Confessions of a Modest Bayesian

References

• Philosophy of Science , 56 See my ‘Bayesianism Without the Black Box,’ 48–69.
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• Philosophical Topics See my ‘Not by the Book,’ (forthcoming).
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• These conditions may not seem so modest to some. For example (they may note), it is an axiom of the probability calculus that every tautology has the maximum probability. This being so, you will count as satisfying the second condition only if you invest the maximum amount of confidence in every tautology. But, if so (they may argue), surely the second condition demands too much. The tautologies are infinite both in number and complexity. None of us possesses a sufficient amount of either logical acumen or time to recognize them all. Similar complaints can be made about the theorem that no hypothesis is more probable than any of its consequences. But the complaint mistakes a regulative ideal for a regulation. As a regulation, the two conditions would indeed require you to succeed in investing the maximum amount of confidence in every tautology. But, as a regulative ideal, they require only that you invest maximum confidence in h if provided proof that h is a tautology. (And, likewise, that you not invest more confidence in h than in g if provided proof that h entails g.) And surely this is a requirement one can justifiably call modest.
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• Miller , Richard W. 1987 . Fact and Method Princeton : Princeton University Press . See, for example, 321.
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• Glymour , Clark . 1980 . Theory and Evidence Princeton : Princeton University Press . 83–4
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• Putnam , Hilary . 1975 . “ ‘Probability and Confirmation,’ in Putnam's ” . In Mathematics, Matter and Method Cambridge : Cambridge University Press . See
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• Pollock , John . 1986 . Contemporary Theories of Knowledge Totowa , NJ : Rowman and Littlefield . See 7–8. (where the contrast between epistemic and prudential reasons is drawn by an example similar to the one I have used) and 99–100. (where an objection not unlike this one is advanced against the Dutch Book Argument).
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• And that, among the hypotheses that T entails and C does not, there are hypotheses of whose truth you are not certain.
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• 1981 . Philosophical Explanations Cambridge , MA : Harvard University Press . This is a paraphrase of Robert Nozick, 255.
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• Jeffrey's , C. , ed. 1970 . Induction, Acceptance and Partial Belief Dordrecht : D. Reidel . To use Richard phrase, from ‘Dracula Meets Wolfman: Acceptance vs. Partial Belief,’ in Marshall Swain, ed., (157–85, at 172.
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• Miller , See . ch. 6 and 7; also look at the many discussions of what it is rational to believe or accept in the face of the lottery described earlier.
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• 1981 . The Journal of Philosophy , 78 In what follows I sketch an account of belief and methodology I first advanced (as an account of rational acceptance) in my ‘A Bayesian Theory of Rational Acceptance,’ (305–30and ‘Rational Acceptance,’ Philosophical Studies 40(1981) 129–45. The defense I offer on its behalf is, however, new. The account was inspired by the one offered in Ronald B. DeSousa, ‘How to Give a Piece of Your Mind: Or, The Logic of Belief and Assent,’ The Review of Metaphysics 25(1971) 52–79., at 62–3.
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• 1967 . Gambling with Truth The view that, in determining what to accept, we seek both comprehensiveness and avoidance of error, has played a central role in the work of Isaac Levi (see [New York: Knopf ] and The Enterprise of Knowledge [Cambridge, MA: MIT Press 1980]). But Levi holds a variant on the view, criticized earlier, that belief is a state of certainty. (For him, maximal confidence is a necessary, though not sufficient, condition of acceptance.) So, from my point of view, Levi can be said to have taken (indeed, pioneered) a correct approach to rational methodology but to have applied it to the wrong thing. (For a more extended discussion, see my review of Levi's The Enterprise of Knowledge, The Philosophical Review 92 (1983) 310–16.) Much more recently Patrick Maher has also construed comprehensiveness and avoidance of error as the aims of rational acceptance. But his account of what acceptance is, though it displays some affinity with the present proposal for defining belief, does not meet the Bayesian challenge. According to Maher, ‘acceptance of H is the state expressed by sincere intentional assertion of H' (Patrick Mayer, Betting on Theories [Cambridge: Cambridge University Press 1993], 132). The trouble here is that, if dictionary definitions are to be trusted (and Maher offers no alternative), an intentional assertion counts as sincere if and only if the asserter believes her assertion to be true. But what is belief? If it is just acceptance by another name, than Maher's definition fails to meet the Bayesian challenge: it presupposes the intelligibility of acceptance. And if belief is something distinct from acceptance, then Maher's definition would seem to be mistaken. For it is a person's belief that H, not her acceptance that H, that is necessary and sufficient for her intentional assertion of H to count as sincere— which would seem to indicate that it is the belief that H, not the acceptance of H, that sincere intentional assertion of H expresses.
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• This objection is due (independently) to Barry Loewer and Patrick Maher, each of whom pressed it upon me in correspondence. Recently the latter has committed it to print. (See Maher, 155–6.)
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• Bas , C. 1983 . “ ‘Glymour on Evidence and Explanation/in John Earman, ed. ” . In Testing Scientific Theories Minneapolis : University of Minnesota Press . See Van Fraassen (165–76, where Van Fraassen argues that the very features of powerful theories that make them seem attractive make them less probable and, hence, less worthy of belief. I address his argument in ‘Believing the Improbable,’ Philosophical Studies (forthcoming).
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• 1984 . Erkentniss , 15 : 469 See, for example, Stephen Leeds, ‘Theories of Reference and Truth,’ (1978; and Robert Brandom, ‘Reference Explained Away,’ The Journal of Philosophy 81—92.
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• I would like to thank Joan Weiner for comments on earlier drafts of this paper. The research of which this paper is, in part, a product was supported by a grant from the National Science Foundation.
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