ECHO CHAMBERS AND EPISTEMIC BUBBLES | Episteme | Cambridge Core

There is no fresh air: A problem with the concept of echo chambers

Standardly, echo chambers are thought to be structures that we should avoid. Agents should keep away from them, to be able to assess a fuller range of evidence and avoid having their confidence in that information manipulated. This paper argues against that standard view. Not only can echo chambers be neutral or good for us, but the existing definitions apply so widely that such chambers are unavoidable. We are all in large numbers of echo chambers at any time – they can be found not just on social media or in political groups, but in almost every social or epistemic group we could categorise ourselves into. Because we are finite and fallible, we cannot escape them and need to exist in them just to get by. The concept, then, does not actually capture something as structurally problematic as the paradigmatic cases would suggest. Our way of using the term in social epistemology needs to change.

On the epistemic structure of voluntary servitude in the infosphere

This paper introduces the concept of Voluntary Epistemic Servitude (VES) to describe a social-epistemic pathology generated by the contemporary infosphere. Drawing on Étienne de La Boétie’s Discours de la Servitude Volontaire as a theoretical resource, we argue that algorithmic systems produce conditions in which agents not only delegate their core belief-forming processes to nontransparent architectures but come to prefer and actively reproduce this delegation through social mechanisms structurally isomorphic to those La Boétie identified in political tyranny. We show that VES is irreducible to existing social-epistemic categories such as epistemic injustice (Fricker 2007), epistemic bubbles and echo chambers (Nguyen 2020), and veritistic failure (Goldman 1999) because it operates at the level of epistemic preference formation rather than credibility attribution or informational access. The paper identifies a preference-laundering mechanism by which algorithmic systems colonize the second-order epistemic desires of agents, thereby undermining the conditions of epistemic autonomy that social epistemology has largely presupposed. We further develop a precise account of reflective access that distinguishes algorithmic opacity from ordinary preference opacity, introduce the concept of epistemic counterfactual capacity with a modal analysis connecting it to Williamson’s (2000) safety condition, situate VES as a structurally induced epistemic vice (Cassam 2019) and a form of misaligned extended cognition (Clark and Chalmers 1998), and provide a typology of three algorithmic architectures through which VES operates. We conclude by stating an explicit normative bridge principle and drawing on La Boétie’s positive ideal of free horizontal epistemic bonds to sketch the preconditions for epistemic liberation in algorithmically mediated environments.

The Liar’s Dividend: Can Politicians Claim Misinformation to Evade Accountability?

This study addresses the phenomenon of misinformation about misinformation, or politicians "crying wolf"' over fake news. Strategic and false claims that stories are fake news or deepfakes may benefit politicians by helping them maintain support after a scandal. We posit that this benefit, known as the "liar's dividend," may be achieved through two politician strategies: by invoking informational uncertainty or by encouraging oppositional rallying of core supporters. We administer five survey experiments to over 15,000 American adults detailing hypothetical politician responses to stories describing real politician scandals. We find that claims of misinformation representing both strategies raise politician support across partisan subgroups. These strategies are effective against text-based reports of scandals, but are largely ineffective against video evidence and do not reduce general trust in media. Finally, these false claims produce greater dividends for politicians than alternative responses to scandal, such as remaining silent or apologizing.

Following news on social media boosts knowledge, belief accuracy and trust

Many worry that news on social media leaves people uninformed or even misinformed. Here we conducted a preregistered two-wave online field experiment in France and Germany (N = 3,395) to estimate the effect of following the news on Instagram and WhatsApp. Participants were asked to follow two accounts for 2 weeks and activate the notifications. In the treatment condition, the accounts were those of news organizations, while in the control condition they covered cooking, cinema or art. The treatment enhanced current affairs knowledge, participants’ ability to discern true from false news stories and awareness of true news stories, as well as trust in the news. The treatment had no significant effects on feelings of being informed, political efficacy, affective polarization and interest in news or politics. These results suggest that, while some forms of social media use are harmful, others are beneficial and can be leveraged to foster a well-informed society.

Epistemic Infrastructure: Building Shared Truth in an Era of Disaggregation

The Construct of Collective Perception

Echo Chambers and Their Effects on Economic and Political Outcomes

In this review, we survey the economics literature on echo chambers. We identify echo chambers as arising from a combination of two phenomena: ( a) the choice of individuals to segregate with like-minded ones, i.e., the creation of chambers, and ( b) behavioral biases that induce polarization when individuals exchange beliefs in these chambers, i.e., the echo. We summarize the literatures on these two phenomena and suggest how to combine the two literatures to gain insights about the effects of echo chambers on economic and political outcomes. We end by suggesting pathways for future research and discussing policy interventions to alleviate echo chambers.

