دانلود کتاب 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.