Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood. We present a formal analysis of symbolic learning—in particular, word learning—in terms of prediction and cue competition, and we consider two possible ways in which symbols might be learned: by learning to predict a label from the features of objects and events in the world, and by learning to predict features from a (...) label. This analysis predicts significant differences in symbolic learning depending on the sequencing of objects and labels. We report a computational simulation and two human experiments that confirm these differences, revealing the existence of Feature-Label-Ordering effects in learning. Discrimination learning is facilitated when objects predict labels, but not when labels predict objects. Our results and analysis suggest that the semantic categories people use to understand and communicate about the world can only be learned if labels are predicted from objects. We discuss the implications of this for our understanding of the nature of language and symbolic thought, and in particular, for theories of reference. (shrink)

As adults age, their performance on many psychometric tests changes systematically, a finding that is widely taken to reveal that cognitive information-processing capacities decline across adulthood. Contrary to this, we suggest that older adults'; changing performance reflects memory search demands, which escalate as experience grows. A series of simulations show how the performance patterns observed across adulthood emerge naturally in learning models as they acquire knowledge. The simulations correctly identify greater variation in the cognitive performance of older adults, and successfully (...) predict that older adults will show greater sensitivity to fine-grained differences in the properties of test stimuli than younger adults. Our results indicate that older adults'; performance on cognitive tests reflects the predictable consequences of learning on information-processing, and not cognitive decline. We consider the implications of this for our scientific and cultural understanding of aging. (shrink)

Two experiments investigated whether infants represent goal‐directed actions of others in a way that allows them to draw inferences to unobserved states of affairs (such as unseen goal states or occluded obstacles). We measured looking times to assess violation of infants' expectations upon perceiving either a change in the actions of computer‐animated figures or in the context of such actions. The first experiment tested whether infants would attribute a goal to an action that they had not seen completed. The second (...) experiment tested whether infants would infer from an observed action the presence of an occluded object that functions as an obstacle. The looking time patterns of 12‐month‐olds indicated that they were able to make both types of inferences, while 9‐month‐olds failed in both tasks. These results demonstrate that, by the end of the first year of life, infants use the principle of rational action not only for the interpretation and prediction of goal‐directed actions, but also for making productive inferences about unseen aspects of their context. We discuss the underlying mechanisms that may be involved in the developmental change from 9 to 12 months of age in the ability to infer hypothetical (unseen) states of affairs in teleological action representations. (shrink)

In a series of studies children show increasing mastery of irregular plural forms (such as mice) simply by producing erroneous over‐regularized versions of them (such as mouses). We explain this phenomenon in terms of successive approximation in imitation: Children over‐regularize early in acquisition because the representations of frequent, regular plural forms develop more quickly, such that at the earliest stages of production they interfere with children's attempts to imitatively reproduce irregular forms they have heard in the input. As the strength (...) of the representations that determine children's productions settle asymptotically, the early advantage for the frequent regular forms is negated, and children's attempts to imitate the irregular forms they have observed become more likely to succeed (a process that produces the classic U‐shape in children's acquisition of plural inflection). These data show that children can acquire correct linguistic behavior without feedback in a situation where, as a result of philosophical and linguistic analyses, it has often been argued that it is logically impossible for them to do so. (shrink)

Empirical studies indicate that analogy consists of two main processes: retrieval and mapping. While current theories and models of analogy have revealed much about the mainly structural constraints that govern the mapping process, the similarities that underpin the correspondences between individual representational elements and drive retrieval are understood in less detail. In existing models symbol similarities are externally defined but neither empirically grounded nor theoretically justified. This paper introduces a new model (EMMA: the environmental model of analogy) which relies on (...) co‐occurrence information provided by LSA (Latent Semantic Analysis; Landauer & Dumais, 1997) to ground the relations between the symbolic elements aligned in analogy. LSA calculates a contextual distribution for each word encountered in a corpus by counting the frequency with which it co‐occurs with other words. This information is used to define a model that locates each word encountered in a high‐dimensional space, with relations between elements in this space representing contextual similarities between words. A series of simulation experiments demonstrate that the environmental approach to semantics embodied in LSA can produce appropriate patterns of analogical retrieval, but that this semantic measure is not sufficient to model analogical mapping. The implications of these findings, both for theories of representation in analogy research and more general theories of semantics in cognition, are explored. (shrink)

