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University of Massachusetts Amherst ScholarWorks@UMass Amherst Open Access Dissertations 9-2010 Bayesian Epistemology and Having Evidence Jeffrey Dunn University of Massachusetts Amherst, [email protected] Follow this and additional works at: https://scholarworks.umass.edu/open_access_dissertations Part of the Philosophy Commons Recommended Citation Dunn, Jeffrey, "Bayesian Epistemology and Having Evidence" (2010). Open Access Dissertations. 273. https://scholarworks.umass.edu/open_access_dissertations/273 This Open Access Dissertation is brought to you for free and open access by ScholarWorks@UMass Amherst. It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of ScholarWorks@UMass Amherst. For more information, please contact [email protected]. BAYESIAN EPISTEMOLOGY AND HAVING EVIDENCE A Dissertation Presented by JEFFREY STEWART DUNN Submitted to the Graduate School of the University of Massachusetts Amherst in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY September 2010 Department of Philosophy © Copyright by Jeffrey Stewart Dunn 2010 All Rights Reserved BAYESIAN EPISTEMOLOGY AND HAVING EVIDENCE A Dissertation Presented by JEFFREY STEWART DUNN Approved as to style and content by: ______________________________________________ Hilary Kornblith, Chairperson ______________________________________________ Phillip Bricker, Member ______________________________________________ David Christensen, Member ______________________________________________ Christopher Meacham, Member ______________________________________________ Shlomo Zilberstein, Member _______________________________________ Phillip Bricker, Head Department of Philosophy DEDICATION To Helen. ACKNOWLEDGMENTS In writing this dissertation I have been helped in many ways and by many people. To each of these people I am extremely grateful. First and foremost, I express my deepest gratitude to my advisor, Hilary Kornblith. Hilary is everything that an advisor should be. He always made himself available for discussion, he provided me with endless good advice, he challenged me philosophically, and he showed me how many things outside philosophy are relevant to philosophy. On top of all that he possesses an uncanny ability to return drafts—with comments!—in record time. I thank him for all he has done. I also sincerely thank Chris Meacham. Chris was always ready to discuss my new ideas, and provide invaluable feedback. He patiently taught me about how to use formal methods, and corrected my many errors and false starts as I was getting the hang of it. I also thank David Christensen and Phil Bricker for challenging and helpful comments on many parts of this dissertation. I thank Shlomo Zilberstein for serving on my committee and for introducing me to computer science. I am also grateful to those faculty members who weren’t on my committee, but provided help on the dissertation or who were especially instrumental in helping me learn how to do philosophy. I thank Fred Feldman, Jonathan Schaffer, Kevin Klement, Casey Perin, Ed Gettier, Pete Graham, Brad Skow, Lynne Baker, Joe Levine, and Louise Antony. I am especially grateful to Beth Grybko for her tireless help with the administrative aspects of successfully navigating graduate school and completing a dissertation. v In writing this disseration I have also benefited from many discussions with fellow graduate students at UMass. I especially thank Kristoffer Ahlstrom, Indrani Bhattacharjee, Jim Binkoski, Heidi Buetow, Donovan Cox, Sam Cowling, Jeremy Cushing, Lowell Friesen, Jayme Johnson, Namjoong Kim, Justin Klocksiem, Casey Knight, Barak Krakauer, Uri Leibowitz, Peter Marchetto, Meghan Masto, Kirk Michaelian, Josh Moulton, Kristian Olsen, James Platt, Alex Sarch, and Kelly Trogdon. Ed Ferrier and Einar Bohn deserve special thanks. They provided much helpful philosophical discussion, but it is their friendship, sense of humor, and their love of Fitzwilly’s that made my time at graduate school much better than it would have otherwise been. I am also deeply grateful to my parents for their love and their enthusiastic support of my decision to go to graduate school. The environment of learning that they created in our home has had a significant impact on who I am, my interest in philosophy, and on my ability to complete this dissertation. I also thank my parents-in- law for their generosity, support, and kindness. Finally, my deepest gratitude is owed to my wife, Helen. I would not have completed this dissertation were it not for her kind and loving support. She has picked me up when things looked grim and celebrated with me when things were going well. I look forward to enjoying the future ups and downs of life with her, and I sincerely thank her for all her love and support. vi ABSTRACT BAYESIAN EPISTEMOLOGY AND HAVING EVIDENCE SEPTEMBER 2010 JEFFREY STEWART DUNN, B.A., WASHINGTON STATE UNIVERSITY Ph.D., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Hilary Kornblith Bayesian Epistemology is a general framework for thinking about agents who have beliefs that come in degrees. Theories in this framework give accounts of rational belief and rational belief change, which share two key features: (i) rational belief states are represented with probability functions, and (ii) rational belief change results from the acquisition of evidence. This dissertation focuses specifically on the second feature. I pose the Evidence Question: What is it to have evidence? Before addressing this question we must have an understanding of Bayesian Epistemology. The first chapter argues that we should understand Bayesian Epistemology as giving us theories that are evaluative and not action-guiding. I reach this verdict after considering the popular ‘ought’-implies-‘can’ objection to Bayesian Epistemology. The second chapter argues that it is important for theories in Bayesian Epistemology to answer the Evidence Question, and distinguishes between internalist and externalist answers. The third and fourth chapters present and defend a specific answer to the Evidence Question. The account is inspired by reliabilist accounts of justification, and vii attempts to understand what it is to have evidence by appealing solely to considerations of reliability. Chapter 3 explains how to understand reliability, and how the account fits with Bayesian Epistemology, in particular, the requirement that an agent’s evidence receive probability 1. Chapter 4 responds to objections, which maintain that the account gives the wrong verdict in a variety of situations including skeptical scenarios, lottery cases, scientific cases, and cases involving inference. After slight modifications, I argue that my account has the resources to answer the objections. The fifth chapter considers the possibility of losing evidence. I show how my account can model these cases. To do so, however, we require a modification to Conditionalization, the orthodox principle governing belief change. I present such a modification. The sixth and seventh chapters propose a new understanding of Dutch Book Arguments, historically important arguments for Bayesian principles. The proposal shows that the Dutch Book Arguments for implausible principles are defective, while the ones for plausible principles are not. The final chapter is a conclusion. viii TABLE OF CONTENTS Page ACKNOWLEDGMENTS ................................................................................................ v ABSTRACT....................................................................................................................vii LIST OF TABLES.........................................................................................................xiv CHAPTER INTRODUCTION ................................................................................................ 1 1. BAYESIAN EPISTEMOLOGY AND ‘OUGHT’-IMPLIES-‘CAN’.................. 4 1.1 Introduction..................................................................................................... 4 1.2 Bayesian Epistemology and Rationality ......................................................... 4 1.3 Survey of Arguments ...................................................................................... 7 1.4 The Argument ............................................................................................... 10 1.5 The Anti-Voluntarist Problem ...................................................................... 14 1.5.1 Premise (V1) .................................................................................. 15 1.5.2 Premise (V2) .................................................................................. 18 1.6 Misunderstanding Bayesian Epistemology................................................... 26 1.7 Understanding Bayesian Epistemology ........................................................ 30 1.8 Conclusion .................................................................................................... 35 2. EVIDENCE: INTERNAL AND EXTERNAL................................................... 37 2.1 Introduction................................................................................................... 37 2.2 Why We Need an Account of Having Evidence .......................................... 39 2.2.1 Case 1............................................................................................. 42 2.2.2 Case 2............................................................................................. 44 2.3 Internalism
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