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 is about a problem that can arise when we try to harness the “wisdom of the crowd” from groups comprised of individuals who exhibit a certain kind of epistemic humility in the way they respond to testimonial evidence. I begin by setting out the problem and then make some initial steps toward solving it. The solution I develop is tentative and may not apply in all circumstances, but it promises to alleviate what seems to me to be a (...) problem of both theoretical interest and practical importance. (shrink)

As more objections have been raised against grant peer-review for being costly and time-consuming, the legitimate question arises whether machine learning algorithms could help assess the epistemic efficiency of the proposed projects. As a case study, we investigated whether project efficiency in high energy physics can be algorithmically predicted based on the data from the proposal. To analyze the potential of algorithmic prediction in HEP, we conducted a study on data about the structure and outcomes of HEP experiments with the (...) goal of predicting their efficiency. In the first step, we assessed the project efficiency using Data Envelopment Analysis of 67 experiments conducted in the HEP laboratory Fermilab. In the second step, we employed predictive algorithms to detect which team structures maximize the epistemic performance of an expert group. For this purpose, we used the efficiency scores obtained by DEA and applied predictive algorithms – lasso and ridge linear regression, neural network, and gradient boosted trees – on them. The results of the predictive analyses show moderately high accuracy, indicating that they can be beneficial as one of the steps in grant review. Still, their applicability in practice should be approached with caution. Some of the limitations of the algorithmic approach are the unreliability of citation patterns, unobservable variables that influence scientific success, and the potential predictability of the model. (shrink)

Confirmation bias has been widely studied for its role in failures of reasoning. Individuals exhibiting confirmation bias fail to engage with information that contradicts their current beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation (...) bias can hurt the knowledge producing capacity of the community. (shrink)

Sometimes inquirers may rationally pursue a theory even when the available evidence does not favor that theory over others. Features of a theory that favor pursuing it are known as considerations of promise or pursuitworthiness. Examples of such reasons include that a theory is testable, that it has a useful associated analogy, and that it suggests new research and experiments. These reasons need not be evidence in favor of the theory. This raises the question: what kinds of reasons are provided (...) by pursuitworthiness considerations? Are they epistemic reasons or practical reasons? I argue that pursuitworthiness considerations are a kind of non-evidential epistemic reason, which I call an inquisitive reason. In support of this, I first point out two important similarities between the traditional pursuitworthiness considerations discussed in philosophy of science, which I call promise reasons, and certain social epistemic reasons that I call social inquisitive reasons. Specifically, both kinds of reason (1) favor pursuing a theory in a non-evidential way, and (2) concern promoting successful inquiry. I then propose recognition of a new category of normative reason: inquisitive reasons. This category contains both promise and social inquisitive reasons. Finally, I argue that inquisitive reasons share three essential features with previously recognized epistemic reasons: a connection to epistemic aims, explanatory independence, and the presence of a specific right-kind/wrong-kind reasons distinction. Each of these features have been used to argue that evidence should be treated as part of a distinct, independent domain of epistemic normativity. Since inquisitive reasons share these features, they too should be considered part of this independent epistemic domain. Thus, inquisitive reasons, including pursuitworthiness considerations, are epistemic reasons. (shrink)

​I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding (...) and application of previously discovered network epistemology effects, notably the Zollman effect (Zollman 2007, 2010). (shrink)

