Scientists, philosophers, and other researchers commonly assert their theories. This is surprising, as there are good reasons for skepticism about theories in cutting-edge research. I propose a new account of assertion in research contexts that vindicates these assertions. This account appeals to a distinct propositional attitude called endorsement, which is the rational attitude of committed advocacy researchers have to their theories. The account also appeals to a theory of conversational pragmatics known as the Question Under Discussion model, or QUD. Hence, (...) I call the theory the EQUD model. Motivating this account is a recognition that the speech act of assertion has two roles to play in research contexts. The first is the advocacy role, in which researchers assert a theory in order to advocate for it. The second is the evidential role, which is used to add to the common stock of information available to a field of inquiry. The EQUD model provides an account of warranted assertion for both these roles in research contexts. This success provides support for the theory of endorsement. It also provides support for information updating accounts of assertion. (shrink)

Social epistemology is the study of the social dimensions of knowledge or information. There is little consensus, however, on what the term "knowledge" comprehends, what is the scope of the "social", or what the style or purpose of the study should be. According to some writers, social epistemology should retain the same general mission as classical epistemology, revamped in the recognition that classical epistemology was too individualistic. According to other writers, social epistemology should be a more radical departure from classical (...) epistemology, a successor discipline that would replace epistemology as traditionally conceived. The classical approach could be realized in at least two forms. One would emphasize the traditional epistemic goal of acquiring true beliefs. It would study social practices in terms of their impact on the truth-values of agents’ beliefs. A second version of the classical approach would focus on the epistemic goal of having justified or rational beliefs. Applied to the social realm, it might concentrate, for example, on when a cognitive agent is justified or warranted in accepting the statements and opinions of others. Proponents of the anti-classical approach have little or no use for concepts like truth and justification. In addressing the social dimensions of knowledge, they understand "knowledge" as simply what is believed, or what beliefs are "institutionalized" in this or that community, culture, or context. They seek to identify the social forces and influences responsible for knowledge production so conceived. Social epistemology is theoretically significant because of the central role of society in the knowledge-forming process. It also has practical importance because of its possible role in the redesign of information-related social institutions. (shrink)

This is the most comprehensive book ever published on philosophical methodology. A team of thirty-eight of the world's leading philosophers present original essays on various aspects of how philosophy should be and is done. The first part is devoted to broad traditions and approaches to philosophical methodology. The entries in the second part address topics in philosophical methodology, such as intuitions, conceptual analysis, and transcendental arguments. The third part of the book is devoted to essays about the interconnections between philosophy (...) and neighbouring fields, including those of mathematics, psychology, literature and film, and neuroscience. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection ft into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the feld. Moreover, we (...) argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive shortcomings, limitations and biases play a positive functional role in yielding various forms of collective cognitive success. When this idea is transposed to the epistemological domain, mandevillian intelligence emerges as the idea that individual forms of intellectual vice may, on occasion, support the epistemic performance of some form of multi-agent ensemble, such as a socio-epistemic system, a collective doxastic agent, or an epistemic group agent. As a specific (...) form of collective intelligence, mandevillian intelligence is relevant to a number of debates in social epistemology, especially those that seek to understand how group (or collective) knowledge arises from the interactions between a collection of individual epistemic agents. Beyond this, however, mandevillian intelligence raises issues that are relevant to the research agendas of both virtue epistemology and applied epistemology. From a virtue epistemological perspective, mandevillian intelligence encourages us to adopt a relativistic conception of intellectual vice/virtue, enabling us to see how individual forms of intellectual vice may (sometimes) be relevant to collective forms of intellectual virtue. In addition, mandevillian intelligence is relevant to the nascent sub-discipline of applied epistemology. In particular, mandevillian intelligence forces us see the potential epistemic value of (e.g., technological) interventions that create, maintain or promote individual forms of intellectual vice. (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)

Agent-based modelling has become a well-established method in social epistemology and philosophy of science but the question of what kind of explanations these models provide remains largely open. This paper is dedicated to this issue. It starts by distinguishing between real-world phenomena, real-world possibilities, and logical possibilities as different kinds of targets which agent-based models can represent. I argue that models representing the former two kinds provide how-actually explanations or causal how-possibly explanations. In contrast, models that represent logical possibilities provide (...) epistemically opaque how-possibly explanations. While highly idealised ABMs in the form in which they are initially proposed typically fall into the last category, the epistemic opaqueness of explanations they provide can be reduced by validation procedures. To this purpose, an examination of results of simulations in terms of classes of models can be particularly helpful. I illustrate this point by discussing a class of ABMs of scientific interaction and the claim that a high degree of interaction can impede scientific inquiry. (shrink)

This paper disputes the widespread assumption that beliefs and desires may be attributed as theoretical entities in the service of the explanation and predic- tion of human behavior. The literature contains no clear account of how beliefs and desires might generate actions, and there is good reason to deny that principles of rationality generate a choice on the basis of an agent’s beliefs and desires. An alter- native conception of beliefs and desires is here introduced, according to which an attribution (...) of belief is, in a certain sense, an assertion on the believer’s behalf and an attribution of desire is, in a certain sense, a command on the desirer’s behalf. In terms of this conception of the attribution of beliefs and desires, we can begin to understand how attributions of beliefs and desires can be explanatory, although we still cannot expect the attribution of beliefs and desires to generate predictions based on an assumption of rationality. Finally, the reality of beliefs and desires is likened to the reality of money; it is the reality of things governed by objective norms. (shrink)

