2. Nguyen on Epistemic Bubbles and Echo Chambers

The term ‘epistemic bubble’ is used to refer to a number of related phenomena in the literature (see Sunstein, Reference Sunstein2018; Pariser, Reference Pariser2011). For Nguyen (Reference Thi Nguyen2020), an epistemic bubble is a social epistemic structure that merely omits relevant information, or sources thereof, from an agent's network. Bubbles are formed, not necessarily by a deliberate attempt to limit or exclude information, but simply because agents exert some degree of control over who they connect with on social media; and these people – typically friends, family, colleagues, or those with whom the agent shares some common interest – will in many cases have similar beliefs and values to the agent's own, at least within particular domains of discourse. Of course, it is not always the case that we have much in common with family, friends, and colleagues, but those in our social media networks with whom we disagree can be easily ‘muted’ to hide their content from our feeds, leaving only posts from sources that we approve of, or agree with. Choosing who we connect with online is perhaps not in itself problematic. However, epistemic problems arise when our online social networks are also used as significant sources of information about the world. For many of us, much of the news we are exposed to comes in the form of online articles and posts that have been shared by people we have chosen to populate our social networks. The composition of these networks may differ across social media platforms. For example, on Facebook, our networks will likely be dominated by our friends, family, and co-workers; on platforms like Twitter and Instagram, by contrast, our networks may include many more members whom we do not know personally (either online or offline). Where we choose who populates our social media feeds, the result is a self-imposed filter on the nature of the information we consume, which tends to merely confirm, rather than challenge or extend, our existing worldview. As Nguyen writes, ‘we impose on ourselves a narrowed and self-reinforcing epistemic filter, which leaves out contrary views and illegitimately inflates our epistemic self-confidence.’ (Nguyen, Reference Thi Nguyen2020, p. 142)

Agents may exert a significant degree of control over what information they consume offline too, of course. For example, we decide which newspapers to read, and we can often avoid talking in person to the people we disagree with, or about topics that we disagree over. Thus, social media's impact on the development of our epistemic bubbles is partly a matter of degree. However, there are also important differences in kind when it comes to the manner in which information is selected for our consumption: on many social media platforms, the epistemic filter that we choose to impose on ourselves is amplified by algorithms that feed us whatever content best succeeds in keeping us from disengaging.Footnote ¹ Moreover, users are typically unaware of how these algorithms work (Nguyen, Reference Thi Nguyen2020, p. 144; Record and Miller, Reference Miller and Record2013).

Nguyen argues that it is important to distinguish epistemic bubbles from echo chambers. Echo chambers, on Nguyen's view, are social epistemic structures in which contrary information or dissenting sources are actively discredited. Following Jamieson and Cappella (Reference Jamieson and Cappella2008), Nguyen claims that the shared beliefs of those within an echo chamber include reasons to distrust those on the outside (Reference Thi Nguyen2020, p. 146). Echo chambers thus serve to prevent uptake of certain kinds of information. Because of this, unlike an epistemic bubble, information that conflicts with an agent's worldview may in fact exist within an echo chamber. The problem is that this information is rejected: it is ignored, devalued, or undermined, and may even play a role in strengthening the ideology prevalent within the chamber, and the conviction of its members.

Nguyen argues that these two phenomena have typically been lumped together in the literature but that it is vital to distinguish between them because the kinds of harms they cause are distinct and the ways to counteract their problematic effects will differ (p. 142).Footnote ² Within an epistemic bubble, the problem is mere lack of exposure to information – epistemic bubbles lack ‘coverage reliability’ (Goldberg, Reference Goldberg, Goldman and Whitcomb2011): they expose the agent only to information that is deemed important and interesting by others in the network, but this does not necessarily include all information that would be important or relevant for the agent herself. As such, Nguyen suggests that introducing the missing information – and thus improving coverage reliability – may be enough to burst a bubble. In contrast, exposure to new information, on its own, would not enable an agent to escape an echo chamber as the echo chamber encourages the agent trapped inside to discredit information from outside sources. Given this understanding of the differences between these structures, Nguyen (Reference Thi Nguyen2020, p. 154) claims that escaping an epistemic bubble is comparatively straightforward. In contrast, escaping an echo chamber is far more difficult: dissenting voices will reinforce an echo chamber, and so mere exposure to information may be, at best, useless and, at worst, counterproductive.