Bayesians standardly claim that there is rational pressure for agents’ credences to cohere across time because they face bad (epistemic or practical) consequences if they fail to diachronically cohere. But as David Christensen has pointed out, groups of individual agents also face bad consequences if they fail to interpersonally cohere, and there is no general rational pressure for one agent's credences to cohere with another’s. So it seems that standard Bayesian arguments may prove too much. Here, we agree with Christensen (...) that there is no general rational pressure to diachronically cohere, but we argue that there are particular cases in which there is rational pressure to diachronically cohere, as well as particular cases in which interpersonal probabilistic coherence is rationally required. More generally, we suggest that Bayesian arguments for coherence apply whenever a collection (of agents or time slices) has a shared dimension of value and an ability to coordinate their actions in a range of cases relevant to that value. Typically, this shared value and ability to coordinate is very strong across the time slices of one human being, and very weak across different human beings, but there are special cases where these can switch—i.e., some groups of humans will have as much reason for their beliefs to cohere across a particular range of cases as the time slices of one human usually do, but some time slices of a human will have as much freedom to differ in their beliefs from the others as the members of a group usually do. (shrink)

Discussions of diversity tend to paint a mixed picture of the practical and epistemic value of diversity. While there are expansive and detailed accounts of the value of cognitive diversity, explorations of identity diversity typically focus on its value as a source or cause of cognitive diversity. The resulting picture on which identity diversity only possesses a derivative practical and epistemic value is unsatisfactory and fails to account for some of its central epistemic benefits. In response, I propose that collective (...) virtue epistemology offers theoretical models that can further our understanding of the benefits of diversity. And I offer a case study to illustrate how this approach could be used to explore the logic of the identity diversity bonus. (shrink)

In this paper, I develop an epistemological argument for freedom from poverty, building on Gerald Gaus’ work on political and moral disagreement in New Diversity Theory (NDT). NDT argues that diversity and disagreement are fundamental to political and moral learning. In this paper, I address Gaus’ central arguments in NDT, and focus on what I argue to be the key epistemological distinction of his account—namely, the argument that the relevant diversity, which is conducive to political and moral learning and should (...) therefore be protected by an institutional order, should not be defended or defined by reference to its performance with regards to discovery of true beliefs, but by reference to the independent epistemic value of protection of disagreeing, redundant and distant investigators. I develop a restatement of this argument from the perspective of institutional epistemology, and show that (along with constitutional liberties, polycentric self-governance and markets) freedom from poverty must be considered an institutional “device” conducive to such a conception of diversity. While Gaus rejects redistributive policies at the level of an institutional order, it is precisely his account of the epistemic powers of diversity and disagreement which provides the strongest defense of minimal redistribution. (shrink)

The foundations of research ethics are riven with fault lines emanating from a fear that if research is too closely connected to weighty social purposes an imperative to advance the common good through research will justify abrogating the rights and welfare of study participants. The result is an impoverished conception of the nature of research, an incomplete focus on actors who bear important moral responsibilities, and a system of ethics and oversight highly attuned to the dangers of research but largely (...) silent about threats of ineffective, inefficient, and inequitable medical practices and health systems. -/- In For the Common Good: Philosophical Foundations of Research Ethics, Alex John London defends a conception of the common good that grounds a moral imperative with two requirements. The first is to promote research that generates the information necessary to enable key social institutions to effectively, efficiently, and equitably safeguard the basic interests of individuals. The second is to ensure that research is organized as a voluntary scheme of social cooperation that respects its various contributors' moral claims to be treated as free and equal. Connecting research to the goals of a just social order grounds a framework for assessing and managing research risk that reconciles these requirements and justifies key oversight practices in non-paternalistic terms. Reconceiving research ethics as resolving coordination problems and providing credible assurance that these requirements are being met expands the issues and actors that fall within the purview of the field and provides the foundation for a more unified and coherent approach to domestic and international research. -/- This is an open access title available under the terms of a CC BY-NC-ND 4.0 license. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. (shrink)

