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)

We motivate a picture of social epistemology that sees forgetting as subject to epistemic evaluation. Using computer simulations of a simple agent-based model, we show that how agents forget can have as large an impact on group epistemic outcomes as how they share information. But, how we forget, unlike how we form beliefs, isn’t typically taken to be the sort of thing that can be epistemically rational or justified. We consider what we take to be the most promising argument for (...) this claim and find it lacking. We conclude that understanding how agents forget should be as central to social epistemology as understanding how agents form beliefs and share information with others. (shrink)

When should you engage with difficult arguments against your cherished controversial beliefs? The primary conclusion of this book is that your obligations to engage with counterarguments are more limited than is often thought. In some standard situations, you shouldn't engage with difficult counterarguments and, if you do, you shouldn't engage with them open-mindedly. This conclusion runs counter to aspects of the Millian political tradition and political liberalism, as well as what people working in informal logic tend to say about argumentation. (...) -/- Not all misleading arguments wear their flaws on their sleeve. Each step of a misleading argument might seem compelling and you might not be able to figure out what's wrong with it. Still, even if you can't figure out what's wrong with an argument, you can know that it's misleading. One way to know that an argument is misleading is, counterintuitively, to lack expertise in the methods and evidence-types employed by the argument. When you know that a counterargument is misleading, you shouldn't engage with it open-mindedly and sometimes shouldn't engage with it at all. You shouldn't engage open-mindedly because you shouldn't be willing to reduce your confidence in response to arguments you know are misleading. And you sometimes shouldn't engage closed-mindedly, because to do so can be manipulative or ineffective. -/- In making this case, Jeremy Fantl discusses echo chambers and group polarization, the importance in academic writing of a sympathetic case for the opposition, the epistemology of disagreement, the account of open-mindedness, and invitations to problematic academic speakers. (shrink)

There is a robust scientific consensus concerning climate change and evolution. But many people reject these expert views, in favour of beliefs that are strongly at variance with the evidence. It is tempting to try to explain these beliefs by reference to ignorance or irrationality, but those who reject the expert view seem often to be no worse informed or any less rational than the majority of those who accept it. It is also tempting to try to explain these beliefs (...) by reference to epistemic overconfidence. However, this kind of overconfidence is apparently ubiquitous, so by itself it cannot explain the difference between those who accept and those who reject expert views. Instead, I will suggest that the difference is in important part explained by differential patterns of epistemic deference, and these patterns, in turn, are explained by the cues that we use to filter testimony. We rely on cues of benevolence and competence to distinguish reliable from unreliable testifiers, but when debates become deeply politicized, asserting a claim may itself constitute signalling lack of reliability. (shrink)

In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...) relevant to robustness analysis. I close by briefly outlining a promising alternative approach inspired by Horwich’s (1982) eliminative account of evidential diversity. (shrink)

Much of contemporary knowledge is generated by groups not single individuals. A natural question to ask is, what features make groups better or worse at generating knowledge? This paper surveys research that spans several disciplines which focuses on one aspect of epistemic communities: the way they communicate internally. This research has revealed that a wide number of different communication structures are best, but what is best in a given situation depends on particular details of the problem being confronted by the (...) group. (shrink)

Computational philosophy is the use of mechanized computational techniques to instantiate, extend, and amplify philosophical research. Computational philosophy is not philosophy of computers or computational techniques; it is rather philosophy using computers and computational techniques. The idea is simply to apply advances in computer technology and techniques to advance discovery, exploration and argument within any philosophical area. -/- After touching on historical precursors, this article discusses contemporary computational philosophy across a variety of fields: epistemology, metaphysics, philosophy of science, ethics and (...) social philosophy, philosophy of language and philosophy of mind, often with examples of operating software. Far short of any attempt at an exhaustive treatment, the intention is to introduce the spirit of each application by using some representative examples. (shrink)

I address the worry that reflective equilibrium is too weak as an account of justification because it fails to let differing views converge. I take up informal aspects of convergence and operationalise them in a formal model of reflective equilibrium. This allows for exploration by the means of computer simulation. Findings show that the formal model does not yield unique outputs, but still boosts agreement. I conclude from this that reflective equilibrium is best seen as a pluralist account of justification (...) that cannot be accused of resulting in an “anything goes” relativism. (shrink)