In this paper, my primary aim is to argue that it is more difficult to escape an epistemic bubble than has been recognised in the literature. The reason for this is the relationship between epistemic bubbles, on the one hand, and the conditions conducive to successful communication, on the other. Roughly, the idea is this: an agent's interpretative resources cannot outstrip the information that is available to her within her epistemic bubble. Interpreting others within the same bubble is relatively easy because interlocutors within a bubble will typically possess similar interpretative dispositions (at least with respect to certain domains). However, interpreting sources from outside a bubble can be very difficult because the agent is thereby attempting to communicate with an interlocutor in the absence of shared contextual information or common ground. As I will argue, mere exposure to information will not help to burst a bubble because the agent may still lack sufficient resources to build a shared context for interpretation. To show this, I will first explain a range of challenges common in online communication that stem from differences in the interlocutors’ respective contextual assumptions. I will then argue for a particular view of the relationship between these communicative issues and the epistemic problems described by Nguyen. It is worth noting that I don't intend my argument in what follows as a sharp criticism of Nguyen's work. I take it that his point in emphasising the relative ease with which we can escape an epistemic bubble is to highlight the difficulty of escaping an echo chamber in comparison, and the distinctive nature of the challenge involved. Nonetheless, I think it is important to attend to obstacles to escaping epistemic bubbles that have been neglected in the literature. I will ultimately argue that epistemic bubbles are not best thought of as structures that we can burst or shatter at all. Rather, epistemic bubbles mark the horizon of our epistemic perspective on the world: they are structures that we can expand, but never escape.

3. Communication and Communicating Online

Whether online or offline, communication involves substantial reliance on context. A context of utterance is the environment or conversational setting in which the utterance is produced. It includes both external physical features of this environment – perhaps just those that are epistemically accessible – as well as facts about the interlocutors’ mental states.Footnote ³ When it comes to understanding communication, what is important is each interlocutor's perspective on the context of utterance (where these perspectives are just one facet of the context of utterance itself). This is a cognitive category, comprising information – knowledge, beliefs, experiences, etc. – that interlocutors bring to bear in their production and interpretation of an utterance. In principle, any information could be relevant here, but common factors include beliefs about the earlier conversation leading up to the exchange, about an interlocutor's habits, preferences, goals, and motivations, about an interlocutor's social identity, about social institutions, about the physical environment in which the utterance is produced, about stereotypes and ‘lexical effects’ associated with expressions used in the utterance, and about conversational principles or norms (see Bezuidenhout, Reference Bezuidenhout2002, p. 177; Cappelen and Lepore, 2005). Call this category ‘contextual information’ or ‘contextual assumptions’. Where the interpretative resources, and knowledge of the language, required to correctly interpret an utterance are largely shared across interlocutors (either prior to the utterance, or as a result of information introduced by the utterance), we can think of this as ‘common ground’ in Stalnaker's (Reference Stalnaker and Cole1978, Reference Stalnaker2002) sense. Stalnaker does not require that interlocutors’ perspectives on the common ground align perfectly (Reference Stalnaker2002, p. 701). However, in this paper, I am primarily concerned with communication in which there are more significant discrepancies between these perspectives – that is, cases in which there is little common ground between participants. Stalnaker (Reference Stalnaker and Cole1978) treats these as ‘defective contexts’.Footnote ⁴ As we will see, defective contexts are especially common in certain kinds of online environment.