The epistemic subject of collective scientific knowledge has been a matter of dispute in recent philosophy of science and epistemology. Following the distributed cognition framework, both collective-subject accounts (most notably by Knorr-Cetina, in _Epistemic Cultures_, Harvard University Press, 1999) as well as no-subject accounts of collective scientific knowledge (most notably by Giere, Social Epistemology 21:313–320, 2007; in Carruthers, Stich, Siegal (eds), _The Cognitive Basis of Science_, Cambridge University Press, 2002a) have been offered. Both strategies of accounting for collective knowledge are (...) problematic from the perspective of mainstream epistemology. Postulating genuinely collective epistemic subjects is a high-commitment strategy with little clear benefit. On the other hand, eliminating the epistemic subject radically severs the link between knowledge and knowers. Most importantly, both strategies lead to the undesirable outcome that in some cases of scientific knowledge there might be no individual knower that we can identify. I argue that distributed cognition offers us a fertile framework for analyzing complex socio-technical processes of contemporary scientific knowledge production, but scientific knowledge should nonetheless be located in individual knowers. I distinguish between the production and possession of knowledge, and argue that collective knowledge is collectively produced knowledge, not collectively possessed knowledge. I then propose an account of non-testimonial, expert scientific knowledge which allows for collectively produced knowledge to be known by individuals. (shrink)

An increasingly popular solution to the anti-scientific climate rising on social media platforms has been the appeal to more critical thinking from the user's side. In this paper, we zoom in on the ideal of critical thinking and unpack it in order to see, specifically, whether it can provide enough epistemic agency so that users endowed with it can break free from enclosed communities on social media (so called epistemic bubbles). We criticise some assumptions embedded in the ideal of critical (...) thinking online and, instead, we propose that a better way to understand the virtuous behaviour at hand is as critical engagement, namely a mutual cultivation of critical skills among the members of an epistemic bubble. This mutual cultivation allows members within an epistemic bubble (in contrast, as we will show, with the authority-based models of epistemic echo chambers) to become more autonomous critical thinkers by cultivating self-trust. We use the model of relational autonomy as well as resources from work on epistemic self-trust and epistemic interdependence to develop an explanatory framework, which in turn may ground rules for identifying and creating virtuous epistemic bubbles within the environments of social media platforms. (shrink)

Recent philosophical literature has turned its attention towards assessments of how to judge scientific proposals as worthy of further inquiry. Previous work, as well as papers contained within this special issue, propose criteria for pursuitworthiness (Achinstein, 1993; Whitt, 1992; DiMarco & Khalifa, 2019; Laudan, 1977; Shan, 2020; Šešelja et al., 2012). The purpose of this paper is to assess the grounds on which pursuitworthiness demands can be legitimately made. To do this, I propose a challenge to the possibility of even (...) minimal criteria of pursuitworthiness, inspired by Paul Feyerabend. I go on to provide a framework for identifying the contexts in which pursuitworthiness criteria may promote the efficiency of scientific inquiry. I then spell out some implications this framework has for values and pursuit. (shrink)

In this paper we will examine how experts from certain epistemic networks behave in the circumstances of a crisis. Our main goal is to show rhetorical strategies experts use to strengthen their own epistemic authority. We will do that by analysing experts’ strategies used in two pandemics: the one caused by A h1n1 virus in 2009 and the current pandemic caused by SARS-CoV-2. There are four different, but interrelated, rhetorical strategies, that epistemic experts use to consolidate their epistemic authority. Two (...) are internally oriented and consist of 1) experts providing additional reasons for why the measures they propose in the time of crises are rational and (2) experts emphasising their own responsibilities in the crises. Experts also use two externally oriented rhetorical strategies by which they (3) challenge the expertise of other experts and (4) raise doubts about the motives of other epistemic experts. (shrink)

Introduction to the Synthese Special Issue on Disagreement in Science.

