Interpretive Blindness
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Abstract (arXiv)
We model here an epistemic bias we call textitinterpretive blindness (IB). IB is a special problem for learning from testimony, in which one acquires information only from text or conversation. We show that IB follows from a co-dependence between background beliefs and interpretation in a Bayesian setting and the nature of contemporary testimony. We argue that a particular characteristic contemporary testimony, textitargumentative completeness, can preclude learning in hierarchical Bayesian settings, even in the presence of constraints that are designed to promote good epistemic practices.
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References · 4
- 2016Understanding deep learning requires rethinking generalizationcited by 1,674
- 2017Exploring Generalization in Deep Learningcited by 600
- 2017Generalization in Deep Learningcited by 146
- 2013Loopy Belief Propagation for Approximate Inference: An Empirical Studycited by 76
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