Free Speech on the Internet: The Crisis of Epistemic Authority

Abstract. Much of our knowledge of the world comes not from direct sensory experience, but from reliance on epistemic authorities: individuals or institutions that tell us what we ought to believe. For example, what most of us believe about natural selection, climate change, or the Holocaust comes from our reliance on epistemic authorities (scientists, historians). Sustaining epistemic authority depends, crucially, on social institutions that inculcate reliable second-order norms about whom to believe about what. The traditional media were crucial, in the age of mass democracy, with promulgating and sustaining such norms. The internet has obliterated the intermediaries who made that possible, and, in the process, undermined the epistemic standing of actual experts. This essay considers some possible changes to existing free speech doctrine to remedy the epistemological crisis brought about by the internet.

The spreading of misinformation online

Significance The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web is a fruitful environment for the massive diffusion of unverified rumors. In this work, using a massive quantitative analysis of Facebook, we show that information related to distinct narratives––conspiracy theories and scientific news––generates homogeneous and polarized communities (i.e., echo chambers) having similar information consumption patterns. Then, we derive a data-driven percolation model of rumor spreading that demonstrates that homogeneity and polarization are the main determinants for predicting cascades’ size. , The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades’ size.

Disinformation and grievance narratives

Synthese - Disinformation is often defined as misleading content intended to instill false beliefs. But this definition is too narrow. We need to focus instead on its broader epistemic effects....

When everything is news, nothing is news

Thoughtlessly repeating PR talking points and sharing guesswork as rumor is creating a trust problem.

The social media context interferes with truth discernment

Simply considering whether to share news on social media reduces the extent to which people discriminate truth from falsehood.

Sharing without clicking on news in social media

Social media have enabled laypersons to disseminate, at scale, links to news and public affairs information. Many individuals share such links without first reading the linked information. Here we analysed over 35 million public Facebook posts with uniform resource locators shared between 2017 and 2020, and discovered that such ‘shares without clicks’ (SwoCs) constitute around 75% of forwarded links. Extreme and user-aligned political content received more SwoCs, with partisans engaging in it more than politically neutral users. In addition, analyses with 2,969 false uniform resource locators revealed higher shares and, hence, SwoCs by conservatives (76.94%) than liberals (14.25%), probably because, in our dataset, the vast majority (76–82%) of them originated from conservative news domains. Findings suggest that the virality of political content on social media (including misinformation) is driven by superficial processing of headlines and blurbs rather than systematic processing of core content, which has design implications for promoting deliberate discourse in the online public sphere.

Deep Storytelling: Collective Sensemaking and Layers of Meaning in U.S. Elections

Misinformation and disinformation about elections remain pressing concerns for researchers, policymakers, and the public. Critics, however, argue that fears surrounding these issues are exaggerated due to a lack of evidence of impact. This debate highlights the challenges inherent in assessing the impacts of misinformation, as the drivers of false and misleading content often exist in the context of a specific claim. To address this issue, we examined false and misleading information surrounding the 2020 and 2022 U.S. national elections, focusing on the contextual features of online conversations that fueled various rumors. We developed two qualitative codebooks, creating the second after realizing that the first, which labeled individual tweets, failed to capture broader rumoring dynamics. By integrating multi-layered qualitative coding with thematic analysis and quantitative visualizations, we show how influencers, political elites, and audiences collaboratively told deep stories from 2020 through 2022. As these stories were told, audiences interpreted events in 2022 through the lens of the 2020 story, guided by influencers' cues, leading to an evolution in storytelling style between the two election cycles. This ongoing performance was tailored to align with the incentive structures, affordances, and attention economy of social media. We combine deep stories with theories of collective sensemaking and rumoring, creating a framework to better assess the contextual features surrounding false and misleading information.

How Social Media Rewards Misinformation

A majority of false stories are spread by a small number of frequent users, suggests a new study co-authored by Yale SOM’s Gizem Ceylan. But they can be taught to change their ways.

Illusion of knowledge through Facebook news? Effects of snack news in a news feed on perceived knowledge, attitude strength, and willingness for discussions

Research indicates that using social network sites as a source for news increases perceived knowledge even if, objectively, people fail to acquire knowledge. This might result from the frequent repetition of topics in news posts caused by multiple news outlets posting about the same news topics and the algorithm that favors similar postings. These repeated encounters can have a positive effect on the perception of knowing more, even if actual learning hardly occurs. An experiment (N = 810, representative of German Internet users) tested these assumptions. Participants were assigned to one of four groups and received a news feed with no information, few news posts, many news posts, or a full-length news article. Results indicate that many news posts increased perceived knowledge that is not paralleled by a gain in factual knowledge. Perceived knowledge mediates effects of reading many news posts on more extreme attitudes and the willingness for discussions. Even if participants who read the news article gained factual knowledge, they did not feel more knowledgeable than participants who were exposed to a news feed containing news posts. The results emphasize the meaning of engaging with full news articles, both for learning facts and for more accurate knowledge assessments.