Conceptual engineers endeavor to improve our concepts. But their endeavors face serious practical difficulties. One such difficulty – rational conceptual conflict - concerns the degree to which agents are incentivized to impede the efforts of conceptual engineers, especially in many of the contexts within which conceptual engineering is viewed as a worthwhile pursuit. Under such conditions, the already difficult task of conceptual engineering becomes even more difficult. Consequently, if they want to increase their chances of success, conceptual engineers should pay (...) closer attention to – and devise strategies to mitigate – rational conceptual conflict. After outlining the phenomenon at greater length and mapping its connections to other similar practical problems (Section 1), I explore the dynamics of such conflict by way of several detailed case studies (Section 2). In particular, I focus on cases driven by material, social, and moral incentives. I then consider some important methodological implications of rational conceptual conflict (Section 3). Among other things, I argue that conceptual engineers should focus more heavily on cultivating settings that modify the payoffs and penalties associated with conceptual conflict. By such indirect means, they can incentivize conceptual cooperation rather than conflict, thus making it easier to achieve success in conceptual engineering. Section 4 concludes. (shrink)

Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents’ beliefs about which of two (or more) possible actions yields the better result. We find a range of possible outcomes, including stable polarization in belief (...) and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community’s ability to reach accurate consensus about the world. (shrink)

Although there has been a lot of investigation into the influence of the network structure of scientific communities on the one hand and into testimonial norms on the other, a discussion of TNs that take the network structure into account has been lacking. In this paper, I introduce two TNs which are sensitive to the local network structure. According to these norms, scientists should give less weight to the results of well-connected colleagues, as compared to less connected ones. I employ (...) an Agent Based Model to test the reliability of the two novel TNs against different versions of conventional, structure-insensitive TNs in networks of varying size and structure. The results of the simulations show that the novel TNs are more reliable. This suggests that it would be beneficial for scientific communities if their members followed such norms. For individual scientists, I show that there are both reasons for and reasons against adopting them. (shrink)

It is widely believed that open and public speech is at the heart of the democratic ideal. Public discourse is instrumentally epistemically valuable for identifying good policies, as well as necessary for resisting domination (e.g., by vocally challenging decision-makers, demanding public justifications, and using democratic speech to hold leaders accountable). But in our highly polarized and socially fragmented political environment, an increasingly pressing question is: do actual democratic societies live up to the ideal of inclusive public speech? In this essay, (...) I explore Maxime Lepoutre's defence of discursive democracy from the challenge of defective public discourse. I argue that political ignorance, dogmatism, and social fragmentation present more formidable challenges to discursive democracy than Lepoutre acknowledges. As a result, his account occasionally veers from warranted optimism to unwarranted idealism. (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)

It's natural to think of scientists as truth seekers, people driven by an intense curiosity to understand the natural world. Yet this picture of scientists and scientific inquiry sits uncomfortably with the reality and prevalence of scientific fraud. If one wants to get at the truth about nature, why lie? Won't that just set inquiry back, as people pursue false leads? To understand why this occurs – and what can be done about it – we need to understand the social (...) structures scientists work within, and how some of the institutions which enable science to be such a successful endeavour all things considered, also abet and encourage fraud. (shrink)

I defend the thesis that friendship can constitutively require epistemic irrationality against a recent, forceful challenge, raised by proponents of moral and pragmatic encroachment. Defenders of the “encroachment strategy” argue that exemplary friends who are especially slow to believe that their friends have acted wrongly are simply sensitive to the high prudential or moral costs of falsely believing in their friends’ guilt. Drawing on psychological work on epistemic motivation (and in particular on the notion of “need for closure”), I propose (...) a different picture of what friendship requires in the doxastic realm. I argue that contrary to what the encroachment strategy suggests, exemplary friends’ belief formation ought not be guided by a concern with accuracy or error avoidance, but instead by a need to avoid a “specific closure” – namely, a need to avoid concluding in their friends’ guilt. I propose that exemplary friendship often generates a defeasible, doxastic obligation to exemplify such a need, despite its inherent corrupting effects on exemplary friends’ epistemic faculties. (shrink)

