"Nivison brings out the exciting variety within Confucian thought, as he interprets and elucidates key thinkers from over two thousand years, from Confucius himself, through Mencius and Xunzi, to such later Confucians as Wang Yangming, Dai Zhen, and Zhang Xuecheng."--Cover.

This collection of essays by leading sinologists, historians, and philosophers both challenges and extends the work of David Nivison, whose contributions range across moral philosophy, religious thought, intellectual history, and Chinese language. Nivison himself replies to each essay.

Scholars of early Chinese philosophy frequently point to the nontranscendent, organismic conception of the cosmos in early China as the source of China's unique perspective and distinctive values. One would expect recent works in Confucian ethics to capitalize on this idea. Reviewing recent works in Confucian ethics by P. J. Ivanhoe, David Nivison, R. P. Peerenboom, Henry Rosemont, and Tu Wei-Ming, the author analyzes these new studies in terms of the extent to which their representation of Confucian ethics (...) reflects and is consistent with the view that in early China the cosmos was conceived to be organismic, nontranscendent, and nondualistic. (shrink)

Corruptionism is the view that following physical death, the human being ceases to exist but their soul persists in the afterlife. Survivalism holds that both the human being and their soul persist in the afterlife, as distinct entities, with the soul constituting the human. Each position has its defenders, most of whom appeal both to metaphysical considerations and to the authority of St Thomas Aquinas. Corruptionists claim that survivalism violates a basic principle of any plausible mereology, while survivalists tend to (...) reject the principle, though without as much detail as one would like. In this paper I examine both the key exegetical issues and the mereological question, arguing that Aquinas cannot be shown to have supported the principle in question, and that the principle should be rejected on independent grounds. If correct, some key planks in support of survivalism are established, with others to await further examination. (shrink)

According to divine premotionism, God does not merely create and sustain the universe. He also moves all secondary causes to action as instruments without undermining their intrinsic causal efficacy. I explain and uphold the premotionist theory, which is the theory of St Thomas Aquinas and his most prominent exponents. I defend the premotionist interpretation of Aquinas in some textual detail, with particular reference to Suarez and to a recent paper by Louis Mancha. Critics, including Molinists and Suarezians, raise various objections (...) to the view that premotion is compatible with genuine secondary causation. I rebut a number of these objections, in the course of which I respond to the central challenge that premotionism destroys free will. I also offer a number of positive reasons for embracing the premotionist theory. (shrink)

The first book-length treatment in English of Habermas’s theory of social evolution and progress.

This fundamental and straightforward text addresses a weakness observed among present-day students, namely a lack of familiarity with formal proof. Beginning with the idea of mathematical proof and the need for it, associated technical and logical skills are developed with care and then brought to bear on the core material of analysis in such a lucid presentation that the development reads naturally and in a straightforward progression. Retaining the core text, the second edition has additional worked examples which users have (...) indicated a need for, in addition to more emphasis on how analysis can be used to tell the accuracy of the approximations to the quantities of interest which arise in analytical limits. (shrink)

This chapter contains sections titled: Learning Difference Against Ignoring Difference I Am Because We Are and We Are Because I Am Practicing Just Parenting Teaching Alienation? Notes.

Ten years after over half a million Christians signed their names to a statement of conscience clarifying where they stood, the three issues dealt with in the Manhattan Declaration are of more cultural importance than ever. The main difference now, as opposed to then, is the state has since claimed authority, not only over life, but also over marriage and religious liberty." -- Amazon.com.

Although the language of vocation was born in a religious context, the contributors in this volume demonstrate that it has now taken root within the broad framework of higher education and has become intertwined with a wide range of concerns. This volume makes a compelling case for vocational reflection and discernment in undergraduate education today, arguing that it will encourage faculty and students alike to venture out of their narrow disciplinary specializations and to reflect on larger questions of meaning and (...) purpose. In conversation with a growing range of scholarly resources, these essays advance the cause of vocational reflection and discernment well beyond its occasional mention in general education courses and career placement offices. The book's thirteen contributors all work in higher education, but they do so as biologists and musicians, sociologists and engineers, doctors and lawyers, college presidents and deans, and scholars of history, literature, and business administration. Together, they demonstrate that vocation has an important role to play across the entire range of traditional academic disciplines and applied fields. Regardless of major, all undergraduates need to consider their current and future responsibilities, determine the stories they will live by, and discover resources for addressing the tensions that will inevitably arise among their multiple callings. Vocation across the Academy will help to reframe current debates about the purpose of higher education. It underscores the important role that colleges and universities can play in encouraging students to reflect more deeply on life's most persistent questions and to consider how they might best contribute to the common good. (shrink)

