Since anonymous agents can spread misinformation with impunity, many people advocate for greater accountability for internet speech. This paper provides a veritistic argument that accountability mechanisms can cause significant epistemic problems for internet encyclopedias and social media communities. I show that accountability mechanisms can undermine both the dissemination of true beliefs and the detection of error. Drawing on social psychology and behavioral economics, I suggest alternative mechanisms for increasing the trustworthiness of internet communication.

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)

Democracy has recently been criticized by several philosophers on grounds of poor epistemic performance. The proposed alternative – epistocracy – faces criticism for failing to uphold and express the core democratic values of civic equality and individual autonomy. In response, proposals have been offered that try to achieve epistocratic performance while retaining democratic inclusion. This paper raises two problems for such proposals, relating to the selection of experts and the incentive-compatibility of the system. Given these failures, I sketch what I (...) call the Wiki-Model. I argue that the Wiki-Model has desirable epistemic properties; realizes our democratic ideals; while also avoiding the two problems that other hybrid models face. (shrink)

In this paper I use philosophical accounts on the relationship between trust and knowledge in science to apprehend this relationship on the Web. I argue that trust and knowledge are fundamentally entangled in our epistemic practices. Yet despite this fundamental entanglement, we do not trust blindly. Instead we make use of knowledge to rationally place or withdraw trust. We use knowledge about the sources of epistemic content as well as general background knowledge to assess epistemic claims. Hence, although we may (...) have a default to trust, we remain and should remain epistemically vigilant; we look out and need to look out for signs of insincerity and dishonesty in our attempts to know. A fundamental requirement for such vigilance is transparency: in order to critically assess epistemic agents, content and processes, we need to be able to access and address them. On the Web, this request for transparency becomes particularly pressing if (a) trust is placed in unknown human epistemic agents and (b) if it is placed in non-human agents, such as algorithms. I give examples of the entanglement between knowledge and trust on the Web and draw conclusions about the forms of transparency needed in such systems to support epistemically vigilant behaviour, which empowers users to become responsible and accountable knowers. (shrink)

Deepfakes are audio, video, or still-image digital artifacts created by the use of artificial intelligence technology, as opposed to traditional means of recording. Because deepfakes can look and sound much like genuine digital recordings, they have entered the popular imagination as sources of serious epistemic problems for us, as we attempt to navigate the increasingly treacherous digital information environment of the internet. In this paper, I attempt to clarify what epistemic problems deepfakes pose and why they pose these problems, by (...) drawing parallels between recordings and our own senses as sources of evidence. I show that deepfakes threaten to undermine the status of digital recordings as evidence. The existence of deepfakes thus encourages a kind of skepticism about digital recordings that bears important similarities to classic philosophical skepticism concerning the senses. However, the skepticism concerning digital recordings that deepfakes motivate is also importantly different from classical skepticism concerning the senses, and I argue that these differences illuminate some possible strategies for solving the epistemic problems posed by deepfakes. (shrink)

This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. (...) For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined. (shrink)

This paper focuses on the epistemic situation one faces when using a Large Language Model based chatbot like ChatGPT: When reading the output of the chatbot, how should one decide whether or not to believe it? By surveying strategies we use with other, more familiar sources of information, I argue that chatbots present a novel challenge. This makes the question of how one could trust a chatbot especially vexing.

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)

The surprisingly high reliability of Wikipedia has often been seen as a beneficial effect of the aggregation of diverse contributors, or as an instance of the wisdom of crowds phenomenon; additional factors such as elite contributors, Wikipedia’s policy or its administration have also been mentioned. We adjudicate between such explanations by modelling and simulating the evolution of a Wikipedia entry. The main threat to Wikipedia’s reliability, namely the presence of epistemically disruptive agents such as disinformers and trolls, turns out to (...) be offset only by a combination of factors: Wikipedia’s administration and the possibility to instantly revert entries, both of which are insufficient when considered in isolation. Our results suggest that the reliability of Wikipedia should receive a pluralist explanation, involving factors of different kinds. (shrink)