In the age of the Internet, people have increased access to information along multiple dimensions. It might seem that we are on our way to an epistemic utopia in which we spend less time and effort on basic cognitive tasks while devoting more time and effort to complex deliberation. However, though there are many accurate sources on the Internet, they must be sifted from the spammers, concern trolls, practical jokers, conspiracy theorists, counterintelligence sock-puppets, and outright liars who also proliferate online. (...) We can approach this problem via the individual or via the network, asking two questions. First, holding the topology of the network constant, which moral and epistemic dispositions are conducive to successful inquiry by nodes at different positions within it? Second, holding the distribution of people’s epistemic dispositions constant, which network topologies are more likely to produce epistemic goods and avoid epistemic ills? To answer these questions, we need to combine virtue-theoretic reflection on individual dispositions with a nuanced understanding of the dynamics of networks. In this paper, I highlight and explore some important properties of such networks and connect those properties with dispositions that make someone an excellent member of an epistemic network. (shrink)

This paper proposes a sender-receiver model to explain two large-scale patterns observed in natural languages: Zipf’s inverse power law relating the frequency of word use and word rank, and the negative correlation between the frequency of word use and rate of lexical change. Computer simulations show that the model recreates Zipf’s inverse power law and the negative correlation between signal frequency and rate of change, provided that agents balance the rates with which they invent new signals and forget old ones. (...) Results are robust across a wide range of parameter values and structural assumptions, such as different forgetting rules and forgetting rates. Analysis of the model further suggests that Zipf’s law relating word frequency and rank arises because of language-external factors and that frequent signals change less because frequent signals are less subject to drift than rare ones. The paper concludes with some brief considerations on model-based and data-driven approaches in philosophy. (shrink)

What structure of scientific communication and cooperation, between what kinds of investigators, is best positioned to lead us to the truth? Against an outline of standard philosophical characteristics and a recent turn to social epistemology, this paper surveys highlights within two strands of computational philosophy of science that attempt to work toward an answer to this question. Both strands emerge from abstract rational choice theory and the analytic tradition in philosophy of science rather than postmodern sociology of science. The first (...) strand of computational research models the effect of communicative networks within groups, with conclusions regarding the potential benefit of limited communication. The second strand models the potential benefits of cognitive diversity within groups. Examples from each strand of research are used in analyzing what makes modeling of this sort both promising and distinctly philosophical, but are also used to emphasize possibilities for failure and inherent limitations as well. (shrink)

Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”.

A small consortium of philosophers has begun work on the implications of epistemic networks (Zollman 2008 and forthcoming; Grim 2006, 2007; Weisberg and Muldoon forthcoming), building on theoretical work in economics, computer science, and engineering (Bala and Goyal 1998, Kleinberg 2001; Amaral et. al., 2004) and on some experimental work in social psychology (Mason, Jones, and Goldstone, 2008). This paper outlines core philosophical results and extends those results to the specific question of thresholds. Epistemic maximization of certain types does show (...) clear threshold effects. Intriguingly, however, those effects appear to be importantly independent from more familiar threshold effects in networks. (shrink)

How much does rationality constrain what we should believe on the basis of our evidence? According to this book, not very much. For most people and most bodies of evidence, there is a wide range of beliefs that rationality permits them to have in response to that evidence. The argument, which takes inspiration from William James' ideas in 'The Will to Believe', proceeds from two premises. The first is a theory about the basis of epistemic rationality. It's called epistemic utility (...) theory, and it says that what it is epistemically rational for you to believe is what it would be rational for you to choose if you were given the chance to pick your beliefs and, when picking them, you were to care only about their epistemic value. So, to say which beliefs are permitted, we must say how to measure epistemic value, and which decision rule to use when picking your beliefs. The second premise is a claim about attitudes to epistemic risk, and it says that rationality permits many different such attitudes. These attitudes can show up in epistemic utility theory in two ways: in the way you measure epistemic value; and in the decision rule you use to pick beliefs. This book explores the latter. The result is permissivism about epistemic rationality: different attitudes to epistemic risk lead to different choices of prior beliefs; given most bodies of evidence, different priors lead to different posteriors; and even once we fix your attitudes to epistemic risk, if they are at all risk-inclined, there is a range of different priors and therefore different posteriors they permit. (shrink)

The present paper addresses the question of whether outsiders in science can be rational. This question is addressed on three levels: the level of beliefs of outsiders, the level of decisions of out-siders, and the level of assertions of outsiders. It is argued that outsiders can indeed be rational but only within tightly constrained limits.

