The Principal Principle Implies the Principle of Indifference

2019

Euro Jnl Phil Sci

Self Cite

This paper poses a problem for Lewis' Principal Principle in a subjective Bayesian framework: we show that, where chances inform degrees of belief, subjective Bayesianism fails to validate normal informal standards of what is reasonable. This problem points to a tension between the Principal Principle and the claim that conditional degrees of belief are conditional probabilities. However, one version of objective Bayesianism has a straightforward resolution to this problem, because it avoids this latter claim. The problem, then, offers some support to this version of objective Bayesianism. Keywords Bayesianism • Principal principle • Subjective Bayesianism • Objective Bayesianism • Pooling We show in Section 1 that standard subjective Bayesianism has a problem in accommodating David Lewis' Principal Principle. In Section 2, we see that the problem does not beset a recent version of objective Bayesianism. In Section 3, we consider three possible ways in which a subjectivist might try to avoid the problem but we argue that none of these suggestions succeed. We conclude that the problem favours objective Bayesianism over subjective Bayesianism (Section 4). In Section 4 we also compare our results to some other lines of recent work.

Section: Related Workmentioning

confidence: 96%

The Principal Principle and subjective Bayesianism

Wallmann

2019

Euro Jnl Phil Sci

Self Cite

“…Arguably, CBCP is poorly suited to objective Bayesianism because it can conflict with the Maximum Entropy Principle (Friedman and Shimony 1971;Williamson 2010, Chapter 4). Moreover, Hawthorne et al (2017) have argued that the Principal Principle in combination with CBCP is not suited to subjective Bayesianism because, under certain auxiliary assumptions about admissibility, it implies the Principle of Indifference, which is a kind of equivocation norm. Hence the Principal Principle, which requires CBCP if it is to play the role of an evidential norm, is on shakier ground than Chance Calibration, which doesn't depend on CBCP.…”

Section: Chance Calibrationmentioning

confidence: 99%

Calibration for Epistemic Causality

2019

Erkenn

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The epistemic theory of causality is analogous to epistemic theories of probability. Most proponents of epistemic probability would argue that one's degrees of belief should be calibrated to chances, insofar as one has evidence of chances. The question arises as to whether causal beliefs should satisfy an analogous calibration norm. In this paper, I formulate a particular version of a norm requiring calibration to chances and argue that this norm is the most fundamental evidential norm for epistemic probability. I then develop an analogous calibration norm for epistemic causality, argue that it is the only evidential norm required for epistemic causality, and show how an epistemic account of causality that incorporates this norm can be used to analyse objective causal relationships.

“…Objective Bayesians often explicitly endorse norms on belief which imply the Principle of Indifference, such as the Maximum Entropy Principle (Jaynes 1957 ; Williamson 2010 ). Moreover, as Hawthorne et al ( 2017 ) argue, Bayesians who endorse any principle which requires calibration of degrees of belief to some probabilities of which one has evidence—e.g., the Principal Principle, the Reflection Principle, or any testimony principle which posits deference to expert authorities—are also committed to a version of the Principle of Indifference.…”

Section: Three Versions Of the Principle Of Indifferencementioning

confidence: 99%

Justifying the principle of indifference

2018

Euro Jnl Phil Sci

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This paper presents a new argument for the Principle of Indifference. This argument can be thought of in two ways: as a pragmatic argument, justifying the principle as needing to hold if one is to minimise worst-case expected loss, or as an epistemic argument, justifying the principle as needing to hold in order to minimise worst-case expected inaccuracy. The question arises as to which interpretation is preferable. I show that the epistemic argument contradicts Evidentialism and suggest that the relative plausibility of Evidentialism provides grounds to prefer the pragmatic interpretation. If this is right, it extends to a general preference for pragmatic arguments for the Principle of Indifference, and also to a general preference for pragmatic arguments for other norms of Bayesian epistemology. Keywords Principle of indifference · Bayesianism · Epistemic consequentialism · AccuracyMany Bayesians are committed to some version or other of the Principle of Indifference, which holds that in certain situations one's degrees of belief should be equivocal. Section 1 introduces three such versions in order of increasing strength. In Section 2, I develop a consequentialist argument for the strongest version. This can be thought of as motivating the principle in terms of its pragmatic consequences: if one is to minimise worst-case expected loss, then one should satisfy the Principle of Indifference. As I explain in Section 3, an analogous argument can be constructed