Synthese (1-2):1-28 (2020)

Authors
Joe Roussos
Institute for Futures Studies
Abstract
When an agent learns of an expert's credence in a proposition about which they are an expert, the agent should defer to the expert and adopt that credence as their own. This is a popular thought about how agents ought to respond to (ideal) experts. In a Bayesian framework, it is often modelled by endowing the agent with a set of priors that achieves this result. But this model faces a number of challenges, especially when applied to non-ideal agents (who nevertheless interact with ideal experts). I outline these problems, and use them as desiderata for the development of a new model. Taking inspiration from Richard Jeffrey's development of Jeffrey conditioning, I develop a model in which expert reports are taken as exogenous constraints on the agent's posterior probabilities. I show how this model can handle a much wider class of expert reports (for example reports of conditional probabilities), and can be naturally extended to cover propositions for which the agent has no prior.
Keywords expert deference  belief revision  awareness  expert disagreement
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Reprint years 2020
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DOI 10.1007/s11229-020-02942-3
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References found in this work BETA

The Logic of Decision.Richard C. Jeffrey - 1965 - New York, NY, USA: University of Chicago Press.
Accuracy and the Laws of Credence.Richard Pettigrew - 2016 - Oxford University Press UK.
Risk and Rationality.Lara Buchak - 2013 - Oxford University Press.
Reflection and Disagreement.Adam Elga - 2007 - Noûs 41 (3):478–502.
Decision Theory with a Human Face.Richard Bradley - 2017 - Cambridge University Press.

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