Synthesized answer
Interpretive blindness is a learning problem that occurs when someone gets information solely from what they read or hear [1]. It happens because a person's existing beliefs and how they understand new information are closely linked [2, 4]. This means that when people encounter new information, they tend to interpret it in a way that fits with what they already believe [2, 4]. A primary cause is relying on a limited number of sources for information, which strengthens their confidence in those sources and their existing beliefs [2, 3].
This bias can prevent learning because people will dismiss information that contradicts their current views [2]. For example, if someone believes a politician is honest, they might interpret the politician's silence on a scandal as a sign of integrity rather than an evasion [4]. The analogy for learning would be like looking at the world through a specific colored lens. If your lens is blue, everything you see will appear in shades of blue, and you might struggle to recognize or appreciate other colors, even if they are present [2, 4]. The passages do not offer a simpler analogy, but illustrate the concept by showing how beliefs shape…
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From the book
Interpretive Blindness Nicholas Asher 1 1 1 CNRS, IRIT and Julie Hunter 2 2 2 Linagora GSO Abstract We model here an epistemic bias we call 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, argumentative completeness , can preclude learning in hierarchical Bayesian settings, even…
ion to few sources of testimony and a natural co-dependence between beliefs and interpretation (Asher and Paul, 2018 ) . Relying on testimony from a restricted set of sources to update one’s beliefs leads to the mutual reinforcement of our confidence in the source and our belief in ; this creates a bias that can preclude learning when an agent tries to exploit new data that are incompatible with or simply distinct from . Agents who are interpretively blind will discount any evidence that challenges their beliefs. We use Wolpert’s 2018 extended Bayesian framework to prove our results. While IB…
humans (and perhaps soon by sophisticated machine learning algorithms) whose beliefs are guided and shaped by testimony. When learning through testimony—perhaps the primary way that most people acquire information nowadays—an agent acquires beliefs through conversations with other agents, or from books, newspapers or social networks, and so on. Typically, such people lack direct access to the phenomena described via that testimony. Typically too, humans only pay attention to a restricted set of bodies of testimony from a limited number of sources for their information—which makes sense in…
n learning because of a co-dependence between beliefs and the interpretation of evidence, in particular its reliability. In this case, we are talking of the interpretation of written or linguistically conveyed information. Others have already noted a co-dependence of beliefs and linguistic interpretation (Asher and Paul, 2018 ) . Consider this exchange. R: “Why hasn’t the senator commented on the story that he received undisclosed gifts from supporters?” A: “The Senator has declared every gift that he has received.” As Asher and Paul ( 2018 ) argue, one could interpret A’s response either as…
body of evidence can give a sense of community, as has been amply documented in the scholarly literature and the press. But this trade off can lead to a problem in learning: when we rely on testimony to learn and we restrict the testimony we pay attention to, the confirming evidence for the evaluation hypothesis and what it supports threaten to collapse into one. We now turn to see how iterated Bayesian updating in learning from testimony can ultimately lead to a situation where only evaluation hypotheses supporting our restricted evidence are credible and this leads to IB. 3 IB in a first…
More questions about this book
- The text states that interpretive blindness "follows from a co-dependence between background beliefs and interpretation... and the nature of contemporary testimony." Elaborate on *how* this co-dependence and the specific characteristic of contemporary testimony (argumentative completeness) interact to prevent an agent from updating their beliefs, even when presented with new, incompatible data.
- How does "argumentative completeness," as described, differ from simpler forms of bias like confirmation bias or selective exposure? Why is this distinction crucial for understanding its impact on learning within both standard and hierarchical Bayesian frameworks?
- The authors claim that argumentative completeness can preclude learning "even in the presence of constraints that are designed to promote good epistemic practices." What specific "good epistemic practices" might they be referring to, and why do they prove insufficient against interpretive blindness when testimony is argumentatively complete?
- Given that interpretive blindness stems from relying on a restricted set of testimony sources, what practical strategies could an individual or a society employ to actively combat this bias in a modern information landscape dominated by social media and specialized interest groups?