Science is a collaborative effort to produce knowledge. Scientists thus must assess what information is trustworthy and who is a competent and honest source and partner. Facing the problem of trust, we can expect scientists to be vigilant. In response to their peers’ vigilance scientists will provide reasons, not only to convince their colleagues to adopt their practices or beliefs, but also to demonstrate that their beliefs and practices are justified. By justifying their beliefs and practices, scientists also justify themselves. (...) Reasons in science thus do not only function as tools of persuasion but also to manage reputation. This analysis strongly suggests that science constitutes a moral system, which has implications for the study and philosophy of science. (shrink)

Universities are knowledge institutions. Compared to several other knowledge institutions (e.g. schools, government research organisations, think tanks), research universities have unusual, anarchic organisational features. We argue that such anarchic features are not a weakness. Rather, they reflect the special standing of research universities among knowledge institutions. We contend that the distributed, self-organising mode of knowledge production maintains a diversity of approaches, topics and solutions needed in frontier research, which involves generating relevant knowledge under uncertainty. Organisational disunity and inconsistencies should sometimes (...) be protected by institutional structures and procedures in order for research universities to best serve their purpose as knowledge institutions. The quality control for the knowledge produced stems from knowledge fields, clusters of knowledge and research that exist beyond the confines of individual organisations. The diversity of epistemic contributions is therefore kept in check by the order imposed by the internal logic of science as a social practice. Our argument provides a new defence for the autonomy of research conducted at universities. (shrink)

Philosophy of the Social Sciences, Volume 52, Issue 5, Page 299-305, September 2022. This is a commentary on William Lynch’s Minority Report, which is a synthesis of the last 75 years of STS writings with philosophical themes from Lakatos, Feyerabend, and others. The comment questions the continued relevance of older ideas of scientific opinion which rested on the supposed autonomy of scientists in the face of the present grant system and the bureaucracy of peer review. The magnitude of the funding (...) of science, and its apparent biases, call the whole of the inherited view of science into question. (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)

A notion that comes from the toolbox of social sciences, trust has become a mainstream epistemological concept in the last 15 years. The notion of epistemic trust has been distinguished from the notion of moral and social trust, the former involves kinds of inferences about the others that are rationally justifiable. If I trust a scientist about the efficacy of a vaccine against COVID-19, I must have an epistemic justification. I am therefore rationally justified in trusting her because I have (...) an epistemic reason to justify my belief. I will challenge the distinction between epistemic and moral and social trust by pointing to several social indicators that contribute to our trustful attitudes in a reasonable way. Social indicators of reputation, values and moral commitments to values are indispensable strategies to come to trust in a rational way, an attitude that is different from merely believing the truth. I also point out the fragility of trusting experts’ reputations and stress the importance of avoiding biases in trusting other people’s reputations to make our deference to experts more robust. (shrink)

One of the most striking and controversial features of Aristotle's moral exemplar, the megalopsychos, is his tendency to be contemptuous. Not surprisingly, modern scholarship has found this attribute of the megalopsychos particularly unappealing. This article probes the question about the targets of the contempt of the Aristotelian megalopsychos and explores the forms that this contempt might take. I argue that the primary targets of the megalopsychos are people who claim superiority on the wrong grounds (their external prosperity and social status). (...) The megalopsychos, who prioritizes virtue over external goods as a criterion of individual worth ( axia), rejects the self-image these people claim for themselves and refuses to grant them the appraisal respect they are accustomed to receiving, and think they deserve. (shrink)

In the social epistemology of scientific knowledge, it is largely accepted that relationships of trust, not just reliance, are necessary in contemporary collaborative science characterised by relationships of opaque epistemic dependence. Such relationships of trust are taken to be possible only between agents who can be held accountable for their actions. But today, knowledge production in many fields makes use of AI applications that are epistemically opaque in an essential manner. This creates a problem for the social epistemology of scientific (...) knowledge, as scientists are now epistemically dependent on AI applications that are not agents, and therefore not appropriate candidates for trust. (shrink)