Before turning to online communication, however, let us first consider the role of contextual information in utterance interpretation more generally. An agent's utterance of a sentence on a particular occasion can be interpreted in indefinitely many ways. Bach (Reference Bach and Szabo2005, p. 16), for example, claims that it is platitudinous to say that what an agent means in uttering a sentence is underdetermined by the linguistic meaning of that sentence. Some authors have even suggested that it is more or less impossible for agents to be fully explicit when expressing themselves in language – leaving some room for interpretation is inevitable (Carston, Reference Carston2009; Bezuidenhout, Reference Bezuidenhout2002). The audience must thus rely on their perception of the context of utterance to interpret an assertion. This reliance is needed to resolve a range of interpretative issues that are left open by the surface form of the utterance itself – for example, to disambiguate expressions, to assign referents to proper names and indexicals, to recover the explicature of the assertion, to recover any implicatures intended by the agent, and to recognise which further inferences the agent intends her assertion to license. Interlocutors must also rely on contextual assumptions when choosing what to utter: they must select a signal that, in combination with available contextual information, will give their audience a good chance of recovering their intended message, or at least something close to it. Here is an example:

1. 1) There is milk in the fridge.

When an agent asserts (1), there is an enormous number of more or less similar contents that she might be trying to communicate.Footnote ⁵ It is not simply that her audience must work out which fridge is being referred to. In one context, the agent might be trying to communicate that there is enough fresh milk in the fridge in the kitchen in which the utterance is produced to make one medium sized latte. But, in another context, she might be trying to communicate that there is still spilled milk on the fridge shelf that has yet to be cleaned. Interlocutors do not usually specify with such precision what they intend to communicate in the surface form of the utterance. Rather, they rely on their audience to use their knowledge of the context of utterance to fill out these details in their interpretation.

Although it may be hidden by its banality, a quite astounding amount of shared contextual information is needed for communication to succeed in the simple example just given.Footnote ⁶ Interpretation of any utterance requires a general understanding of relevant conversational norms and some kind of commonsense person theory (Fricker, Reference Fricker, Matilal and Chakrabarti1994), which agents acquire and refine over a lifetime. But, on top of this, a great deal of domain-specific knowledge is involved. Communicating information about milk that could be used in a latte requires that interlocutors possess shared (or relevantly similar) beliefs about the ways milk can be used, about types of coffee-based beverage, about how much a human typically drinks in one sitting, about why certain items are refrigerated, and also about the interlocutors’ particular habits and preferences (especially those relating to coffee-making). Consider, for example, that in a social milieu in which it was unheard of to use milk in coffee, an utterance of (1), in a coffee-making context, could seem like a non-sequitur, and it would be difficult to work out an agent's intended message and its implications without asking her what she meant.

Despite the sheer volume of information required for successful interpretation, it is often fairly easy for an audience to work out roughly what their interlocutor intended to communicate in these everyday examples. Even in such familiar contexts, however, things can go awry. Perhaps the agent didn't realise that her audience was seeking plant milk, or perhaps she didn't realise that she was making coffee for 6 people, or that she has different standards for when milk can be considered fresh. Even when the interlocutors are quite aware of one another's differing standards, this is no guarantee that utterance interpretation will run smoothly. You know that your housemate is aware of your standards for milk-freshness – you have argued about this many times – but is she accommodating you by adopting your standards, or is she protesting by using her own? This is to say, it is not always clear what information is, or ought to be, considered relevant to interpretation. When communicating in-person, about everyday issues, we can often discover and correct misunderstandings as they become apparent – ‘Sorry, I forgot you were vegan!’, or ‘I meant fresh by my standards – yours are unreasonably strict!’.Footnote ⁷ Many of the cases of online communication that social epistemologists are interested in, in contrast, are not like this simple example in a number of crucial respects: online environments more often involve communication between interlocutors with mismatched contextual assumptions, and these differences can be perpetuated by reduced opportunities to provide missing contextual information or to repair defective exchanges. In the following subsections, I describe these obstacles in more detail.