The purpose of this introduction is to give a rough overview of the discussion of the formalization of arguments, focusing on deductive arguments. The discussion is structured around four important junctions: i) the notion of support, which captures the relation between the conclusion and premises of an argument, ii) the choice of a formal language into which the argument is translated in order to make it amenable to evaluation via formal methods, iii) the question of quality criteria for such formalizations, (...) and finally iv) the choice of the underlying logic. This introductory discussion is supplemented by a brief description of the genesis of the special issue, acknowledgements, and summaries of each article. (shrink)

Does pre-voting group deliberation improve majority outcomes? To address this question, we develop a probabilistic model of opinion formation and deliberation. Two new jury theorems, one pre-deliberation and one post-deliberation, suggest that deliberation is beneficial. Successful deliberation mitigates three voting failures: (1) overcounting widespread evidence, (2) neglecting evidential inequality, and (3) neglecting evidential complementarity. Formal results and simulations confirm this. But we identify four systematic exceptions where deliberation reduces majority competence, always by increasing Failure 1. Our analysis recommends deliberation that (...) is 'participatory', 'neutral', but not necessarily 'equal', i.e., that involves substantive sharing, privileges no evidences, but might privilege some persons. (shrink)

Can arguments and their properties influence the development of issue polarisation in debates among artificial agents? This paper presents an agent-based model of debates with logical constraints based on the theory of dialectical structures. Simulations on this model reveal that the exchange of arguments can drive polarisation even without social influence, and that the usage of different argumentation strategies can influence the obtained levels of polarisation.

An introduction to philosophy of language since Frege, focusing on the 20th century.

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)

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.”.

In the past two decades, epistemologists have significantly expanded the focus of their field. To the traditional question that has dominated the debate — under what conditions does belief amount to knowledge? — they have added questions about testimony, epistemic virtues and vices, epistemic trust, and more. This broadening of the range of epistemic concern has coincided with an expansion in conceptions of epistemic agency beyond the individualism characteristic of most earlier epistemology. We believe that these developments have not gone (...) far enough. While the weak anti-individualism we see in contemporary epistemology may be adequate for the kinds of cases it tends to focus on, a great deal of human knowledge production and transmission does not conform to these models. Furthermore, the dispositions and norms that are knowledge-conducive in the familiar cases may not be knowledge-conducive generally. In fact, dispositions that, at an individual level, count as epistemic vices may be epistemic virtues in common social contexts. We argue that this overlooked feature of human social life means that epistemology must become more deeply and pervasively social. (shrink)

Preface to a special section on "Cooperation in nature, science, and society".

We use recently developed approaches in argumentation theory in order to revamp the hypothetico-deductive model of confirmation, thus alleviating the well-known paradoxes the H-D account faces. More specifically, we introduce the concept of dialectic confirmation on the background of the so-called theory of dialectical structures (Betz 2010, 2012b). Dialectic confirmation generalises hypothetico-deductive confirmation and mitigates the raven paradox, the grue paradox, the tacking paradox, the paradox from conceptual difference, and the problem of surprising evidence.

Science advances by means of argument and debate. Based on a formal model of complex argumentation, this article assesses the interplay between evidential and inferential drivers in scientific controversy, and explains, in particular, why both evidence accumulation and argumentation are veritistically valuable. By improving the conditions for applying veritistic indicators , novel evidence and arguments allow us to distinguish true from false hypotheses more reliably. Because such veritistic indicators also underpin inductive reasoning, evidence accumulation and argumentation enhance the reliability of (...) inductive inference, for example, inference to the best explanation. 1 Introduction2 Theory of Dialectical Structures3 Debate Simulations4 From Evidence and Arguments to Truth: The First Route5 From Evidence to Truth: The Second Route6 Conclusion. (shrink)

This article discusses how inference to the best explanation can be justified as a practical meta - argument. It is, firstly, justified as a practical argument insofar as accepting the best explanation as true can be shown to further a specific aim. And because this aim is a discursive one which proponents can rationally pursue in — and relative to — a complex controversy, namely maximising the robustness of one’s position, IBE can be conceived, secondly, as a meta - argument. (...) My analysis thus bears a certain analogy to Sellars ’ well - known justification of inductive reasoning ; it is based on recently developed theories of complex argumentation. (shrink)