How do we understand time and other entities we can neither touch nor see? One possibility is that we tap into our concrete, experiential knowledge, including our understanding of physical space and motion, to make sense of abstract domains such as time. To examine how pervasive an aspect of cognition this is, we investigated whether thought about a nonliteral type of motion called fictive motion (FM; as in The road runs along the coast) can influence thought about time. Our results (...) suggest that FM uses the same structures evoked in understanding literal motion, and that these literal aspects of FM influence temporal reasoning. (shrink)

How are natural symbol systems best understood? Traditional “symbolic” approaches seek to understand cognition by analogy to highly structured, prescriptive computer programs. Here, we describe some problems the traditional computational metaphor inevitably leads to, and a very different approach to computation (Ramscar, Yarlett, Dye, Denny, & Thorpe, 2010; Turing, 1950) that allows these problems to be avoided. The way we conceive of natural symbol systems depends to a large degree on the computational metaphors we use to understand them, and (...) machine learning suggests an understanding of symbolic thought that is very different to traditional views (Hummel, 2010). The empirical question then is: Which metaphor is best? (shrink)

The uncertainty associated with paradigmatic families has been shown to correlate with their phonetic characteristics in speech, suggesting that representations of complex sublexical relations between words are part of speaker knowledge. To better understand this, recent studies have used two-layer neural network models to examine the way paradigmatic uncertainty emerges in learning. However, to date this work has largely ignored the way choices about the representation of inflectional and grammatical functions in models strongly influence what they subsequently learn. To explore (...) the consequences of this, we investigate how representations of IFS in the input-output structures of learning models affect the capacity of uncertainty estimates derived from them to account for phonetic variability in speech. Specifically, we examine whether IFS are best represented as outputs to neural networks or as inputs by building models that embody both choices and examining their capacity to account for uncertainty effects in the formant trajectories of word final [ɐ], which in German discriminates around sixty different IFS. Overall, we find that formants are enhanced as the uncertainty associated with IFS decreases. This result dovetails with a growing number of studies of morphological and inflectional families that have shown that enhancement is associated with lower uncertainty in context. Importantly, we also find that in models where IFS serve as inputs—as our theoretical analysis suggests they ought to—its uncertainty measures provide better fits to the empirical variance observed in [ɐ] formants than models where IFS serve as outputs. This supports our suggestion that IFS serve as cognitive cues during speech production, and should be treated as such in modeling. It is also consistent with the idea that when IFS serve as inputs to a learning network. This maintains the distinction between those parts of the network that represent message and those that represent signal. We conclude by describing how maintaining a “signal-message-uncertainty distinction” can allow us to reconcile a range of apparently contradictory findings about the relationship between articulation and uncertainty in context. (shrink)

Children with developmental language disorder (DLD) have significant deficits in language ability that cannot be attributed to neurological damage, hearing impairment, or intellectual disability. The symptoms displayed by children with DLD differ across languages. In English, DLD is often marked by severe difficulties acquiring verb inflection. Such difficulties are less apparent in languages with rich verb morphology like Spanish and Italian. Here we show how these differential profiles can be understood in terms of an interaction between properties of the input (...) language, and the child's ability to learn predictive relations between linguistic elements that are separated within a sentence. We apply a simple associative learning model to sequential English and Spanish stimuli and show how the model's ability to associate cues occurring earlier in time with later outcomes affects the acquisition of verb inflection in English more than in Spanish. We relate this to the high frequency of the English bare form (which acts as a default) and the English process of question formation, which means that (unlike in Spanish) bare forms frequently occur in third‐person singular contexts. Finally, we hypothesize that the pro‐drop nature of Spanish makes it easier to associate person and number cues with the verb inflection than in English. Since the factors that conspire to make English verb inflection particularly challenging for learners with weak sequential learning abilities are much reduced or absent in Spanish, this provides an explanation for why learning Spanish verb inflection is relatively unaffected in children with DLD. (shrink)