4. Online Communication and Epistemic Bubbles

An epistemic bubble, recall, is a social epistemic structure in which relevant information is simply missing. Nguyen suggested that shattering a bubble can be relatively easy: one simply adds the missing information or source and thereby improves coverage reliability. He writes,

However, I think that merely being exposed to information is often insufficient to enable one to escape an epistemic bubble in any meaningful sense. The problem here is not the mistrust or discrediting of sources that is characteristic of echo chambers. Rather, the problem is that an epistemic bubble shapes the knowledge that is possessed by the agent within it and thus constrains her interpretative resources. When attempting to interpret a new utterance, the agent can appeal to no more than the existing knowledge that she has at her disposal, and the information given in the communicative exchange itself. In what follows I will argue that, as a result, even when a new source of information is added to an epistemic bubble, this is no guarantee that the information they provide can be integrated into the epistemic perspective of the audience who is exposed to it – this information often remains inaccessible to her.

Epistemic bubbles, as we have seen, tend to be populated by people with whom we have much in common. Indeed, it is this feature of them that is thought to be epistemically problematic: epistemic bubbles connect us predominantly with those who share our perspective on the world; they thus tend to reinforce this perspective, rather than challenging or expanding it. Because of this, agents within our bubble tend to be similar to us with respect to their speech and interpretative dispositions – for these dispositions are grounded in our epistemic perspectives. What this means is that it is relatively easy to communicate with others within an epistemic bubble because we tend (or are more likely) to share contextual assumptions with these people: we have enough common ground for communication to run smoothly – at least with respect to certain domains. This relationship is often asymmetric in online communication. That is, your familiarity with the epistemic perspective of someone you follow on Twitter might enable you to interpret her utterances very accurately – the two of you share beliefs about how she ought to be interpreted; but this interpretative skill may not be mirrored back at you, especially if this person does not follow you back or take an interest in what you have to say. Bubble-membership itself is plausibly often asymmetric in this way.

Due to the relationship between epistemic bubbles and interpretative resources, then, an agent will typically be relatively good at interpreting utterances from sources within her bubble. Things are quite different, however, when the agent reaches outside of a bubble. When she does so, she will find herself in unfamiliar contextual territory: that is, she will be in contextual discordance with her interlocutor. In these cases, the agent lacks the background knowledge required to accurately interpret what her interlocutor is trying to communicate – either at the level of literal meaning, explicature, implicature, speech act, inference, etc. When this happens, although the agent is ‘exposed’ to relevant missing information – she observes the interlocutor's utterance – this information is nonetheless still inaccessible to her in some sense (or to some degree). She may recover the wrong content, derive unintended implicatures, or draw incorrect conclusions due to misunderstanding. As a result, she may employ the content she recovers in reasoning in ways that are counterproductive or contrary to the intentions of its source. Importantly, agents who make this kind of mistake are not being irrational. Rather, they may be employing their new beliefs in reasoning as best they can, given the epistemic position they are working from. The problem is that communication is simply very hard in the absence of shared or concordant contextual assumptions and, by the very nature of epistemic bubbles, reaching outside of them requires communicating in the absence of this common ground to a greater or lesser degree.

There are two lessons I would like to draw from this. The first is that contextual discordance presents a special challenge to escaping epistemic bubbles. I return to this issue in Section 5. The second lesson to draw, more briefly, concerns the role of epistemic bubbles in explanations of the so-called ‘post-truth’ phenomenon. Nguyen (Reference Thi Nguyen2020) claims that epistemic bubbles are not especially useful in explanations of why agents reject claims for which there is overwhelming evidence. He writes,

I agree with Nguyen, of course, that epistemic bubbles cannot wholly explain this phenomenon on their own. However, I do think that they may have a somewhat greater role to play than he allows for here. That is, even a good faith attempt to interpret new evidence can fail if one's interpretative resources lead one to misunderstand the content of this evidence, or what its implications are, etc. Linguistic barriers to escaping echo chambers are briefly discussed by Nguyen. Following Jamieson and Cappella (Reference Jamieson and Cappella2008), he describes how those who maintain echo chambers use their own private language, in which familiar terms are given alternative meanings and new jargon is introduced in order to strengthen the in-group's identity (Nguyen, Reference Thi Nguyen2020, p. 146). My point is that, even in a rather benign situation, in which the agent is not in the grip of any conspiracy theories, or subject to manipulation, she can still fail to properly integrate the information that is presented to her if the interpretative resources supplied by her epistemic bubble are insufficient.

