My aim in this paper is to engage with C. Thi Nguyen’s characterization of the echo chamber and to propose two things. First, I argue that a proper reading of his concept of echo chamber should make use of the notion of ignorance in the form of a structural epistemic insensitivity. My main contention is that ignorance as a substantive structural practice accounts for the epistemically deleterious effects of echo chambers. Second, I propose that from the talk of ignorance we (...) should be able to see echo chambers in terms of their more harmful impacts in our daily lives. To do that, I argue that we should think of echo chambers as tools to promote hermeneutical domination. If my representation of Nguyen’s concept is accurate, I believe we can see some important theoretical consequences stemming from the way Nguyen understands it. (shrink)

Epistemic injustice occurs when we fail to appropriately respect others as epistemic agents. Philosophers building on the work of Miranda Fricker, who introduced the concept, have focused on epistemic injustices involving certain social categories, particularly race and gender. Can there be epistemic injustice attached to political conviction and affiliation? I argue yes: politics can be a salient social category that draws epistemic injustice. Epistemic injustices might also be intersectional, based on the overlap of politics and some other identity category like (...) race or sex. Further, and more provocatively, I argue that political minorities in academia, in particular conservatives and libertarians, are most likely the victims of epistemic injustice on the basis of their politics. Such epistemic injustices might even be routine. Although more limited in scope and severity than other forms of epistemic injustice, political epistemic injustices in academia ought to be of special concern from a standpoint of social justice because of the academy’s central role in knowledge production and dissemination. (shrink)

Partisan epistemology – individuals granting greater credibility to co-partisan sources in evaluating information – is often taken to be evidence of directionally motivated reasoning in which concerns about group membership override concerns about accuracy. Against this dominant view, I outline a novel accuracy-based account of this mode of reasoning. According to this account, partisan epistemology stems from the inference that co-partisans are more likely to be right as they have superior epistemic access to the relevant facts and seek to realize (...) the correct values. I argue that this theory fits better with relevant findings than motivated-reasoning theories of partisan epistemology. Finally, I suggest it has adequate explanatory power vis-à-vis patterns of misinformation belief. (shrink)

Conviction Narrative Theory (CNT) is a theory of choice underradical uncertainty– situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people usenarratives– structured representations of causal, temporal, analogical, and valence relationships – rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, (...) narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels “right” to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences. (shrink)

Why do people who disagree about one subject tend to disagree about other subjects as well? In this paper, we introduce a model to explore this phenomenon of ‘epistemic factionization’. Agents attempt to discover the truth about multiple propositions by testing the world and sharing evidence gathered. But agents tend to mistrust evidence shared by those who do not hold similar beliefs. This mistrust leads to the endogenous emergence of factions of agents with multiple, highly correlated, polarized beliefs.

Many philosophers hold there are genuine cases of culpable ignorance. This paper argues that there are conditions that can render knowledge epistemically culpable too. First, we contrast culpable ignorance with morally culpable knowledge. Second, we examine the nature of epistemically culpable knowledge using a key example. We then highlight empirical support for the claim that there are real-world conditions that make epistemically culpable knowledge possible. Next, we survey three kinds of epistemic culpability fostered by culpable knowledge. Finally, we address the (...) benefits objection and argue that it fails. (shrink)

The current research investigates how prior preferences affect causal learning. Participants were tasked with repeatedly choosing policies (e.g., increase vs. decrease border security funding) in order to maximize the economic output of an imaginary country and inferred the influence of the policies on the economy. The task was challenging and ambiguous, allowing participants to interpret the relations between the policies and the economy in multiple ways. In three studies, we found evidence of motivated reasoning despite financial incentives for accuracy. For (...) example, participants who believed that border security funding should be increased were more likely to conclude that increasing border security funding actually caused a better economy in the task. In Study 2, we hypothesized that having neutral preferences (e.g., preferring neither increased nor decreased spending on border security) would lead to more accurate assessments overall, compared to having a strong initial preference; however, we did not find evidence for such an effect. In Study 3, we tested whether providing participants with possible functional forms of the policies (e.g., the policy takes some time to work or initially has a negative influence but eventually a positive influence) would lead to a smaller influence of motivated reasoning but found little evidence for this effect. This research advances the field of causal learning by studying the role of prior preferences, and in doing so, integrates the fields of causal learning and motivated reasoning using a novel explore‐exploit task. (shrink)