? Deliberation , Judgement and the Nature of Evidence ?

One kind of deliberation involves an individual reassessing the strengths of her beliefs in the light of new evidence. Bayesian epistemology measures the strength to which one ought to believe a proposition by its probability relative to all available evidence, and thus provides a normative account of individual deliberation. This can be extended to an account of individual judgement by treating the act of judgement as a decision problem, amenable to the tools of decision theory. A normative account of public deliberation and judgement can be provided by merging the evidence of the individuals in question and calculating appropriate Bayesian probabilities and judgement thresholds relative to this merged evidence. But this formal epistemology for deliberation and judgement lacks substance without an account of how evidence can be merged. And in order to provide such an account, we need in turn an account of what the evidence is that grounds Bayesian probabilities. This paper attempts to tackle these two concerns. After finding fault with several views on the nature of evidence (the views that evidence is knowledge; that evidence is whatever is fully believed; that evidence is observationally set credence; that evidence is information), it is argued that evidence is whatever is rationally taken for granted. This view has consequences for an account of merging, and it is shown that standard axioms for merging need to be altered somewhat. §1 Deliberation and Judgement Bayesian epistemology provides a natural account of certain questions to do with judgement and doxastic deliberation: Individual Deliberation. How strongly should I believe θ? Individual Judgement. Should I judge θ as true? Public Deliberation. How strongly should we believe θ? Public Judgement. Should we judge θ as true? Let us consider these questions in turn. ¶ Individual Deliberation. Turning first to the question of individual deliberation, the Bayesian would answer: believe θ to degree PE(θ), where PE is your rational belief function, relative to your total evidence E, which assigns a degree of belief to each proposition θ that is expressible in your language. Bayesians agree that to count as rational, your belief function must be a probability function and must satisfy constraints imposed by evidence E. (Bayesians disagree about exactly what constraints evidence imposes, about how belief functions should be updated in the light of new evidence, and about whether further norms impose constraints on the belief function, but these disagreements will not be relevant to the concerns of this paper.) Since PE(θ) varies only with E and θ, for individual deliberation to result in a change in strength of belief in θ, the evidence base E must change, either through introspection or through observation or other forms of external interaction. ¶ Individual Judgement. To address the question of individual judgement, the Bayesian can treat the decision as to whether or not to judge θ to be true as she would treat any other decision, by invoking the apparatus of Bayesian decision theory. The Bayesian’s answer to this question would then be: judge θ as true if the expected utility of judging θ is greater than that of not judging θ. Bayesian decision theory presumes that an agent is equipped with a utility function as well as a belief function, and that decision matrices can be populated with these utilities in order to evaluate the prospects of alternative choices. For example, a decision matrix for judging θ might look like: