It is often claimed that social media accelerate political extremism by employing personalization algorithms that filter users into groups with homogenous beliefs. While an intuitive position, recent research has shown that social media users exhibit self-filtering tendencies. In this paper, I apply Hannah Arendt’s theory of political judgment to hypothesize a cause for self-filtering on social media. According to Arendt, a crucial step in political judgment is the imagination of a general standpoint of distinct yet equal perspectives, against which individuals (...) compare their own judgments in order to test their defensibility. I argue that social media inhibit this step by gamifying the pursuit of social status, which encourages users to consider the perspectives of others not for the sake of a general standpoint but for the sake of improving their social status, resulting in self-filtering. Consequently, ameliorating political extremism on social media requires not just reforming the algorithms that deliver content to users, but the interfaces on which users present their social identities. (shrink)

In this article, I argue that online echo chambers are in some cases and in some respects good. I do not attempt to refute arguments that they are harmful, but I argue that they are sometimes beneficial. In the first section, I argue that it is sometimes good to be insulated from views with which one disagrees. In the second section, I argue that the software-design principles that give rise to online echo chambers have a lot to recommend them. Further, (...) the opposing principle, serendipity, could give rise to serious harm, in light of the conclusion of the first section that sometimes we are better off being insulated from some content online. In the third section, I argue that polarization can be a useful tool for inculcating the appropriate attitudes in a person. (shrink)

New technologies are the source of uncertainties about the applicability of moral and morally connotated concepts. These uncertainties sometimes call for conceptual engineering, but it is not often recognized when this is the case. We take this to be a missed opportunity, as a recognition that different researchers are working on the same kind of project can help solve methodological questions that one is likely to encounter. In this paper, we present three case studies where philosophers of technology implicitly engage (...) in conceptual engineering (without naming it as such). We subsequently reflect on the case studies to find out how these illustrate conceptual engineering as an appropriate method to deal with pressing concerns in the philosophy of technology. We have two main goals. We first want to contribute to the literature on conceptual engineering by presenting concrete examples of conceptual engineering in the philosophy of technology. This is especially relevant, because the technologies that are designed based on the conceptual work done by philosophers of technology potentially have crucial moral and social implications. Secondly, we want to make explicit what choices are made when doing this conceptual work. Making explicit that some of the implicit assumptions are, in fact, debated in the literature allows for reflection on these questions. Ultimately, our hope is that conscious reflection leads to an improvement of the conceptual work done. (shrink)

We present a novel model of individual people, online posts, and media platforms to explain the online spread of epistemically toxic content such as fake news and suggest possible responses. We argue that a combination of technical features, such as the algorithmically curated feed structure, and social features, such as the absence of stable social-epistemic norms of posting and sharing in social media, is largely responsible for the unchecked spread of epistemically toxic content online. Sharing constitutes a distinctive communicative act, (...) governed by a dedicated norm and motivated to a large extent by social identity maintenance. But confusion about this norm and its lack of inherent epistemic checks lead readers to misunderstand posts, attribute excess or insufficient credibility to posts, and allow posters to evade epistemic accountability—all contributing to the spread of epistemically toxic content online. This spread can be effectively addressed if people and platforms add significantly more context to shared posts and platforms nudge people to develop and follow recognized epistemic norms of posting and sharing. (shrink)

This paper proposes three principles for the ethical design of online social environments aiming to minimise the unintended harms caused by users while interacting online, specifically by enhancing the users’ awareness of the moral load of their interactions. Such principles would need to account for the strong mediation of the digital environment and the particular nature of user interactions: disembodied, asynchronous, and ambiguous intent about the target audience. I argue that, by contrast to face to face interactions, additional factors make (...) it more difficult for users to exercise moral sensitivity in an online environment. An ethics for social media user interactions is ultimately an ethics of human relations mediated by a particular environment; hence I look towards an enactive inspired ethics in formulating principles for human interactions online to enhance or at least do not hinder a user’s moral sensitivity. This enactive take on social media ethics supplements classical moral frameworks by asking us to focus on the relations established through the interactions and the environment created by those interactions. (shrink)

ABSTRACT The rise of social media has correlated with an increase in political polarization, which many perceive as a threat to public discourse and democratic governance. This paper presents a framework, drawing on social epistemology and the economic theory of public goods, to explain how social media can contribute to polarization, making us collectively poorer, even while it provides a preferable media experience for individual consumers. Collective knowledge and consensus is best served by having richly connected networks that are epistemically (...) integrated: individuals with diverse levels of expertise should be relatively well connected to each other. In epistemically segregated networks, by contrast, we have reason to predict collective epistemic failures. Expert knowledge will be isolated from the majority, leading average opinion to be less informed than is socially optimal, and entrenching disagreements. Because social media enables users to very easily adopt homophilous network connections – connections to those with similar opinions, education levels, and social backgrounds – it is likely to have increased epistemic segregation compared to older media platforms. The paper explains the theoretical foundations of these predictions, and sketches regulatory measures – such as taxes – that might be employed to preserve the public good of a well integrated social media network. (shrink)

This paper proposes a conceptual framework for evaluating how social networking platforms fare as epistemic environments for human users. I begin by proposing a situated concept of epistemic agency as fundamental for evaluating epistemic environments. Next, I show that algorithmic personalisation of information makes social networking platforms problematic for users’ epistemic agency because these platforms do not allow users to adapt their behaviour sufficiently. Using the tracing principle inspired by the ethics of self-driving cars, I operationalise it here and identify (...) three requirements that automated epistemic environments need to fulfil: (a) the users need to be afforded a range of skilled actions; (b) users need to be sensitive to the possibility to use their skills; (c) the habits built when adapting to the platform should not undermine the user’s pre-existing skills. I then argue that these requirements are almost impossible to fulfil all at the same time on current SN platforms; yet nevertheless, we need to pay attention to these whenever we evaluate an epistemic environment with automatic features. Finally, as an illustration, I show how Twitter, a popular social networking platform, will fare regarding these requirements. (shrink)