Paul Mayer

In this book and in its sequels, Warrant and Proper Function and Warranted Christian Belief, I examine the nature of epistemic warrant, that quantity, enough of which distinguishes knowledge from mere true belief. Contemporary epistemologists seldom focus attention on the nature of warrant; and when they do, they display deplorable diversity: some claim that what turns true belief into knowledge is a matter of epistemic dutifulness, others that it goes by coherence, and still others that it is conferred by reliability. I shall argue that none of these claims is correct, and (in Warrant and Proper Function) suggest a more satisfactory alternative. In the present book, I survey current contributions to the discussion of warrant and neighboring issues. I begin with internalism, looking first at the carefully crafted foundationalist internalism of Roderick Chisholm (Chs. 2 and 3). To better understand Chisholm and other internalists, however, I first make a preliminary excursus (Ch 1) into the classical internalism of Descartes, Locke, and others. After Chisholmian internalism, I turn to coherentism, which for classificatory purposes I take as a form of internalism. In the next three chapters, I consider coherentism taken generally (Ch. 4), the specific version of coherentism developed by Laurence BonJour (Ch. 5), and contemporary Bayesian versions of coherentism (Chs. 6 and 7). Next (Ch. 8), there is the more attenuated internalism of John Pollock, which I see as a transition from internalism to externalism. Finally, I examine the reliabilist and externalist views of William Alston, Fred Dretske, and Alvin Goldman (Ch. 9), and close with a preview of Warrant and Proper Function (Ch. 10).

When _After Virtue_ first appeared in 1981, it was recognized as a significant and potentially controversial critique of contemporary moral philosophy. _Newsweek _called it “a stunning new study of ethics by one of the foremost moral philosophers in the English-speaking world.” Since that time, the book has been translated into more than fifteen foreign languages and has sold over one hundred thousand copies. Now, twenty-five years later, the University of Notre Dame Press is pleased to release the third edition of _After Virtue_, which includes a new prologue “_After Virtue_ after a Quarter of a Century.” In this classic work, Alasdair MacIntyre examines the historical and conceptual roots of the idea of virtue, diagnoses the reasons for its absence in personal and public life, and offers a tentative proposal for its recovery. While the individual chapters are wide-ranging, once pieced together they comprise a penetrating and focused argument about the price of modernity. In the Third Edition prologue, MacIntyre revisits the central theses of the book and concludes that although he has learned a great deal and has supplemented and refined his theses and arguments in other works, he has “as yet found no reason for abandoning the major contentions” of this book. While he recognizes that his conception of human beings as virtuous or vicious needed not only a metaphysical but also a biological grounding, ultimately he remains “committed to the thesis that it is only from the standpoint of a very different tradition, one whose beliefs and presuppositions were articulated in their classical form by Aristotle, that we can understand both the genesis and the predicament of moral modernity.”

_Why efforts to create a scientific basis of morality are neither scientific nor moral_ In this illuminating book, James Davison Hunter and Paul Nedelisky trace the origins and development of the centuries-long, passionate, but ultimately failed quest to discover a scientific foundation for morality. The “new moral science” led by such figures as E. O. Wilson, Patricia Churchland, Sam Harris, Jonathan Haidt, and Joshua Greene is only the newest manifestation of that quest. Though claims for its accomplishments are often wildly exaggerated, this new iteration has been no more successful than its predecessors. But rather than giving up in the face of this failure, the new moral science has taken a surprising turn. Whereas earlier efforts sought to demonstrate what is right and wrong, the new moral scientists have concluded, ironically, that right and wrong don’t actually exist. Their (perhaps unwitting) moral nihilism turns the science of morality into a social engineering project. If there is nothing moral for science to discover, the science of morality becomes, at best, a feeble program to achieve arbitrary societal goals. Concise and rigorously argued, _Science and the Good_ is a definitive critique of a would-be science that has gained extraordinary influence in public discourse today and an exposé of that project’s darker turn.

This book addresses controversies concerning the epistemological foundations of data science: Is it a genuine science? Or is data science merely some inferior practice that can at best contribute to the scientific enterprise, but cannot stand on its own? The author proposes a coherent conceptual framework with which these questions can be rigorously addressed. Readers will discover a defense of inductivism and consideration of the arguments against it: an epistemology of data science more or less by definition has to be inductivist, given that data science starts with the data. As an alternative to enumerative approaches, the author endorses Federica Russo’s recent call for a variational rationale in inductive methodology. Chapters then address some of the key concepts of an inductivist methodology including causation, probability and analogy, before outlining an inductivist framework. The inductivist framework is shown to be adequate and useful for an analysis of the epistemological foundations of data science. The author points out that many aspects of the variational rationale are present in algorithms commonly used in data science. Introductions to algorithms and brief case studies of successful data science such as machine translation are included. Data science is located with reference to several crucial distinctions regarding different kinds of scientific practices, including between exploratory and theory-driven experimentation, and between phenomenological and theoretical science. Computer scientists, philosophers and data scientists of various disciplines will find this philosophical perspective and conceptual framework of great interest, especially as a starting point for further in-depth analysis of algorithms used in data science.