"Why should we care about having true beliefs? And why do demonstrably false beliefs persist and spread despite consequences for the people who hold them? Philosophers of science Cailin O’Connor and James Weatherall argue that social factors, rather than individual psychology, are what’s essential to understanding the spread and persistence of false belief. It might seem that there’s an obvious reason that true beliefs matter: false beliefs will hurt you. But if that’s right, then why is it irrelevant to many (...) people whether they believe true things or not? In an age riven by "fake news," "alternative facts," and disputes over the validity of everything from climate change to the size of inauguration crowds, the authors argue that social factors, not individual psychology, are what’s essential to understanding the persistence of false belief and that we must know how those social forces work in order to fight misinformation effectively."–Publisher’s description. (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.

Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents’ beliefs about which of two possible actions yields the better result. We find a range of possible outcomes, including stable polarization in belief and action. (...) The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community’s ability to reach accurate consensus about the world. (shrink)

Public discussions of political and social issues are often characterized by deep and persistent polarization. In social psychology, it’s standard to treat belief polarization as the product of epistemic irrationality. In contrast, we argue that the persistent disagreement that grounds political and social polarization can be produced by epistemically rational agents, when those agents have limited cognitive resources. Using an agent-based model of group deliberation, we show that groups of deliberating agents using coherence-based strategies for managing their limited resources tend (...) to polarize into different subgroups. We argue that using that strategy is epistemically rational for limited agents. So even though group polarization looks like it must be the product of human irrationality, polarization can be the result of fully rational deliberation with natural human limitations. (shrink)

Recent philosophy has paid considerable attention to the way our biases are liable to encroach upon our cognitive lives, diminishing our capacity to know and unjustly denigrating the knowledge of others. The extent of the bias, and the range of domains to which it applies, has struck some as so great as to license talk of a new form of skepticism. I argue that these depressing consequences are real and, in some ways, even more intractable than has previously been recognized. (...) For the difficulties we face in this domain are fueled not only by implicit biases but by various other sorts of entrenched cognitive attitudes we bear toward others, whether or not we judge them to be our peers. Inasmuch as the epistemic standing of this broader set of attitudes is itself quite dubious, the problem of epistemic injustice turns out to be just one special case—albeit of a particularly nasty kind—from a broader domain of cases where the collaborative character of knowledge clashes with tendencies that make collaboration difficult. This makes the threat of skepticism all the greater, and at the same time makes it harder to see what path of escape there might be. (shrink)

The purpose of this paper is to explore the connection between expressivism and disagreement. More in particular, the aim is to defend that one of the desiderata that can be derived from the study of disagreement, the explanation of ‘crossed disagreements’, can only be accommodated within a semantic theory that respects, at the meta-semantic level, certain expressivistic restrictions. We will compare contemporary dynamic expressivism with three different varieties of contextualist strategies to accommodate the specificities of evaluative language –indexical contextualism – (...) truth-conditional pragmatics –, pragmatic strategies using implicatures, and presuppositional accounts. Our conclusion will be that certain assumptions of expressivism are necessary in order to provide a semantic account of evaluative uses of language that can allow us to detect and prevent crossed disagreements. (shrink)

Contemporary societies are often “polarized”, in the sense that sub-groups within these societies hold stably opposing beliefs, even when there is a fact of the matter. Extant models of polarization do not capture the idea that some beliefs are true and others false. Here we present a model, based on the network epistemology framework of Bala and Goyal, 784–811 1998), in which polarization emerges even though agents gather evidence about their beliefs, and true belief yields a pay-off advantage. As we (...) discuss, these results are especially relevant to polarization in scientific communities, for these reasons. The key mechanism that generates polarization involves treating evidence generated by other agents as uncertain when their beliefs are relatively different from one’s own. (shrink)

Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents’ beliefs about which of two (or more) possible actions yields the better result. We find a range of possible outcomes, including stable polarization in belief (...) and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community’s ability to reach accurate consensus about the world. (shrink)