What is the cultural value of illegal works that violate the copyrights of popular fiction? Why do they persist despite clear and stringent intellectual property laws? Drawing on the disciplines of new media, law, and literary studies, Illegal Literature suggests that extralegal works such as fan fiction are critical to a system that spurs the evolution of culture. Reconsidering voices relegated to the cultural periphery, David S. Roh shows how infrastructure--in the form of legal policy and network distribution--slows or (...) accelerates the rate of change. He analyzes the relationship between intellectual property rights and American literature in two recent copyright disputes. And, in comparing American fan fiction and Japanese dojinshi, he illustrates how infrastructure and legal climates detract from or encourage fledgling creativity. Illegal Literature fills a crucial gap between the scholarly and the popular by closely examining several modes of marginalized cultural production. Roh makes the case for protecting an environment conducive to literary heresy, the articulation of an accretive rather than solitary authorial genius, and the idea that letting go rather than holding on is important to a generative creative process. In a media ecology inundated by unauthorized materials, Illegal Literature argues that the proliferation of unsanctioned texts may actually benefit literary and cultural development. (shrink)

_Real Essentialism_ presents a comprehensive defence of neo-Aristotelian essentialism. Do objects have essences? Must they be the kinds of things they are in spite of the changes they undergo? Can we know what things are really like – can we define and classify reality? Many, if not most, philosophers doubt this, influenced by centuries of empiricism, and by the anti-essentialism of Wittgenstein, Quine, Popper, and other thinkers. _Real Essentialism_ reinvigorates the tradition of realist, essentialist metaphysics, defending the reality and knowability (...) of essence, the possibility of objective, immutable definition, and its relevance to contemporary scientific and metaphysical issues such as whether essence transcends physics and chemistry, the essence of life, the nature of biological species, and the nature of the person. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

DCPS is a connectionist production system interpreter that uses distributed representations. As a connectionist model it consists of many simple, richly interconnected neuron‐like computing units that cooperate to solve problems in parallel. One motivation for constructing DCPS was to demonstrate that connectionist models are capable of representing and using explicit rules. A second motivation was to show how “coarse coding” or “distributed representations” can be used to construct a working memory that requires far fewer units than the number of different (...) facts that can potentially be stored. The simulation we present is intended as a detailed demonstration of the feasibility of certain ideas and should not be viewed as a full implementation of production systems. Our current model only has a few of the many interesting emergent properties that we eventually hope to demonstrate: It is damage‐resistant, it performs matching and variable binding by massively parallel constraint satisfaction, and the capacity of its working memory is dependent on the similarity of the items being stored. (shrink)

As machine learning has gradually entered into ever more sectors of public and private life, there has been a growing demand for algorithmic explainability. How can we make the predictions of complex statistical models more intelligible to end users? A subdiscipline of computer science known as interpretable machine learning (IML) has emerged to address this urgent question. Numerous influential methods have been proposed, from local linear approximations to rule lists and counterfactuals. In this article, I highlight three conceptual challenges that (...) are largely overlooked by authors in this area. I argue that the vast majority of IML algorithms are plagued by (1) ambiguity with respect to their true target; (2) a disregard for error rates and severe testing; and (3) an emphasis on product over process. Each point is developed at length, drawing on relevant debates in epistemology and philosophy of science. Examples and counterexamples from IML are considered, demonstrating how failure to acknowledge these problems can result in counterintuitive and potentially misleading explanations. Without greater care for the conceptual foundations of IML, future work in this area is doomed to repeat the same mistakes. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealisedexplanation gamein which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of (...) variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

We examine two different descriptions of the behavioral functions of the hippocampal system. One emphasizes spatially organized behaviors, especially those using cognitive maps. The other emphasizes memory, particularly working memory, a short-term memory that requires iexible stimulus-response associations and is highly susceptible to interference. The predictive value of the spatial and memory descriptions were evaluated by testing rats with damage to the hippocampal system in a series of experiments, independently manipulating the spatial and memory characteristics of a behavioral task. No (...) dissociations were found when the spatial characteristics of the stimuli to be remembered were changed; lesions produced a similar deficit in both spatial and nonspatial test procedures, indicating that the hippocampus was similarly involved regardless of the spatial nature of the task. In contrast, a marked dissociation was found when the memory requirements were altered. Rats with lesions were able to perform accurately in tasks that could be solved exclusively on the basis of reference memory. They performed at chance levels and showed no signs of recovery even with extensive postoperative training in tasks that required working memory. In one experiment all the characteristics of the reference memory and working memory procedures were identical except the type of memory required. Consequently, the behavioral dissociation cannot be explained by differences in attention, motivation, response inhibition, or the type of stimuli to be remembered. As a result of these experiments we propose that the hippocampus is selectively involved in behaviors that require working memory, irrespective of the type of material that is to be processed by that memory. (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