Proponents of epistocracy worry that high levels of voter ignorance can harm democracies. To combat such ignorance, they recommend allocating comparatively more political power to more politically knowledgeable citizens. In response, some recent critics of epistocracy contend that epistocratic institutions risk causing even more harm, since much evidence from political psychology indicates that more politically knowledgeable citizens are typically more biased, less open-minded, and more prone to motivated reasoning about political matters than their less knowledgeable counterparts. If so, perhaps epistocratic (...) institutions will perform worse epistemically than corresponding democratic institutions. Call this 'the problem of epistocratic irrationality'. This paper argues that the problem of epistocratic irrationality can be overcome. First, I argue that critics of epistocracy have overlooked several complications regarding the psychological data they claim shows that more knowledgeable citizens are less politically rational. Second, I argue that appropriately designed epistocratic institutions could overcome the problem of epistocratic irrationality even if such critics have interpreted the data correctly. I first explore whether refined selection mechanisms could allow epistocrats to avoid empowering less rational citizens, before assessing the prospects of implementing only those epistocratic institutions with a solid track record of reliable performance. (shrink)

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)

In the past few years, social epistemologists have developed several formal models of the social organisation of science. While their robustness and representational adequacy has been analysed at length, the function of these models has begun to be discussed in more general terms only recently. In this article, I will interpret many of the current formal models of the scientific community as representing the latest development of what I will call the ‘Kuhnian project’. These models share with Kuhn a number (...) of questions about the relation between individuals and communities. At the same time, they also inherit some of Kuhn’s problematic characterisations of the scientific community. In particular, current models of the social organisation of science represent the scientific community as essentially value-free. This may put into question both their representational adequacy and their normative ambitions. In the end, it will be shown that the discussion on the formal models of the scientific community may contribute in fruitful ways to the ongoing debates on value judgements in science. (shrink)

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types of conformity (...) that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups. (shrink)

Pragmatic theories of truth need to pass the pragmatic test: they need to make a difference. Unfortunately, defenders of the pragmatic theory have rarely applied this test. I argue that a Deweyan pragmatic account of truth passes the test by identifying the political and epistemic dangers of certain types of social networks that create a durable consensus around false beliefs. To better understand Dewey’s account of truth I propose an excursion through Wittgenstein’s later views on knowledge and certainty.

Scientific reasoning represents complex argumentation patterns that eventually lead to scientific discoveries. Social epistemology of science provides a perspective on the scientific community as a whole and on its collective knowledge acquisition. Different techniques have been employed with the goal of maximization of scientific knowledge on the group level. These techniques include formal models and computer simulations of scientific reasoning and interaction. Still, these models have tested mainly abstract hypothetical scenarios. The present thesis instead presents data-driven approaches in social epistemology (...) of science. A data-driven approach requires data collection and curation for its further usage, which can include creating empirically calibrated models and simulations of scientific inquiry, performing statistical analyses, or employing data- mining techniques and other procedures. -/- We present and analyze in detail three co-authored research projects on which the thesis’ author was engaged during her PhD. The first project sought to identify optimal team composition in high energy physics laboratories using data-mining techniques. The results of this project are published in (Perović et al. 2016), and indicate that projects with smaller numbers of teams and team members outperform bigger ones. In the second project, we attempted to determine whether there is an epistemic saturation point in experimentation in high energy physics. The initial results from this project are published in (Sikimić et al. 2018). In the thesis, we expand on this topic by using computer simulations to test for biases that could induce scientists to invest in projects beyond their epistemic saturation point. Finally, in previous examples of data-driven analyses, citations are used as a measure of epistemic efficiency of projects in high energy physics. In order to additionally justify and analyze the usage of this parameter in their data-driven research, in the third project Perović & Sikimić (2019) analyzed and compared inductive patterns in experimental physics and biology with the reliability of citation records in these fields. They conclude that while citations are a relatively reliable measure of efficiency in high energy physics research, the same does not hold for the majority of research in experimental biology. -/- Additionally, contributions of the author that are for the first time published in this theses are: (a) an empirically calibrated model of scientific interaction of research groups in biology, (b) a case study of irregular argumentation patterns in some pathogen discoveries, and (c) an introductory discussion of the benefits and limitations of data- driven approaches to the social epistemology of science. Using computer simulations of an empirically calibrated model, we demonstrate that having several levels of hierarchy and division into smaller research sub-teams is epistemically beneficial for researchers in experimental biology. We also show that argumentation analysis in biology represents a good starting point for further data-driven analyses in the field. Finally, we conclude that a data-driven approach is informative and useful for science policy, but requires careful considerations about data collection, curation, and interpretation. (shrink)

