Probabilistic knowledge

This book argues that credences can be knowledge. Say you have . credence that a certain coin landed heads, . credence that your friend Jones smokes, and . credence that your friend Brown smokes. I argue that each of these credences can be knowledge, in just the same way that your full beliefs can be knowledge. Traditional epistemology has focused on the epistemic status of full beliefs in propositions, such as the proposition that you are not dreaming, or that God exists, or that you have hands. But in addition to having knowledge of black and white propositions, we have knowledge that comes in every shade of grey. This book is about credences, but not just about credences. More generally, it is about probabilistic beliefs. For instance, I argue that you can know that it might be raining outside,where this epistemicmodal belief cannot be reduced to full belief in any proposition. Similarly, your conditional beliefs and conditional credences can be probabilistic knowledge.Also, this book is about knowledge, but not just about knowledge—it is alsoabout belief andassertion.There is something common to credences, epistemic modal beliefs, conditional beliefs, conditional credences, and so on. The contents of these attitudes are sets of probability spaces over propositions, or probabilistic contents. Just as tradition holds that you believe and assert propositions, I hold that you can believe and assert probabilistic contents.Hence probabilistic contents play a central role not only in epistemology, but in the philosophy of mind and the philosophy of language as well. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for a wide range of contemporary debates. For instance, my arguments about probabilistic belief support a novel account of the relationship between full belief and credence. As I defend the claim that we can assert probabilistic contents, I develop and defend a formal semantics for epistemic modals and probability operators, as well as a formal semantics for indicative conditionals. Along the way, I give arguments that challenge the celebrated connection between indicative conditionals and conditional probability. In later chaptersof thebook, I discuss several arguments for the claimthatwe canperceive probabilistic contents, including arguments informed by Bayesian models of human visual perception. I develop several knowledge norms governing rational belief and action, including norms that have implications for what you should believe when you find out that you disagree with an epistemic peer. I spell out a precise interpretation of the claim that the resources of standard decision theory are inadequate when it comes to decisions about whether to have transformative experiences. I defend perceptual dogmatism from the objection that it is inconsistent with Bayesian principles of rational updating. Along with many philosophical questions, probabilistic knowledge also helps us answer questions of interest to broader audiences. For instance, accepting probabilistic knowledge should prompt us to rethink common negative evaluations of stereotypically female speech. Probabilistic knowledge plays an important role in legal standards of proof, such as the standard of proof beyond a reasonable doubt. The fact that legal proof requires probabilistic knowledge explains why merely statistical evidence is insufficient to license a legal verdict of guilt or liability. Finally, probabilistic knowledge can be used to explain why acts of racial profiling violate not only moral norms, but also epistemic norms. I hope that in addition to moving many philosophical debates forward, this book will also help move them outward, by identifying practical and political problems towhichmy central claimsmay be usefully applied. Some readers with limited time may be interested in reading selected portions of the book. Epistemologists will hit many important highlights by reading chapter , sections .–, and chapters  through . Philosophers of language will find it useful to focus on chapters –, chapter , and sections .–. For anyone wishing to read a condensed version of this book, say for one meeting of a graduate seminar or a reading group, I recommend sections .–, ., ., ., and .–, with the possible addition of section . for readers unfamiliar with the literature on epistemic modals, and sections . and .– for readers interested in practical applications of probabilistic knowledge. The main ten chapters of the book are accessible to readers with no background in formal semantics; the appendix is an additional chapter for linguistically-minded readers who would like this book to turn it up to eleven. Contents Preface ix . The case for probabilistic contents  . Probabilistic beliefs  . An argument for probabilistic contents of belief  . The roles played by contents of belief  . Full beliefs  . Alternative roles for contents of belief  . The case for probabilistic assertion  . Familiar arguments against propositional contents of assertion  . Foundational arguments for probabilistic contents of assertion  . Modeling communication  . Epistemic modals and indicative conditionals  . A test battery for probabilistic content  . Epistemic modals and probability operators  . Motivations for my semantics  . Embedded epistemic vocabulary  . Challenges for other theories  . A semantics for epistemic modals and probability operators  . A semantics for simple sentences  . The relationship between credence and full belief  . Indicative conditionals  . Probabilities of conditionals as conditional probabilities  . A semantics for conditionals  . Why probabilities of conditionals are not conditional probabilities  . A semantics for other logical operators  . The pragmatics of epistemic vocabulary  . The case for probabilistic knowledge  . The thesis that probabilistic beliefs can be knowledge  . Testimony  . Perception  . Arguments for probabilistic contents of experience  . Other sources of knowledge  . Justified true belief without knowledge  . Traditional theories of knowledge  . An alternative mental state?  . Applications  . Factivity  . Alternatives to probabilistic knowledge?  . The contents of knowledge ascriptions  . Frequently asked questions  . Relativism  . Objective chance  . Skepticism  . A skeptical puzzle  . The argument from inconsistency  . The argument from closure  . The argument from disjunction  . The argument from safety  . Knowledge and belief  . The knowledge norm of belief  . Peer disagreement  . Applying the knowledge norm of belief  . Statistical inference  . Responses to skepticism about perceptual knowledge  . Knowledge and action  . Knowledge norms of action  . Addressing objections  . Applying knowledge norms of action  . Pragmatic encroachment  . Transformative experience  . Knowledge and persons  . Statistical evidence  . An account of legal proof  . Applying knowledge standards of proof  . Racial and other profiling  . Applying the rule of consideration  Appendix: A formal semantics for epistemic vocabulary  A. Background  A. Epistemic modals and probability operators  A. Simple sentences  A. Indicative conditionals  A. Other logical operators  References  Index  Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. Sarah Moss argues that in addition to full beliefs, credences can constitute knowledge. For instance, your 0.4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, but of probabilistic contents. The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other. Traditional philosophical discussions of knowledge have focused on the epistemic status of full beliefs. This book argues that in addition to full beliefs, credences can constitute knowledge. For instance, your .4 credence that it is raining outside can constitute knowledge, in just the same way that your full beliefs can. In addition, you can know that it might be raining, and that if it is raining then it is probably cloudy, where this knowledge is not knowledge of propositions, but of probabilistic contents. The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other. "The notion of probabilistic content introduced in this book plays a central role not only in epistemology, but in the philosophy of mind and language as well. Just as tradition holds that you believe and assert propositions, you can believe and assert probabilistic contents. Accepting that we can believe, assert, and know probabilistic contents has significant consequences for many philosophical debates, including debates about the relationship between full belief and credence, the semantics of epistemic modals and conditionals, the contents of perceptual experience, peer disagreement, pragmatic encroachment, perceptual dogmatism, and transformative experience. In addition, accepting probabilistic knowledge can help us discredit negative evaluations of female speech, explain why merely statistical evidence is insufficient for legal proof, and identify epistemic norms violated by acts of racial profiling. Hence the central theses of this book not only help us better understand the nature of our own mental states, but also help us better understand the nature of our responsibilities to each other."-- Provided by publisher Sarah Moss Argues That In Addition To Full Beliefs, Credences Can Constitute Knowledge. She Introduces The Notion Of Probabilistic Content And Shows How It Plays A Central Role Not Only In Epistemology, But In The Philosophy Of Mind And Language. Just You Can Believe And Assert Propositions, You Can Believe And Assert Probabilistic Contents. Sarah Moss. Includes Bibliographical References (pages 243-259) And Index.