The article presents an agent-based model of scientific interaction aimed at examining how different degrees of connectedness of scientists impact their efficiency in knowledge acquisition. The model is built on the basis of Zollman’s ABM by changing some of its idealizing assumptions that concern the representation of the central notions underlying the model: epistemic success of the rivalling scientific theories, scientific interaction and the assessment in view of which scientists choose theories to work on. Our results suggest that whether and (...) to what extent the degree of connectedness of a scientific community impacts its efficiency is a highly context-dependent matter since different conditions deem strikingly different results. More generally, we argue that simplicity of ABMs may come at a price: the requirement to run extensive robustness analysis before we can specify the adequate target phenomenon of the model.1 1Introduction2Zollman's 2010 Model3Static versus Dynamic Epistemic Success 3.1Introducing the notion of dynamic epistemic success3.2Implementation and results for the basic setup4Critical Interaction 4.1Introducing critique4.2Implementation and results5Inertia of Inquiry 5.1Introducing rational inertia5.2Implementation and results6Threshold Below Which Theories Are Equally Promising 6.1An inquiry that is even more difficult6.2Implementation and results7Discussion8Conclusion. (shrink)

There are different varieties of conservatism concerning belief formation and revision. We assesses the veritistic effects of a particular kind of conservatism commonly attributed to Quine: the so-called maxim of minimum mutiliation, which states that agents should give up as few beliefs as possible when facing recalcitrant evidence. Based on a formal bounded rationality model of belief revision, which parametrizes degree of conservatism, and corresponding multi-agent simulations, we eventually argue against doxastic conservatism from the vantage point of veritistic social epistemology.

In this paper, we investigate the problem of truth approximation via belief merging, i.e., we ask whether, and under what conditions, a group of inquirers merging together their beliefs makes progress toward the truth about the underlying domain. We answer this question by proving some formal results on how belief merging operators perform with respect to the task of truth approximation, construed as increasing verisimilitude or truthlikeness. Our results shed new light on the issue of how rational (dis)agreement affects the (...) inquirers’ quest for truth. In particular, they vindicate the intuition that scientific inquiry, and rational discussion in general, benefits from some heterogeneity in opinion and interaction among different viewpoints. The links between our approach and related analyses of truth tracking, judgment aggregation, and opinion dynamics, are also highlighted. (shrink)

Since at least the 1980s, the role of adversariality in argumentation has been extensively discussed within different domains. Prima facie, there seem to be two extreme positions on this issue: argumentation should never be adversarial, as we should always aim for cooperative argumentative engagement; argumentation should be and in fact is always adversarial, given that adversariality is an intrinsic property of argumentation. I here defend the view that specific instances of argumentation are adversarial or cooperative to different degrees. What determines (...) whether an argumentative situation should be primarily adversarial or primarily cooperative are contextual features and background conditions external to the argumentative situation itself, in particular the extent to which the parties involved have prior conflicting or else convergent interests. To further develop this claim, I consider three teloi that are frequently associated with argumentation: the epistemic telos, the consensus-building telos, and the conflict management telos. I start with a brief discussion of the concepts of adversariality, cooperation, and conflict in general. I then sketch the main lines of the debates in the recent literature on adversariality in argumentation. Next, I discuss the three teloi of argumentation listed above in turn, emphasizing the roles of adversariality and cooperation for each of them. (shrink)

It has recently been argued that the concept of natural kinds should be eliminated because it does not play a productive theoretical role and even harms philosophical research on scientific classification. We argue that this justification for eliminativism fails because the notion of ‘natural kinds’ plays another epistemic role in philosophical research, namely, it enables fruitful investigation into non-arbitrary classification. It does this in two ways: first, by providing a fruitful investigative entry into scientific classification; and second—as is supported by (...) bibliometric evidence—by tying together a research community devoted to non-arbitrary classification. The question of eliminativism then requires weighing off the benefits of retaining the concept against its harms. We argue that the progressive state of philosophical work on natural kinds tips this balance in favour of retaining the concept. (shrink)