Concepts allow us to treat different objects equivalently according to shared attributes, and hence to communicate about, draw inferences from, reason with, and explain these objects. Understanding how concepts are formed and used is thus essential to understanding and applying these basic processes, and the topic of similarity-based classification is central to psychology, artificial intelligence, statistics, and philosophy. This book brings together leading researchers, reflecting the key topics and important developments in the field and provides a uniquely interdisciplinary overview of (...) the subject. (shrink)

There is an old joke about a theoretical physicist who was charged with figuring out how to increase the milk production of cows. Although many farmers, biologists, and psychologists had tried and failed to solve the problem before him, the physicist had no trouble coming up with a solution on the spot. “ First,” he began, “we assume a spherical cow... ” [Tenenbaum & Griffiths].

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences—and the relations between the elements they comprise—are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the learning of sequences are rarely investigated. We present three experiments that seek to examine these mechanisms during a typing task. Experiments 1 and 2 tested learning during typing single letters on each trial. (...) Experiment 3 tested for “chunking” of these letters into “words.” The results of these experiments were used to examine the mechanisms that could best account for them, with a focus on two particular proposals: statistical transitional probability learning and discriminative error-driven learning. Experiments 1 and 2 showed that error-driven learning was a better predictor of response latencies than either n-gram frequencies or transitional probabilities. No evidence for chunking was found in Experiment 3, probably due to interspersing visual cues with the motor response. In addition, learning occurred across a greater distance in Experiment 1 than Experiment 2, suggesting that the greater predictability that comes with increased structure leads to greater learnability. These results shed new light on the mechanism responsible for sequence learning. Despite the widely held assumption that transitional probability learning is essential to this process, the present results suggest instead that the sequences are learned through a process of discriminative learning, involving prediction and feedback from prediction error. (shrink)

It is a reasonable assumption that universal properties of natural languages are not accidental. They occur either because they are underwritten by genetic code, because they assist in language processing or language learning, or due to some combination of the two. In this paper we investigate one such language universal: the suffixing preference across the world’s languages, whereby inflections tend to be added to the end of words. A corpus analysis of child‐directed speech in English found that suffixes were more (...) accurate at cuing the grammatical category of the root word than were prefixes. An artificial language experiment found that there was a learning advantage for suffixes over prefixes in terms of grammatical categorization within an artificial language. The results are consistent with an account of language universals that originate in general purpose learning mechanisms. (shrink)

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language learning experiment, (...) we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non‐confusable. Regarding levels of abstraction, we find that premarking of super‐ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation‐based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre‐ and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system. (shrink)

Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers (premarkers, e.g., gendered articles) or succeeding category markers (postmarkers, e.g., gendered suffixes). Given that numerous systems for marking grammatical categories exist in natural languages, it follows that a better understanding of these findings can shed light on the factors underlying this diversity. In two discriminative learning simulations and an artificial language learning experiment, (...) we identify two factors that modulate linear order effects in linguistic category learning: category structure and the level of abstraction in a category hierarchy. Regarding category structure, we find that postmarking brings an advantage for learning category diagnostic stimulus dimensions, an effect not present when categories are non‐confusable. Regarding levels of abstraction, we find that premarking of super‐ordinate categories (e.g., noun class) facilitates learning of subordinate categories (e.g., nouns). We present detailed simulations using a plausible candidate mechanism for the observed effects, along with a comprehensive analysis of linear order effects within an expectation‐based account of learning. Our findings indicate that linguistic category learning is differentially guided by pre‐ and postmarking, and that the influence of each is modulated by the specific characteristics of a given category system. (shrink)

