Under conditions of high social and political polarization, expressing political anger online toward systemic injustice faces an apparent trilemma: Express none but lose anger's valuable goods; express anger to heterogeneous audiences but risk aggravating inter-group polarization; or express anger to like-minded people but succumb to the epistemic pitfalls and extremist tendencies inherent to homogeneous groups. Solving the trilemma requires cultivating an online environment as a deliberative system composed of four kinds of groups—each with distinct purposes and norms. I argue that (...) applying empirically-guided design principles to this systems framework provides political anger a place where its powers can serve justice without damaging the epistemic, ethical, emotional, and community resources required for a democratic path to correcting systemic injustice. (shrink)

Predictable polarization is everywhere: we can often predict how people’s opinions, including our own, will shift over time. Extant theories either neglect the fact that we can predict our own polarization, or explain it through irrational mechanisms. They needn’t. Empirical studies suggest that polarization is predictable when evidence is ambiguous, that is, when the rational response is not obvious. I show how Bayesians should model such ambiguity and then prove that—assuming rational updates are those which obey the value of evidence—ambiguity (...) is necessary and sufficient for the rationality of predictable polarization. The main theoretical result is that there can be a series of such updates, each of which is individually expected to make you more accurate, but which together will predictably polarize you. Polarization results from asymmetric increases in accuracy. This mechanism is not only theoretically possible, but empirically plausible. I argue that cognitive search—searching a cognitively accessible space for a particular item—often yields asymmetrically ambiguous evidence, I present an experiment supporting its polarizing effects, and I use simulations to show how it can explain two of the core causes of polarization: confirmation bias and the group polarization effect. (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)

Belief polarization is widely seen to threaten havoc on our shared political lives. It is often assumed that BP is the product of epistemically irrational behaviors at the individual level. After distinguishing between BP as it occurs in intra-group and inter-group settings, this paper argues that neither process necessarily reflects individual epistemic irrationality. It is true that these processes can work in tandem to produce so-called “echo chambers.” But while echo chambers are often problematic from the point of view of (...) collective rationality, it doesn't follow that individuals are doing anything wrong, epistemically speaking, in seeking them out. In non-ideal socio-epistemic contexts, echo chamber construction might provide one's best defense against systematic misinformation and deception. (shrink)

Social media platforms have been rapidly increasing the number of informational labels they are appending to user-generated content in order to indicate the disputed nature of messages or to provide context. The rise of this practice constitutes an important new chapter in social media governance, as companies are often choosing this new “middle way” between a laissez-faire approach and more drastic remedies such as removing or downranking content. Yet information labeling as a practice has, thus far, been mostly tactical, reactive, (...) and without strategic underpinnings. In this paper, we argue against defining success as merely the curbing of misinformation spread. The key to thinking about labeling strategically is to consider it from an epistemic perspective and to take as a starting point the “social” dimension of online social networks. The strategy we articulate emphasizes how the moderation system needs to improve the epistemic position and relationships of platform users — i.e., their ability to make good judgements about the sources and quality of the information with which they interact on the platform — while also appropriately respecting sources, seekers, and subjects of information. A systematic and normatively grounded approach can improve content moderation efforts by providing clearer accounts of what the goals are, how success should be defined and measured, and where ethical considerations should be taken into consideration. We consider implications for the policies of social media companies, propose new potential metrics for success, and review research and innovation agendas in this regard. (shrink)