Policymakers who seek to make scientifically informed decisions are constantly confronted by scientific uncertainty and expert disagreement. This thesis asks: how can policymakers rationally respond to expert disagreement and scientific uncertainty? This is a work of non-ideal theory, which applies formal philosophical tools developed by ideal theorists to more realistic cases of policymaking under scientific uncertainty. I start with Bayesian approaches to expert testimony and the problem of expert disagreement, arguing that two popular approaches— supra-Bayesianism and the standard model of (...) expert deference—are insufficient. I develop a novel model of expert deference and show how it can deal with many of these problems raised for them. I then turn to opinion pooling, a popular method for dealing with disagreement. I show that various theoretical motivations for pooling functions are irrelevant to realistic policymaking cases. This leads to a cautious recommendation of linear pooling. However, I then show that any pooling method relies on value judgements, that are hidden in the selection of the scoring rule. My focus then narrows to a more specific case of scientific uncertainty: multiple models of the same system. I introduce a particular case study involving hurricane models developed to support insurance decision-making. I recapitulate my analysis of opinion pooling in the context of model ensembles, confirming that my hesitations apply. This motivates a shift of perspective, to viewing the problem as a decision theoretic one. I rework a recently developed ambiguity theory, called the confidence approach, to take input from model ensembles. I show how it facilitates the resolution of the policymaker’s problem in a way that avoids the issues encountered in previous chapters. This concludes my main study of the problem of expert disagreement. In the final chapter, I turn to methodological reflection. I argue that philosophers who employ the mathematical methods of the prior chapters are modelling. Employing results from the philosophy of scientific models, I develop the theory of normative modelling. I argue that it has important methodological conclusions for the practice of formal epistemology, ruling out popular moves such as searching for counterexamples. (shrink)

Philosophers have usually highlighted how the weakness and paucity of historical evidence underdetermine the choice between rival historical explanations. Focusing underdetermination on the link between theory and evidence comes, I argue, with three assumptions: competing hypotheses are easy to generate, investigators agree on the constitution and interpretation of the evidence and a plurality of hypotheses is a useful evil to reach consensus. The last assumption implies that the sustained coexistence of incompatible hypotheses is considered as a scientific failure. I argue (...) that this negative vision of sustained disagreement has monistic undertones. By drawing from a case study in evolutionary biology, this paper defends a form of scientific pluralism. Firstly, I show that underdetermination is not only found at the inferential level but also at the level of the constitution and interpretation of the evidence, on the choice of investigative scaffolds and when interpreting background theories. Because of that, competing hypotheses exhibit a degree of methodological incommensurability. While catastrophic from a monistic standpoint, I defend that scientific pluralism gives a different, and I think richer, account of such situations. On the plus side, competing approaches benefit from their sustained coexistence and interaction. I argue that this generates direct and indirect epistemic goods independently of whether the controversy is solved. Scientific pluralism also shifts our attention from achieving consensus to managing disagreement. The challenge becomes to maintain the conditions for fruitful interactions in a community with incommensurable approaches and heterogeneous expertise. (shrink)

Thought: A Journal of Philosophy, EarlyView.

