What are the proper epistemic aims of social media sites? A great deal of social media critique presupposes an exceptionalist attitude, according to which social media is either uniquely good, or uniquely bad for our collective knowledge-generating practices. Exceptionalism about social media is troublesome, both because it leads to oversimplistic narratives, and because it prevents us making relevant comparisons to other epistemic systems. The goal of this chapter is to offer an anti-exceptionalist account of the epistemic aims of social media. (...) I will argue that social systems (and epistemic institutions in general) ought to pursue three distinct epistemic goals: promoting good epistemic outcomes for users, realising epistemically good institutional features, and achieving structural epistemic justice. Although these goals are often mutually supportive, I will consider a number of cases in which these values conflict. This means that there are epistemic dilemmas about how to design social media platforms (and other kinds of epistemic system) which can only be resolved by appealing to ethical considerations. This discussion highlights that just as in the political realm, there is no such thing as a neutral epistemic system. (shrink)

Posts on social media platforms like Twitter are sometimes the products of deceptively designed bots. These bots can cause obvious epistemic problems, such as tricking human users into believing the contents of misleading posts. However, less-considered epistemic problems involve false bot judgements where a human user mistakes another human user’s post for a bot-post, or where a human user mistakenly believes that bots are the primary vehicles for tokening certain content on social media. This paper takes up three questions concerning (...) false bot judgements: what exactly are their associated epistemic harms, just how harmful are they, and what should we do about them? (shrink)

The paper argues that (i) the notion of epistemic reliability, as it is standardly defined within mainstream epistemology, is a multidimensional concept, and that (ii) paying attention to reliability’s multidimensional nature can significantly expand reliabilism’s purview both in the theoretical and practical domain. Reliabilist theories of knowledge and justification agree that a process is reliable just in case it leads to a ‘sufficiently high preponderance of true over false beliefs.’ Given this straightforward definition, reliability appears to be, and so far (...) has been implicitly treated by epistemologists as, a mono-dimensional concept. Nevertheless, the terminology and formulas that statisticians and computers scientists have developed for assessing the reliability of binary classification processes reveal that for any belief-forming process whose aim is to identify the presence or the absence of some quality ι, there are at least four different interpretations of the above definition. These interpretations correspond to four separate dimensions of reliability: Precision, Negative Predictive Value (NPV), Recall and Specificity. Though epistemologists do not explicitly specify how they interpret the above definition of reliability, due to their main interest in ‘know-that’, their mono-dimensional focus seems to have so far been mainly directed at Precision alone (or, at best, to both Precision and NPV—but without distinguishing between the two). As it transpires, however, the (entirely) neglected dimensions of Recall and Specificity can guide the satisfaction of another important epistemic goal, best captured by the locution ‘know-most/all.’ The upshot is that different epistemic goals call for high levels of reliability along different dimensions (and, often, their combinations too). This observation invites upgrading reliabilism into dimensional reliabilism, according to which assessing whether a process is knowledge-conducive depends on whether it manifests high reliability along the appropriate dimension(s), given the epistemic goal at hand. (shrink)

The internet has considerably changed epistemic practices in science as well as in everyday life. Apparently, this technology allows more and more people to get access to a huge amount of information. Some people even claim that the internet leads to a democratization of knowledge. In the following text, we will analyze this statement. In particular, we will focus on a potential change in epistemic structure. Does the internet change our common epistemic practice to rely on expert opinions? Does it (...) alter or even undermine the division of epistemic labor? The epistemological framework of our investigation is a naturalist-pragmatist approach to knowledge. We take it that the internet generates a new environment to which people seeking information must adapt. How can they, and how should they, expand their repertory of social markers to continue the venture of filtering, and so make use of the possibilities the internet apparently provides? To find answers to these questions we will take a closer look at two case studies. The first example is about the internet platform WikiLeaks that allows so-called whistle-blowers to anonymously distribute their information. The second case study is about the search engine Google and the problem of personalized searches. Both instances confront a knowledge-seeking individual with particular difficulties which are based on the apparent anonymity of the information distributor. Are there ways for the individual to cope with this problem and to make use of her social markers in this context nonetheless? (shrink)

Various social epistemologists employ what seem to be rather distinct notions of group rationality. In this essay, I offer an account of group rationality that is able to unify the dominant notions present in the literature under a single framework. I argue that if we employ a teleological account of epistemic rationality, and then allow that there are many different epistemic goals that are worth pursuing for various groups and individuals, we can then see how those seemingly divergent understandings of (...) group rationality are all intimately related. I close by showing how the view has the additional benefit of allowing us to generate practical, normative suggestions for groups in the real world. (shrink)

Ignorance of one’s privileges and prejudices is an epistemic problem. While the sources of ignorance of privilege and prejudice are increasingly understood, less clarity exists about how to remedy ignorance. In fact, the various causes of ignorance can seem so powerful, various, and mutually reinforcing that studying the epistemology of ignorance can inspire pessimism about combatting socially constructed ignorance. I argue that this pessimism is unwarranted. The testimony of members of oppressed groups can often help members of privileged groups overcome (...) their ignorance. This paper argues that a particular type of speaker’s trust—hopeful trust—can motivate hearers to become cognizant of their privilege and prejudice. I argue that hopeful trust is a powerful way of eliciting trust-responsiveness that can be an effective mechanism for challenging privilege and prejudice. To make this case, I draw on case studies of online attempts to challenge ignorance. While the problems of testimonial injustice, defensi... (shrink)

AbstractSimion and Kelp offer a prima facie very promising account of trustworthy AI. One benefit of the account is that it elegantly explains trustworthiness in the case of cancer diagnostic AIs, which involve the acquisition by the AI of a representational etiological function. In this brief note, I offer some reasons to think that their account cannot be extended — at least not straightforwardly — beyond such cases (i.e., to cases of AIs with non-representational etiological functions) without incurring the unwanted (...) cost of overpredicting untrustworthiness. (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)

Information providing and gathering increasingly involve technologies like search ‎engines, which actively shape their epistemic surroundings. Yet, a satisfying account ‎of the epistemic responsibilities associated with them does not exist. We analyze ‎automatically generated search suggestions from the perspective of social ‎epistemology to illustrate how epistemic responsibilities associated with a ‎technology can be derived and assigned. Drawing on our previously developed ‎theoretical framework that connects responsible epistemic behavior to ‎practicability, we address two questions: first, given the different technological ‎possibilities available (...) to searchers, the search technology, and search providers, ‎who should bear which responsibilities? Second, given the technology’s ‎epistemically relevant features and potential harms, how should search terms be ‎autocompleted? Our analysis reveals that epistemic responsibility lies mostly with ‎search providers, which should eliminate three categories of autosuggestions: those ‎that result from organized attacks, those that perpetuate damaging stereotypes, and ‎those that associate negative characteristics with specific individuals.‎. (shrink)