Contents:Acknowledgements Foreword (Lt. Ervin J. Rokke)Preface (Davis S. Alberts and Thomas Czerwinski)SETTING THE SCENEThe Simple and the Complex (Murray Gell-Mann)America in the World Today (Zbigniew Brzezinski)COMPLEXITY THEORY and NATIONAL SECURITY POLICYComplex Systems: The Role of Interactions (Robert Jervis)Many Damn Things Simultaneously: Complexity Theory and World Affairs (James N. Rosenau)Complexity, Chaos, and National Security Policy: Metaphors or Tools? (Alvin M. Saperstein)The Reaction to Chaos (Steven R. Mann)COMPLEXITY THEORY, STRATEGY, and OPERATIONSClausewitz, Nonlinearity, and the Importance of Imagery (Alan D. Beyerchen)Complexity and Organization (...) Management (Robert R. Maxfield)Command and (Out of) Control: The Military Implications of Complexity Theory (John F. Schmitt)Complexity Theory and Air Power (Steven M. Rinaldi)Chaos Theory and U. S. Military Strategy: A "Leapfrog" Strategy for U.S. Defense Policy (Michael J. Mazarr)Contributors EditorsBibliography. (shrink)

The distinction between the essence of an object and its properties has been obscured in contemporary discussion of essentialism. Locke held that the properties of an object are exclusively those features that ‘flow’ from its essence. Here he follows the Aristotelian theory, leaving aside Locke’s own scepticism about the knowability of essence. I defend the need to distinguish sharply between essence and properties, arguing that essence must be given by form and that properties flow from form. I give a precise (...) definition of what the term of art ‘flow’ amounts to, and apply the distinction to various kinds of taxonomic issues. (shrink)

Unsupervised learning algorithms are widely used for many important statistical tasks with numerous applications in science and industry. Yet despite their prevalence, they have attracted remarkably little philosophical scrutiny to date. This stands in stark contrast to supervised and reinforcement learning algorithms, which have been widely studied and critically evaluated, often with an emphasis on ethical concerns. In this article, I analyze three canonical unsupervised learning problems: clustering, abstraction, and generative modeling. I argue that these methods raise unique epistemological and (...) ontological questions, providing data-driven tools for discovering natural kinds and distinguishing essence from contingency. This analysis goes some way toward filling the lacuna in contemporary philosophical discourse on unsupervised learning, as well as bringing conceptual unity to a heterogeneous field more often described by what it isnot(i.e., supervised or reinforcement learning) than by what itis. I submit that unsupervised learning is not just a legitimate subject of philosophical inquiry but perhaps the most fundamental branch of all AI. However, an uncritical overreliance on unsupervised methods poses major epistemic and ethical risks. I conclude by advocating for a pragmatic, error-statistical approach that embraces the opportunities and mitigates the challenges posed by this powerful class of algorithms. (shrink)

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence, a fast-growing research area that is so far lacking in firm theoretical foundations. In this article, an expanded version of a paper originally presented at the 37th Conference on Uncertainty in Artificial Intelligence, we attempt to fill this gap. Building on work in logic, probability, and causality, we establish the central role of (...) necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We propose a novel formulation of these concepts, and demonstrate its advantages over leading alternatives. We present a sound and complete algorithm for computing explanatory factors with respect to a given context and set of agentive preferences, allowing users to identify necessary and sufficient conditions for desired outcomes at minimal cost. Experiments on real and simulated data confirm our method’s competitive performance against state of the art XAI tools on a diverse array of tasks. (shrink)

The public forum has been connected to the functioning of democracy, expressive freedom, and the media's role in society. While the public forum's legal contours have been examined, the ethical foundation of the public forum has not. Relying on archival research, this article argues that ideas about the public forum can be traced to the pragmatism of Grenville Clark, who influenced ideas about the public forum through his work on the American Bar Association's Bill of Rights Committee.

This paper describes differences in two perspectives on the idea of virtue as a theoretical foundation for positive organizational ethics (POE). The virtue ethics perspective is grounded in the philosophical tradition, has classical roots, and focuses attention on virtue as a property of character. The positive social science perspective is a recent movement (e.g., positive psychology and positive organizational scholarship) that has implications for POE. The positive social science movement operationalizes virtue through an empirical lens that emphasizes virtuous behaviors. From (...) a virtue ethics perspective, a behaviorally based account of virtue is a weak theory of virtue. Observations are suggested for integrating the two perspectives. First, virtue should always be understood as an excellence and is often an optimal point between extreme dysfunctions on continuum of potential states. Second, an empirical exploration of virtue needs to account for character and context. Finally, the properties of organization-level virtue need to be further specified and explored. Implications and directions for future research are discussed. (shrink)

Through Narcissus' Glass Darkly presents a genealogy and critique of the ideal of conscience in modern philosophical theology, particularly in the writings of ...