5. Escaping Epistemic Bubbles?

The argument in the preceding has been that, whilst it may be relatively easy to expose oneself to missing sources of information, and thus achieve a kind of coverage reliability, it is much harder to properly digest this information in ways that allow it to play a meaningful role in our epistemic lives. What does this mean for our prospects for escaping an epistemic bubble? One obvious direction for the resolution of this problem is to implement strategies for increasing common ground between interlocutors. Record and Miller (Reference Record and Miller2022, p. 14ff.) suggest some solutions to the problem of epistemically toxic content, which employ this kind of strategy. They suggest, for example, encouraging the introduction of stable norms that govern responsibility for the content of social media posts, and for the interpretation of ambiguous elements of online interfaces (such as emojis). They also identify a range of ways to add more context to posts. For example, they suggest that platforms could employ algorithms that position related posts next to each other in a newsfeed, such that contextual information is collated rather than fragmented; they also consider that platforms can make it easier for (or even require) users to add context to their own posts and reposts. Frost-Arnold (Reference Frost-Arnold and Lackey2021, pp. 445–6) also considers proposals for redesigning social media platforms (from Hull et al., Reference Hull, Lipford and Latulipe2011; and McMillan Cottom, Reference Cottom2016), which may aid in counteracting context collapse. However, she is sceptical that such technological solutions would be sufficient, suggesting also that individual users need to change their online practices to develop habits of trustworthiness and discretion (Frost-Arnold, Reference Frost-Arnold and Lackey2021, p. 450).

Both Record and Miller, and Frost-Arnold, are addressing somewhat different challenges to the one that I focus on here. Nonetheless, as these challenges all broadly concern contextual discordance, it is natural to wonder whether strategies like these could be employed to improve our prospects for shattering epistemic bubbles. However, while I do think that it is useful to strategize ways to improve communication in online environments (in cases where this improvement would be all-things-considered preferable), I think it is unhelpful to think of epistemic bubbles as structures that can be shattered or burst, even when additional contextual information is added. This way of thinking about epistemic bubbles simply reproduces a naïve model of communication as floating largely free of contextual considerations. To see this, first consider the initial picture of epistemic bubbles with which we began: on this picture, an epistemic bubble is a structure that can easily be shattered if only the agent within it is exposed to information from sources that had previously been omitted. I argued that it is inappropriate to describe the agent's bubble as ‘shattered’ in such circumstances because agents communicating across the boundaries of a bubble will lack the interpretative resources required to properly understand an utterance from the new source; and, because of this, they will fail to integrate the new information into their epistemic perspective.Footnote ¹⁴ For these same reasons, however, I don't think it is helpful to think of an epistemic bubble as something that can be burst, if only we offer a bit more contextual information to the agent to support integration of the original content – this picture, too, fails to properly acknowledge the role of contextual information in communication. The main issue is that, especially in online environments, agents are often communicating in circumstances in which contextual discordance is very pronounced. As such, the amount of contextual information that a platform would need to provide to render the context non-defective is extremely high, and the further an agent reaches outside of her bubble, the greater this problem is likely to be. A related consideration is that utterance understanding is something that comes in degrees. In practice, there is no limit to how well, or how much better, we could understand an assertion from another interlocutor. There is always more contextual information that could be given to an agent to enrich her understanding in ways that bring to light new aspects of her interlocutor's perspective on the world. Moreover, there is very often a deeper or subtler understanding of a proposition possible than that which the agent arrives at: a deep understanding of a proposition from a domain of technical or practical expertise can be a lifetime of work for an individual. Most all agents develop an incredibly rich understanding of propositions in particular domains, of course. But this deep understanding is not the kind of thing that an agent could hope to achieve with respect to all, or even many, of the domains of information that are important or relevant to her life. There is simply too much information in the world, and not enough time to truly comprehend all of it.

