generics lead children to view categories as having rich inductive and causal potential; in particular, they suggest that children interpret generics as signals that speakers in their community view the referenced categories as meaningful kinds that support generalization. The findings also point the way to concrete suggestions for how adults can effectively correct problematic generics (e.g., gender stereotypes) that children may hear in daily life. (shrink)

The theory of concepts advanced in the dissertation aims at accounting for a) how a concept makes successful practice possible, and b) how a scientific concept can be subject to rational change in the course of history. Traditional accounts in the philosophy of science have usually studied concepts in terms only of their reference; their concern is to establish a stability of reference in order to address the incommensurability problem. My discussion, in contrast, suggests that each scientific concept consists of (...) three components of content: 1) reference, 2) inferential role, and 3) the epistemic goal pursued with the concept's use. I argue that in the course of history a concept can change in any of these three components, and that change in one component—including change of reference—can be accounted for as being rational relative to other components, in particular a concept's epistemic goal.This semantic framework is applied to two cases from the history of biology: the homology concept as used in 19th and 20th century biology, and the gene concept as used in different parts of the 20th century. The homology case study argues that the advent of Darwinian evolutionary theory, despite introducing a new definition of homology, did not bring about a new homology concept (distinct from the pre-Darwinian concept) in the 19th century. Nowadays, however, distinct homology concepts are used in systematics/evolutionary biology, in evolutionary developmental biology, and in molecular biology. The emergence of these different homology concepts is explained as occurring in a rational fashion. The gene case study argues that conceptual progress occurred with the transition from the classical to the molecular gene concept, despite a change in reference. In the last two decades, change occurred internal to the molecular gene concept, so that nowadays this concept's usage and reference varies from context to context. I argue that this situation emerged rationally and that the current variation in usage and reference is conducive to biological practice.The dissertation uses ideas and methodological tools from the philosophy of mind and language, the philosophy of science, the history of science, and the psychology of concepts. (shrink)

Explaining phenomena is a primary goal of science. Consequently, it is unsurprising that gaining a proper understanding of the nature of explanation is an important goal of science education. In order to properly understand explanation, however, it is not enough to simply consider theories of the nature of explanation. Properly understanding explanation requires grasping the relation between explanation and understanding, as well as how explanations can lead to scientific knowledge. This article examines the nature of explanation, its relation to understanding, (...) and how explanations are used to generate scientific knowledge via inferences to the best explanation. Studying these features and applications of explanation not only provides insight into a concept that is important for science education in its own right, but also sheds light on an aspect of recent debates concerning the so-called consensus view of nature of science (NOS). Once the relation between explanation, understanding, and knowledge is clear, it becomes apparent that science is unified in important ways. Seeing this unification provides some support for thinking that there are general features of NOS of the sort proposed by the consensus view and that teaching about these general features of NOS should be a goal of science education. (shrink)

Most explanations are either about events (why things happen), or about properties (why objects have the enduring characteristics that they do). Explanations of events have been studied extensively in philosophy and psychology, whereas the explanations of properties have received little or no attention in the literature. The present study is an exploration of the ways in which we explain various types of properties. Ten participants provided explanations of 45 properties by completing sentences of the form: “Xs have p because…” where (...) p is a property of the concept X. When coded into three traditional kinds of explanation (i.e. causal, purposive, categorical), nearly half of the explanations did not fit into any of these categories and were classified as “other”. Different patterns of preference for explanations emerged across the various property types for each domain. A qualitative analysis of the other kind revealed that the most frequent form of explanation involved another property of the object, as in ‘Xs have property p because they have property q”. Explanations of properties showed a homeostatic character. Simply relating two properties of a concept seems sufficient as an explanation of a property. (shrink)

Philosophers of the social sciences are increasingly convinced that macro-and micro-explanations are complementary. Whereas macro-explanations are broad, micro-explanations are deep. I distinguish between weak and strong complementarity: Strongly complementary explanations improve one another when integrated, weakly complementary explanations do not. To demonstrate the explanatory autonomy of different levels of explanation, explanatory pluralists mostly presuppose the weak form of complementarity. By scrutinizing the notions of explanatory depth and breadth, I argue that macro- and micro-accounts of the same phenomenon are more often (...) strongly complementary. This invites a revision of the pluralist position in which integration promotes explanatory progress. (shrink)

Philosophers of the social sciences are increasingly convinced that macro-and micro-explanations are complementary. Whereas macro-explanations are broad, micro-explanations are deep. I distinguish between weak and strong complementarity: Strongly complementary explanations improve one another when integrated, weakly complementary explanations do not. To demonstrate the explanatory autonomy of different levels of explanation, explanatory pluralists mostly presuppose the weak form of complementarity. By scrutinizing the notions of explanatory depth and breadth, I argue that macro- and micro-accounts of the same phenomenon are more often (...) strongly complementary. This invites a revision of the pluralist position in which integration promotes explanatory progress. Key Words: explanatory pluralism • social science • explanatory depth • explanatory breadth • mechanism. (shrink)

The rise of appeals to intuitive theories in many areas of cognitive science must cope with a powerful fact. People understand the workings of the world around them in far less detail than they think. This illusion of knowledge depth has been uncovered in a series of recent studies and is caused by several distinctive properties of explanatory understanding not found in other forms of knowledge. Other experimental work has shown that people do have skeletal frameworks of expectations that constrain (...) richer ad hoc theory construction on the fly. These frameworks are supplemented by an ability to evaluate and rely on the division of cognitive labour in one's culture, an ability shown to be present even in young children. (shrink)

Why do we represent the world around us using causal generalizations, rather than, say, purely statistical generalizations? Do causal representations contain useful additional information, or are they merely more efficient for inferential purposes? This paper considers the second kind of answer: it investigates some ways in which causal cognition might aid us not because of its expressive power, but because of its organizational power. Three styles of explanation are considered. The first, building on the work of Reichenbach in "The Direction (...) of Time", points to causal representation as especially efficient for predictive purposes in a world containing certain pervasive patterns of conditional independence. The second, inspired by work of Woodward and others, finds causal representation to be an excellent vehicle for representing all-important relations of manipulability. The third, based in part on my own work, locates the importance of causal cognition in the special role it reserves for information about underlying mechanisms. All three varieties of explanation show promise, but particular emphasis is placed on the third. (shrink)

In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...) (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed-forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. (shrink)

If folk science means individuals having well worked out mechanistic theories of the workings of the world, then it is not feasible. Laypeople’s explanatory understandings are remarkably coarse, full of gaps, and often full of inconsistencies. Even worse, most people overestimate their own understandings. Yet recent views suggest that formal scientists may not be so different. In spite of these limitations, science somehow works and its success offers hope for the feasibility of folk science as well. The success of science (...) arises from the ways in which scientists learn to leverage understandings in other minds and to outsource explanatory work through sophisticated methods of deference and simplification of complex systems. Three studies ask whether analogous processes might be present not only in laypeople but also in young children and thereby form a foundation for supplementing explanatory understandings almost from the start of our first attempts to make sense of the world. (shrink)