Many metaphor theorists argue that our mental experience of time is grounded in our understanding of space, including motion through space. Results from recent experiments – in which people think about motion, which in turn influences their thinking about time – support this position. Still, many questions remain about the nature of the metaphorical connection between time and space. Can the mere suggestion of motion influence how people reason about time, and if so, when and how? Three experiments investigated how (...) thinking about “abstract” motion through sequences of numbers or letters would influence reasoning about time. Our results extend earlier psychological work on the link between time and space by showing that even motion in non-physical domains can influence temporal reasoning. The results provide further evidence that metaphorical understanding is grounded in our everyday physical and conceptual experience. (shrink)

A central goal of typological research is to characterize linguistic features in terms of both their functional role and their fit to social and cognitive systems. One long-standing puzzle concerns why certain languages employ grammatical gender. In an information theoretic analysis of German noun classification, Dye, Milin, Futrell, and Ramscar enumerated a number of important processing advantages gender confers. Yet this raises a further puzzle: If gender systems are so beneficial to processing, what does this mean for languages that (...) make do without them? Here, we compare the communicative function of gender marking in German to that of prenominal adjectives in English, finding that despite their differences, both systems act to efficiently smooth information over discourse, making nouns more equally predictable in context. We examine why evolutionary pressures may favor one system over another and discuss the implications for compositional accounts of meaning and Gricean principles of communication. (shrink)

This book defends a form of ethical intuitionism, according to which (i) there are objective moral truths; (ii) we know some of these truths through a kind of immediate, intellectual awareness, or "intuition"; and (iii) our knowledge of moral truths gives us reasons for action independent of our desires. The author rebuts all the major objections to this theory and shows that the alternative theories about the nature of ethics all face grave difficulties.

Part I: The representation of life -- Can life be given a real definition? -- The representation of the living individual -- The representation of the life-form itself -- Part II: Naive action theory -- Types of practical explanation -- Naive explanation of action -- Action and time -- Part III: Practical generality -- Two tendencies in practical philosophy -- Practices and dispositions as sources of the goodness of individual actions -- Practice and disposition as sources of individual action.

The first edition of The Scientific Background to Modern Philosophy took the dialogue of science and philosophy from Aristotle through to Newton. This second edition adds eight chapters, taking the dialogue through the Enlightenment and up to Darwin. This anthology is an attempt to help bridge the gap between the history of science and the history of philosophy.

Virtually all philosophers agree that for a belief to be epistemically justified, it must satisfy certain conditions. Perhaps it must be supported by evidence. Or perhaps it must be reliably formed. Or perhaps there are some other "good-making" features it must have. But does a belief's justification also require some sort of awareness of its good-making features? The answer to this question has been hotly contested in contemporary epistemology, creating a deep divide among its practitioners. Internalists, who tend to focus (...) on scientific or theoretical beliefs as the ideal, insist that such awareness is required for justification. Externalists, who think children's ordinary beliefs in obvious facts are paradigm cases of justified belief, say it isn't required. Michael Bergmann's book offers a decisive refutation of internalism and a sustained defense of externalism. (shrink)

Externalist theories of justification create the possibility of cases in which everything appears to one relevantly similar with respect to two propositions, yet one proposition is justified while the other is not. Internalists find this difficult to accept, because it seems irrational in such a case to affirm one proposition and not the other. The underlying internalist intuition supports a specific internalist theory, Phenomenal Conservatism, on which epistemic justification is conferred by appearances.