According to some, the current political fracture is best described as political polarization – where extremism and political separation infest an entire whole population. Political polarization accounts often point to the psychological phenomenon of belief polarization – where being in a like-minded groups tends to boost confidence. The political polarization story is an essentially symmetrical one, where both sides are subject to the same basic dividing forces and cognitive biases, and are approximately as blame-worthy. On a very different account, what's (...) going on is best described propaganda – where a discrete set of bad actors have manipulated some part of the media environ-ment. The propaganda story is usually told as a highly asymmetrical story, where only some media consumers are under the spell of the propagandists. Which is right? I consider two analyses of the 2016 American election: Robert Talisse's polarization-style account in Overdoing Democracy, and Benkler et. al.'s propaganda-style account in Network Propaganda. I suggest that the propaganda account has better empirical support. I also offer a diagnosis of the appeal of the polarization story. Those who accept a polarization account are often political centrists, who accuse those at the political extremes of motivated reasoning – of believing what they find comfortable. Such centrists also tend to treat political extremism as the product of the irrational belief polarization, arising from living in like-minded groups. But, I argue, these arguments are too quick. First, we can’t dismiss a group as irrational merely be-cause they are likeminded. The existence of like-minded group can be explained in terms of irrational belief polarization, but it can also be explained by rational convergence on the truth. Second, belief polarization is not always irrational, such as when its emotional effects are used to repair impaired self-confidence. Third, political centrists are also subject to similar debunking argument. When we accept a polarization account, we get to feel the comfort of being “above it all”. Political centrists are just as plausibly subject to the irrational effects of living in like-minded groups. Belief polarization isn’t just for extremists. (shrink)

The US populace appears to be increasingly polarized on partisan lines. Political fissures bifurcate the country even on empirical matters like vaccine safety and anthropogenic climate change. There now exists an ever-expanding interdisciplinary research program in which theorists attempt to explain increases in political polarization and myriad other phenomena collected under the “post-truth” heading by appeal to social-epistemic structures, like echo chambers and epistemic bubbles, that affect the flow and uptake of information in various communities. In this paper, I critically (...) analyze C. Thi Nguyen’s important and popular analysis of echo chambers and epistemic bubbles. As I demonstrate, the explanatory mechanisms on which Nguyen focuses are, arguably, overly cognitive and obscure significant effects of social-epistemic structures on our affective lives. The broader lesson to draw from my discussion is the following: commonly used expressions intended to refer to social-epistemic problems, like “political polarization”, possess no univocal definition across theorists, and various ways of making the terms precise are differentially successful in characterizing verifiable phenomena. Theorizing about social-epistemic structures should be responsive to relevant empirical work on various phenomena that we have good reason to believe constitute real and substantive problems that result from the flow and uptake of information. (shrink)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

Is it possible to disagree with someone without considering them cognitively flawed? The answer seems to be a resounding yes: disagreeing with someone doesn't entail thinking less of them. You can disagree with someone and not think that they are unreasonable. Deep disagreements, however, may challenge this assumption. A disagreement is deep when it involves many interrelated issues, including the proper way to resolve the disagreement, resulting in its persistence. The parties to a deep disagreement can hold neutral or even (...) positive judgements of each other's epistemic character, as parties’ judging each other's epistemic character negatively (i.e., epistemic disdain) is not a defining feature of deep disagreements. When analysing real-life cases, however, we find that epistemic disdain is typical of deep disagreements. In this article, I analyse why this is the case. Given that epistemic disdain undermines cognitive peerhood, the prospects of deep disagreements between epistemic peers seem bleak. Finally, it is discussed how the phenomenon of epistemic disdain, as it relates to deep disagreements, may increase affective polarisation. (shrink)

This model explores consensus among agents in a population in terms of two properties. The first is a probability of belief change. This value indicates how likely agents are to change their mind in interactions. The other is the size of the agents audience: the proportion of the population the agent has access to at any given time. In all instances, the agents converge on a single belief, although the agents are arational. I argue that this generates a skeptical hypothesis: (...) any instance of purportedly rational consensus might just as well be a case of arational belief convergence. I also consider what the model tells us about increasing the likelihood that one agent’s belief is adopted by the rest. Agents are most likely to have their beliefs adopted by the entire population when their value for PBC is low relative to the rest of the population and their audience sizes are roughly three-quarters of the largest possible audience. I further explore the consequences of dogmatists to the population; individuals who refuse to change their mind end up polarizing the population. I conclude with reflections on the supposedly special character of rationality in belief-spread. (shrink)