Purpose This study aims to analyse how first-year undergraduate audiovisual communication students assess the credibility and reliability of information on Wikipedia in Basque and analyse whether the experience of being a Wikipedia editor helps to improve students’ perceptions of Wikipedia’s trustworthiness. The purpose of this project was to help students to better understand the credibility mechanisms of Wikipedia in Basque regarding the work of editing and creating entries. Do students’ perceptions about how reliable Wikipedia is change if they receive training (...) as Wikipedia content editors and understand Wikipedia’s credibility mechanisms? What are their perceptions about the credibility of Wikipedia? Design/methodology/approach The authors observed and analysed students’ behaviour and perceptions when creating Wikipedia articles and learning about the process of evaluating Wikipedia. This research was carried out at [masked for review] over four consecutive years, where 188 students in the Degree Programme in Audiovisual Communication participated through a questionnaire and in-depth interviews. Findings After the experience of creating content on Wikipedia and learning about Wikipedia’s credibility mechanisms experientially, the majority of students reported that their perception of Wikipedia’s credibility had increased, and 70% of students believed Wikipedia to be reliable or more reliable than expected. A smaller number of students stated that understanding Wikipedia’s editing processes decreased their perception of Wikipedia’s credibility. Practical implications This project will lead to a better understanding of the performance of students in editing content on Wikipedia and of the impact that this editing experience has on students’ perceptions of credibility with respect to Wikipedia. It will make it possible to better incorporate Wikipedia content editing into the learning processes of students and citizens. This study provides interesting keys to improving the reliability and credibility of Wikipedia among students. Social implications As the study examined Basque Wikipedia, it has important social implications since Basque is a minority language and Wikipedia is the main sources of information for students who study in Basque. Originality/value The authors have been analysing the credibility of information in general and that of information on Wikipedia in particular since 2010. Based on this experience, the authors decided to design this study so that it was carried out while the students were creating and editing Wikipedia content as part of a project in their educational curriculum. Furthermore, the study expands the body of research carried out to date by incorporating the perspectives of media studies students. (shrink)

Wikipedia has become increasingly prominent in online search results, serving as an initial path for the public to access “facts,” and lending plausibility to its autobiographical claim to be “the sum of all human knowledge.” However, this self-conception elides Wikipedia’s role as the world’s largest online site of encyclopedic knowledge production. A repository for established facts, Wikipedia is also a social space in which the facts themselves are decided. As a community, Wikipedia is guided by the five pillars—principles that inform (...) and undergird the prevailing epistemic and social norms and practices for Wikipedia participation and contributions. We contend these pillars lend structural support to and help entrench Wikipedia’s gender gap as well as its lack of diversity in both participation and content. In upholding these pillars, Wikipedians may unknowingly undermine otherwise reasonable calls for inclusivity, subsequently reproducing systemic biases. We propose an alternative set of pillars developed through the lens of feminist epistemology, drawing on Lorraine Code’s notion of epistemic responsibility and Helen Longino’s notion of procedural objectivity. Our aim is not only to reduce bias, but also to make Wikipedia a more robust, reliable, and transparent site for knowledge production. (shrink)

Philosophers of argumentation and of testimony suggest that we can rely on what someone says because of its epistemic merits. If so, then we should never credit Wikipedia, since we cannot assess what its anonymous contributors know. I propose instead that Wikipedia can have pragmatic merits, in that the contributors’ passion for the project, and the emerging communicative design through which that passion is made manifest, provide a reason for trust.

En este trabajo se analiza, en el marco de la epistemología social aplicada (es decir, desde una perspectiva analítica y normativa) el debate en torno a la confiabilidad de Wikipedia como fuente de conocimiento, proponiendo que es fiable y que, por tanto, debiéramos confiar en ella para adquirir creencias verdaderas. En primer lugar, se analizan las limitaciones y aciertos de las posturas tradicionales acerca de la fiabilidad de Wikipedia, para luego cuestionar el rol epistemológico que ha adquirido la noción de (...) confianza en dicho debate. En segundo lugar, se introduce la noción de “confianza afectiva” propia de la epistemología del testimonio para contrastarla con la “confianza esperanza”, esto con el fin de caracterizar la normatividad social tanto interna como externa que rige y hace fiable a Wikipedia. Finalmente, se resumen los resultados en una serie de razones de orden epistémico para confiar en Wikipedia como fuente de conocimiento como lo son el poseer virtudes en relación con la difusión de información, mecanismos internos y externos que la sustentan, y su supervivencia al colapso del contexto en internet. De este modo, se sugiere que es adecuado, desde el punto de vista epistemológico, emplear con confianza Wikipedia en nuestra vida cotidiana. (shrink)