At the University of Sheffield during 2011 and 2012, a leading group of philosophers, psychologists, and others gathered to explore the nature and significance of implicit bias. The two volumes of Implicit Bias and Philosophy emerge from these workshops. Each volume philosophically examines core areas of psychological research on implicit bias as well as the ramifications of implicit bias for core areas of philosophy. Volume I: Metaphysics and Epistemology is comprised of two parts: “The Nature of Implicit Attitudes, Implicit Bias, (...) and Stereotype Threat,” and “Skepticism, Social Knowledge, and Rationality.” The first part contains chapters examining the relationship between implicit attitudes and “dual process” models of the mind; the role of affect in the formation and change of implicit associations; the unity (or disunity) of implicit attitudes; whether implicit biases are mental states at all; and whether performances on stereotype-relevant tasks are automatic and unconscious or intentional and strategic. The second part contains chapters examining implicit bias and skepticism; the effects of implicit bias on scientific research; the accessibility of social stereotypes in epistemic environments; the effects of implicit bias on the self-perception of members of stigmatized social groups as rational agents; the role of gender stereotypes in philosophy; and the role of heuristics in biased reasoning. (shrink)

In this engaging and spirited text, Michael Lynch argues that truth does matter, in both our personal and political lives. He explains that the growing cynicism over truth stems in large part from our confusion over what truth is.

Dignity plays a central role in current thinking about law and human rights, but there is sharp disagreement about its meaning. Combining conceptual precision with a broad historical background, Michael Rosen puts these controversies in context and offers a novel, constructive proposal. “Penetrating and sprightly...Rosen rightly emphasizes the centrality of Catholicism in the modern history of human dignity. His command of the history is impressive...Rosen is a wonderful guide to the recent German constitutional thinking about human dignity...[Rosen] is in (...) general an urbane and witty companion, achieving his aim of accessibly written philosophy.” —Samuel Moyn, The Nation “[An] elegant, interesting and lucid exploration of the concept of dignity...Drawing on classical, liberal and Catholic traditions, Rosen hopes to rehabilitate dignity to its rightful place near the centre of moral thought...Rosen's admirable book deserves wide attention from political theorists, jurisprudes and political philosophers.” —Simon Blackburn, Times Higher Education “Dignity deserves to be widely read, not only for its intrinsic interest, but also as a corrective to the habit of discussing such topics in abstraction from their social context. Whether or not one agrees with Rosen's arguments, there can be no doubt he has widened our horizons.” —Rae Langton, Times Literary Supplement. (shrink)

edition (unseen), $12.95. traditions, bringing into being new modes of understanding. Paper Anthropology, and particularly ethnography, is torn between two quests, one to capture the diversity of social life and the other to discover universal principles structuring that diversity. Jackson examines these quests within the context of ethnographic fieldwork, focusing on the relationship between ethnographers and the people they study. He is concerned with defining the anthropological project as something more than the projection of the anthropologist's traditions and concerns onto (...) an alien culture. Rather, he would have the project open a genuine dialogue between people from different cultures or Annotation copyrighted by Book News, Inc., Portland, OR. (shrink)

At the heart of ethics reside the concepts of good and bad; they are at work when we assess whether a person is virtuous or vicious, an act right or wrong, a decision defensible or indefensible, a goal desirable or undesirable. But there are many varieties of goodness and badness. At their core lie intrinsic goodness and badness, the sort of value that something has for its own sake. It is in virtue of intrinsic value that other types of value (...) may be understood, and hence that we can begin to come to terms with questions of virtue and vice, right and wrong, and so on. This book investigates the nature of intrinsic value: just what it is for something to be valuable for its own sake, just what sort of thing can have such value, just how such a value is to be computed. In the final chapter, the fruits of this investigation are applied to a discussion of pleasure, pain, and displeasure and also of moral virtue and vice, in order to determine just what value lies within these phenomena. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