We often need to have beliefs about things on which we are not experts. Luckily, we often have access to expert judgements on such topics. But how should we form our beliefs on the basis of expert opinion when experts conflict in their judgments? This is the core of the novice/2-expert problem in social epistemology. A closely related question is important in the context of policy making: how should a policy maker use expert judgments when making policy in domains in (...) which she is not herself an expert? This question is more complex, given the messy and strategic nature of politics. In this paper we argue that the prediction with expert advice framework from machine learning provides helpful tools for addressing these problems. We outline conditions under which we should expert PWEA to be helpful and those under which we should not expect these methods to perform well. (shrink)

Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of ‘methodological iteration’ whereby the models initiate new lines (...) of inquiry, isolate and clarify problems with existing knowledge claims, and stimulate further research. (shrink)

In recent epistemology, belief polarization is generally defined as a process by which a disagreement on a single proposition becomes more extreme over time. Outside of the philosophical literature, however, ‘polarization’ is often used for a different epistemic phenomenon, namely the process by which people’s beliefs on unrelated topics become increasingly correlated over time. This paper argues that the latter type of polarization, here labeled interthematic polarization, is often rational from each individual’s point of view. This suggests that belief polarization (...) is not necessarily a failure of individual rationality, but instead a failure of the social structures within which we live our epistemic lives. (shrink)

A perennial problem in social epistemology is the problem of expert testimony, specifically expert testimony regarding scientific issues: for example, while it is important for me to know information pertaining to anthropogenic climate change, vaccine safety, Covid-19, etc., I may lack the scientific background required to determine whether the information I come across is, in fact, true. Without being able to evaluate the science itself, then, I need to find trustworthy expert testifiers to listen to. A major project in social (...) epistemology has thus become determining what the markers of trustworthiness are that laypersons can appeal to in order to identify and acquire information from expert testifiers. At the same time, the ways in which we acquire scientific information has changed significantly, with much of it nowadays being acquired in online environments. While much has been said about the potential pitfalls of seeking information online, little has been said about how the nature of seeking information online should make us think about the problem of expert testimony. Indeed, it seems to be an underlying assumption that good markers of trustworthiness apply equally well when seeking information from expert testifiers in online and offline environments alike, and that the new challenges and opportunities presented by online environments merely affects the methods by which we can acquire evidence of said trustworthiness. Here I argue that in making this assumption one risks failing to account for how unique features of the ways in which we acquire information online affect how we evaluate the trustworthiness of experts. Specifically, I argue for two main claims: first, that the nature of information-seeking online is such that the extent to which information is susceptible to manipulation is a dominant marker of trustworthiness; second, as a result, one will be more likely to seek out a particular kind of expert testifier in online environments, what I call a cooperative as opposed to preemptive expert. The result is that criteria for expert trustworthiness may look significantly different when acquiring information online as opposed to offline. (shrink)

There have been many discussions recently from philosophers, cognitive scientists, and psychologists about group polarization, with online and social media environments in particular receiving a lot of attention, both because of people's increasing reliance on such environments for receiving and exchanging information and because such environments often allow individuals to selectively interact with those who are like-minded. My goal here is to argue that the group epistemologist can facilitate understanding the kinds of factors that drive group polarization in a way (...) that has been overlooked by the existing research. Specifically, I argue that polarization can occur in part because of the ways that members of a group treat the group itself (as opposed to an individual member within that group) as a source of information, and in doing so makes their own position, as well as that of the group, more extreme. I refer to this as a structural factor in driving polarization, and argue that such factors can contribute to explanations of polarization that occurs specifically in an important subset of groups, namely online and social media groups in which little is known about other members within the group, what I refer to as anonymous, semi-anonymous and pseudonymous (ASAP) groups. (shrink)

