Interpretive Blindness

TL;DR

This paper introduces the concept of interpretive blindness, an epistemic bias affecting learning from testimony, caused by the interplay of background beliefs and interpretation within Bayesian models, especially under argumentative completeness.

Contribution

It formalizes interpretive blindness as an epistemic bias in Bayesian models and analyzes how argumentative completeness in testimony can hinder learning.

Findings

Interpretive blindness arises from the dependence between beliefs and interpretation.

Argumentative completeness can prevent effective learning even with good epistemic practices.

The model highlights limitations in learning from certain types of testimony.

Abstract

We model here an epistemic bias we call \textit{interpretive 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, \textit{argumentative completeness}, can preclude learning in hierarchical Bayesian settings, even in the presence of constraints that are designed to promote good epistemic practices.