In previous work I have argued against internalism by means of a dilemma intended to force all internalists to accept one of two undesirable options: either their internalism is unmotivated or it is saddled with vicious regress problems. Recently it has been argued that Phenomenal Conservatism—a theory of justification according to which justification depends on seemings—is a kind of internalism that can escape this dilemma. In this paper, I argue that Phenomenal Conservatism cannot escape my dilemma for internalism. In order (...) to do this, it is helpful to get clear on what Phenomenal Conservatism is saying, and for that reason I begin, in section I, by examining in some detail what seemings are. I then argue, in the remainder of the paper, that, whichever horn of the dilemma for internalism they take, Phenomenal Conservatives are in trouble. (shrink)

Can an ugly experiment be a good experiment? Philosophers have identified many beautiful experiments and explored ways in which their beauty might be connected to their epistemic value. In contrast, the present chapter seeks out (and celebrates) ugly experiments. Among the ugliest are those being designed by AI algorithms. Interestingly, in the contexts where such experiments tend to be deployed, low aesthetic value correlates with high epistemic value. In other words, ugly experiments can be good. Given this, we should conclude (...) that beauty is not generally necessary or sufficient for epistemic value, and increasing beauty will not generally tend to increase epistemic value. (shrink)

Radical skepticism endorses the extreme claim that large swaths of our ordinary beliefs, such as those produced by perception or memory, are irrational. The best arguments for such skepticism are, in their essentials, as familiar as a popular science fiction movie and yet even seasoned epistemologists continue to find them strangely seductive. Moreover, although most contemporary philosophers dismiss radical skepticism, they cannot agree on how best to respond to the challenge it presents. In the tradition of the 18th century Scottish (...) philosopher, Thomas Reid, Radical Skepticism and Epistemic Intuition joins this discussion by taking up four main tasks. First, it identifies the strongest arguments for radical skepticism, namely, underdetermination arguments, which emphasize the gap between our evidence and our ordinary beliefs based on that evidence. Second, it rejects all inferential or argument-based responses to radical skepticism, which aim to lay out good noncircular reasoning from the evidence on which we base our ordinary beliefs to the conclusion that those beliefs are probably true. Third, it develops a commonsense noninferential response to radical skepticism with two distinctive features: it consciously and extensively relies on epistemic intuitions, which are seemings about epistemic goods, such as knowledge and rationality, and it can be endorsed without difficulty by both internalists and externalists in epistemology. Fourth, and finally, it defends this commonsense epistemic-intuition-based response to radical skepticism against a variety of objections, including those connected with underdetermination worries, epistemic circularity, disagreement problems, experimental philosophy, and concerns about whether it engages skepticism in a sufficiently serious way. (shrink)

A paradigm-shifting work that revolutionizes our understanding of the origins and structure of science. Captivatingly written, interwoven with tantalizing illustrations and historical vignettes ranging from Newton's alchemy to quantum mechanics to the storm surge of Hurricane Sandy, Michael Strevens's wholly original investigation of science asks two fundamental questions: Why is science so powerful? And why did it take so long, two thousand years after the invention of philosophy and mathematics, for the human race to start using science to learn (...) the secrets of nature? The Knowledge Machine's radical answer is that science calls on its practitioners to do something irrational: by willfully ignoring religion, theoretical beauty, and, especially, philosophy-essentially stripping away all previous knowledge-scientists embrace an unnaturally narrow method of inquiry, channeling unprecedented energy into observation and experimentation. Like Yuval Harari's Sapiens or Thomas Kuhn's 1962 classic, The Structure of Scientific Revolutions, The Knowledge Machine overturns much of what we thought we knew about the origins of the modern world. (shrink)

Imagination is important for many things in science: solving problems, interpreting data, designing studies, etc. Philosophers of imagination typically account for the productive role played by imagination in science by focusing on how imagination is constrained, e.g., by using self-imposed rules to infer logically, or model events accurately. But the constraints offered by these philosophers either constrain too much, or not enough, and they can never account for uses of imagination that are needed to break today’s constraints in order to (...) make progress tomorrow. Thus, epistemology of imagination needs to make room for an element of epistemological anarchy. (shrink)