Some common explanations of issue polarization and echo chambers rely on social or cognitive mechanisms of exclusion. Accordingly, suggested interventions like “be more open-minded” target these mechanisms: avoid epistemic bubbles and don’t discount contrary information. Contrary to such explanations, we show how a much weaker mechanism—the preference for belief—can produce issue polarization in epistemic communities with little to no mechanisms of exclusion. We present a network model that demonstrates how a dynamic interaction between the preference for belief and common structures (...) of epistemic communities can turn very small unequal distributions of initial beliefs into full-blown polarization. This points to a different class of explanations, one that emphasizes the importance of the initial spread of information. We also show how our model complements extant explanations by including a version of biased assimilation and motivated reasoning—cognitive mechanisms of exclusion. We find that mechanisms of exclusion can exacerbate issue polarization, but may not be the ultimate root of it. Hence, the recommended interventions suggested by extant literature is expected to be limited and the problem of issue polarization to be even more intractable. (shrink)

When public opinion gets polarized, the population’s beliefs can experience two different changes: they can become more extreme in their contents or they can be held with greater confidence. These two possibilities point to two different understandings of the rupture that characterizes political polarization: extremism and radicalism. In this article, I show that from the close examination of the best available evidence regarding how we get polarized, it follows that the pernicious type of political polarization has more to do with (...) radicalism than with extremism. Reinforcing the confidence in the core beliefs of the group we identify with makes our beliefs immune to the reasons coming from the other political side. Finally, I also suggest that the rise of political polarization is not necessarily the result of an irrational process. (shrink)

Theories of rational decision making often abstract away from computational and other resource limitations faced by real agents. An alternative approach known as resource rationality puts such matters front and center, grounding choice and decision in the rational use of finite resources. Anticipated by earlier work in economics and in computer science, this approach has recently seen rapid development and application in the cognitive sciences. Here, the theory of rationality plays a dual role, both as a framework for normative assessment (...) and as a source of scientific hypotheses about how mental processes in fact work. The latter project, often called rational analysis, depends for its success on a fine-grained characterization of the computational problem facing a decision maker, which may in turn depend on realistic assumptions about what the relevant agent is like. As a consequence, resource rationality involves a delicate, but often fruitful interplay between the normative and the descriptive. (shrink)

In this talk I present the main results from Anta (2021), namely, that the theoretical division between Boltzmannian and Gibbsian statistical mechanics should be understood as a separation in the epistemic capabilities of this physical discipline. In particular, while from the Boltzmannian framework one can generate powerful explanations of thermal processes by appealing to their microdynamics, from the Gibbsian framework one can predict observable values in a computationally effective way. Finally, I argue that this statistical mechanical schism contradicts the Hempelian (...) (1958) thesis that the predictive power of a scientific theory is directly proportional to its explanatory potential, and vice versa. (shrink)

The way digital information technologies work and, more specifically, the possibilities for action that technological devices offer to us affect our processes of political belief formation. In particular, there seems to be a close connection between our digital affordances and the increase of the sort of polarization that threatens the proper functioning of democracy. In this paper, we analyze whether the type of polarization linked to the use of digital technologies, and which endangers the health of public deliberation, has to (...) do with the adoption of beliefs whose contents are increasingly extreme—extremism—or, on the contrary, has more to do with increasing our credence in the core beliefs of our political identity—radicalism. (shrink)

This article aims to describe the last 10 years of the collaborative scientific endeavors on polarization in particular and collective problem-solving in general by our multidisciplinary research team. We describe the team’s disciplinary composition—social psychology, political science, social philosophy/epistemology, and complex systems science— highlighting the shared and unique skill sets of our group members and how each discipline contributes to studying polarization and collective problem-solving. With an eye to the literature on team dynamics, we describe team logistics and processes that (...) we believe make our multidisciplinary team persistent and productive. We emphasize challenges and difficulties caused by disciplinary differences in terms of terminology, units/levels of analysis, methodology, and theoretical assumptions. We then explain how work disambiguating the concepts of polarization and developing an integrative theoretical and methodological framework with complex systems perspectives has helped us overcome these challenges. We summarize the major findings that our research has produced over the past decade, and describe our current research and future directions. Last, we discuss lessons we have learned, including difficulties in a “three models” project and how we addressed them, with suggestions for effective multidisciplinary team research. (shrink)