Mind and Language 36 (5):664-682 (2021)
AbstractIs there some general reason to expect organisms that have beliefs to have false beliefs? And after you observe that an organism occasionally occupies a given neural state that you think encodes a perceptual belief, how do you evaluate hypotheses about the semantic content that that state has, where some of those hypotheses attribute beliefs that are sometimes false while others attribute beliefs that are always true? To address the first of these questions, we discuss evolution by natural selection and show how organisms that are risk-prone in the beliefs they form can be fitter than organisms that are risk-free. To address the second question, we discuss a problem that is widely recognized in statistics – the problem of over-fitting – and one influential device for addressing that problem, the Akaike Information Criterion (AIC). We then use AIC to solve epistemological versions of the disjunction and distality problems, which are two key problems concerning what it is for a belief state to have one semantic content rather than another.
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Citations of this work
Disjunction and distality: the hard problem for purely probabilistic causal theories of mental content.William Roche & Elliott Sober - 2019 - Synthese 198 (8):7197-7230.
Disjunction and distality: the hard problem for purely probabilistic causal theories of mental content.William Roche - 2019 - Synthese 198 (8):7197-7230.
References found in this work
Evolution, population thinking, and essentialism.Elliott Sober - 1980 - Philosophy of Science 47 (3):350-383.
How to Tell When Simpler, More Unified, or Less A d Hoc Theories Will Provide More Accurate Predictions.Malcolm R. Forster & Elliott Sober - 1994 - British Journal for the Philosophy of Science 45 (1):1-35.