The epistemic attitudes of scientists, such as epistemic tolerance and authoritarianism, play important roles in the discourse about rivaling theories. Epistemic tolerance stands for the mental attitude of an epistemic agent, e.g., a scientist, who is open to opposing views, while epistemic authoritarianism represents the tendency to uncritically accept views of authorities. Another relevant epistemic factor when it comes to the epistemic decisions of scientists is the skepticism towards the scientific method. However, the question is whether these epistemic attitudes are (...) influenced by their sociopolitical counterparts, such as the researcher’s degree of conservatism. To empirically investigate the interplay between epistemic and sociopolitical attitudes of scientists, we conducted a survey with researchers (N = 655) across different disciplines. We propose scales for measuring epistemic tolerance and epistemic authoritarianism, as well as a scale for detecting the participants' readiness to question the scientific method. Furthermore, we investigate the relationship between epistemic tolerance and epistemic authoritarianism on the one hand, and career stage and sociopolitical views on the other hand. Interestingly, our study found only small correlations between the participants' degree of conservatism and their epistemic attitudes. This suggests that political views, against common argumentation, actually do not play an important role in one’s scientific decisions. Moreover, social scientists scored higher on the epistemic tolerance and lower on the epistemic authoritarianism scale than natural scientists. Finally, the results indicate that natural scientists question the scientific method less than social scientists. (shrink)

A new way to transpose the virtue epistemologist’s ‘knowledge = apt belief’ template to the collective level, as a thesis about group knowledge, is developed. In particular, it is shown how specifically judgmental belief can be realised at the collective level in a way that is structurally analogous, on a telic theory of epistemic normativity (e.g., Sosa 2020), to how it is realised at the individual level—viz., through a (collective) intentional attempt to get it right aptly (whether p) by alethically (...) affirming that p. An advantage of the proposal developed is that it is shown to be compatible with competing views—viz., joint acceptance accounts and social-distributive accounts—of how group members must interact in order to materially realise a group belief. I conclude by showing how the proposed judgment-focused collective (telic) virtue epistemology has important advantages over a rival version of collective virtue epistemology defended in recent work by Jesper Kallestrup (2016). (shrink)

Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of ‘methodological iteration’ whereby the models initiate new lines (...) of inquiry, isolate and clarify problems with existing knowledge claims, and stimulate further research. (shrink)

Our aim in this chapter is to draw attention to what we see as a disturbing feature of conciliationist views of disagreement. Roughly put, the trouble is that conciliatory responses to in-group disagreement can lead to the frustration of a group's epistemic priorities: that is, the group's favoured trade-off between the "Jamesian goals" of truth-seeking and error-avoidance. We show how this problem can arise within a simple belief aggregation framework, and draw some general lessons about when the problem is most (...) pronounced. We close with a tentative proposal for how to solve the problem raised without rejecting conciliationism. (shrink)

Group agents can act, and they can have knowledge. How should we understand the species of collective action which aims at knowledge? In this paper, I present an account of group inquiry. This account faces two challenges: to make sense of how large-scale distributed activities might be a kind of group action, and to make sense of the kind of division of labour involved in collective inquiry. In the first part of the paper, I argue that existing accounts of group (...) action face problems dealing with large-scale group actions, and propose a minimal alternative account. In the second part of the paper, I draw on an analogy between inquiry and conversation, arguing that work by Robert Stalnaker and Craige Roberts helps us to think about the division of labour. In the final part of the paper I put the accounts of group action and inquiry together, and consider how to think about group knowledge, deep ignorance, and the different kinds of division of labour. (shrink)