With the preceding in mind, I want to propose an alternative model of epistemic bubbles than the one presented by Nguyen. Nguyen's account sees an epistemic bubble as comprising a network of sources, and the information they share, which an agent is connected to via the observation of utterances. On this approach, information can exist within your bubble regardless of how well you understand it; thus, bubbles are relatively easy to burst. Whilst it may be useful to include this network in a model of an agent's broader epistemic environment, I think that an account of epistemic bubbles should reflect the limitations that our interpretative resources place on our access to, and comprehension of, the information we consume. In order to demarcate what information is available within a bubble, I propose appealing to the notion of common ground. On this second approach, although the members of your epistemic bubble may be just those with whom you are connected via utterances, the information available is limited to that which is expressed with utterances that you are able to correctly interpret.Footnote ¹⁵ The idea is that, as two agents may share common ground with respect to one domain, but not another, the information within your bubble is not just any information shared by the members of your network, but only the information shared via utterances that your common ground with these members enables you to understand. Given the nature of utterance understanding, noted above, this is plausibly a matter of degree: information exists within your bubble to the degree that you are able to correctly interpret the utterances used to express it.

If we adopt this alternative model of epistemic bubbles, the result is that attempting to escape one's bubble is not merely a matter of adding missing sources, exposing oneself to new information, and thereby improving coverage reliability. For example, the fact that you follow climate scientists on Twitter does not guarantee that the information they share regarding their research is available within your epistemic bubble. If you lack the interpretative resources to understand their utterances, then following these agents on social media, and even reading their posts regarding climate science, is just one small step in the direction of genuinely integrating the information they share into your own epistemic perspective. This point, of course, does not merely apply to science communication on social media. Similarly, adding activists or political pundits to your social networks does not automatically entitle you to consider all of the information they share as falling within your bubble – the information available to you will depend on which utterances your common ground enables you to interpret, and this will vary across different domains of discourse. To capture new information within your bubble, depending on your starting point, may require significant work, building common ground that can provide the scaffolding for improved utterance interpretation. And this is plausibly work that often involves gradual progress over time. In contrast to the ‘fragile’ conception of epistemic bubbles that authors like Nguyen have been working with, then, I suggest we instead adopt an ‘elastic’ conception: that is, epistemic bubbles cannot be shattered, but are instead slowly and incrementally expanded to improve our (inevitably partial) perspective on the world, and our ability to understand others within it. This is not a project that we could hope to complete simply by improving the composition of our social networks, or adding a bit more context to social media posts (although these things surely help); rather, it is a potentially unbounded project that, if we work very hard, we can make modest progress towards within a lifetime.

6. Conclusion

In this paper, I have argued for a particular view of the relationship between epistemic bubbles, on the one hand, and interpretative resources, on the other: epistemic bubbles mark the boundaries of our knowledge of the world and, as such, we can appeal to no more than is available within a bubble in our attempts to understand utterances concerning domains beyond it. For this reason, attempts to ‘shatter’ an epistemic bubble by adding missing sources of information will often be ineffective in practice: communicating across the boundaries of a bubble is communication in the absence of common ground and, without this common ground, the likelihood of misunderstanding is very high. This problem will be especially pronounced in online networks, where contextual discordance between interlocutors is rife, and where there are fewer opportunities to repair defective exchanges. It may be possible to improve online communication by providing more contextual information to aid in the interpretation of utterances from unfamiliar domains. However, I have suggested that it is unhelpful to think of epistemic bubbles as structures that we can, in practice, burst or escape simply by adding more information or sources thereof. Rather, adding contextual scaffolding to online contexts will help us to, gradually and incrementally, enhance our epistemic perspective on the world, and our ability to understand others, but this perspective will always be partial. Thought of this way, the problem with the structure of our online networks is not that they keep us trapped within our epistemic bubbles – for that is inevitable – but that they keep us from expanding our epistemic horizons.