Abstract‘Serendipity’ is a category used to describe discoveries in science that occur at the intersection of chance and wisdom. In this paper, I argue for understanding serendipity in science as an emergent property of scientific discovery, describing an oblique relationship between the outcome of a discovery process and the intentions that drove it forward. The recognition of serendipity is correlated with an acknowledgment of the limits of expectations about potential sources of knowledge. I provide an analysis of serendipity in science (...) as a defense of this definition and its implications, drawing from theoretical and empirical research on experiences of serendipity as they occur in science and elsewhere. I focus on three interrelated features of serendipity in science. First, there are variations of serendipity. The process of serendipitous discovery can be complex. Second, a valuable outcome must be obtained before reflection upon the significance of the unexpected observation or event in respect to that outcome can take place. Therefore, serendipity is retrospectively categorized. Third, the primacy of epistemic expectations is elucidated. Finally, I place this analysis within discussions in philosophy of science regarding the impact of interpersonal competition upon the number and significance of scientific discoveries. Thus, the analysis of serendipity offered in this paper contributes to discussions about the social-epistemological aspects of scientific discovery and has normative implications for the structure of epistemically effective scientific communities. (shrink)

Building on Friedrich A. Hayek’s work in social philosophy, the paper gives an account of the central role of ignorance in institutional epistemology. The first part of the paper argues that if individuals involved in the search for knowledge are constitutionally ignorant and guided by norms, as Hayek saw them, they are more likely to attain knowledge if they follow different norms, including those that are redundant. The second part of the paper argues that the market as an institutional arrangement, (...) preferred by Hayek for its epistemic features, may lead to an epistemically detrimental reduction of agents following redundant norms. (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)

There is growing interest in understanding and eliciting division of labor within groups of scientists. This paper illustrates the need for this division of labor through a historical example, and a formal model is presented to better analyze situations of this type. Analysis of this model reveals that a division of labor can be maintained in two different ways: by limiting information or by endowing the scientists with extreme beliefs. If both features are present however, cognitive diversity is maintained indefinitely, (...) and as a result agents fail to converge to the truth. Beyond the mechanisms for creating diversity suggested here, this shows that the real epistemic goal is not diversity but transient diversity. (shrink)

Conformity is an often criticized feature of human belief formation. Although generally regarded as a negative influence on reliability, it has not been widely studied. This paper attempts to determine the epistemic effects of conformity by analyzing a mathematical model of this behavior. In addition to investigating the effect of conformity on the reliability of individuals and groups, this paper attempts to determine the optimal structure for conformity. That is, supposing that conformity is inevitable, what is the best way for (...) conformity effects to occur? The paper finds that in some contexts conformity effects are reliability inducing and, more surprisingly even when it is counterproductive, not all methods for reducing its effect are helpful. These conclusions contribute to a larger discussion in social epistemology regarding the effect of social behavior on individual reliability. (shrink)

Diversity of practice is widely recognized as crucial to scientific progress. If all scientists perform the same tests in their research, they might miss important insights that other tests would yield. If all scientists adhere to the same theories, they might fail to explore other options which, in turn, might be superior. But the mechanisms that lead to this sort of diversity can also generate epistemic harms when scientific communities fail to reach swift consensus on successful theories. In this paper, (...) we draw on extant literature using network models to investigate diversity in science. We evaluate different mechanisms from the modeling literature that can promote transient diversity of practice, keeping in mind ethical and practical constraints posed by real epistemic communities. We ask: what are the best ways to promote an appropriate amount of diversity of practice in scientific communities? (shrink)

This paper argues for two propositions. (I) Large asymmetries of power, status and influence exist between economists. These asymmetries constitute a hierarchy that is steeper than it could be and steeper than hierarchies in other disciplines. (II) This situation has potentially significant epistemic consequences. I collect data on the social organization of economics to show (I). I then argue that the hierarchy in economics heightens conservative selection biases, restricts criticism between economists and disincentivizes the development of novel research. These factors (...) together constrain economics’ capacity to develop new beliefs and reduce the likelihood that its outputs will be true. (shrink)

Computer models and simulations have provided enormous benefits to researchers in the natural and social sciences, as well as many areas of philosophy. However, to date, there has been little attempt to use computer models in the development and evaluation of metaphysical theories. This is a shame, as there are good reasons for believing that metaphysics could benefit just as much from this practice as other disciplines. In this paper I assess the possibilities and limitations of using computer models in (...) metaphysics. I outline the way in which different kinds of model could be useful for different areas of metaphysics, and I illustrate in more detail how agent-based models specifically could be used to model two well-known theories of laws: David Lewis’s "Best System Account" and David Armstrong's "Nomic Necessitation" view. Some logically possible processes cannot be simulated on a standard computing device. I finish by assessing how much of a threat this is to the prospect of metaphysical modeling in general. (shrink)

(2013). Modeling herding behavior and its risks. Journal of Economic Methodology: Vol. 20, Methodology, Systemic Risk, and the Economics Profession, pp. 6-18. doi: 10.1080/1350178X.2013.774843.

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)

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)

Recent models of scientific collaboration show that minorities can end up at a disadvantage in bargaining scenarios. However, these models presuppose the existence of social categories. Here, we present a model of scientific collaboration in which inequality arises in the absence of social categories. We assume that all agents are identical except for the position that they occupy in the collaboration network. We show that inequality arises in the absence of social categories. We also show that this is due to (...) the structure of the collaboration network and that similar patterns arise in two real-world collaboration networks. (shrink)

Scientists collect evidence in order to confirm or falsify scientific theories. Unfortunately, scientific evidence may sometimes be false or deceiving and as a consequence lead individuals to believe in a false theory. By interaction between scientists, such false beliefs may spread through the entire community. There is currently a debate about the effect of various network configurations on the epistemic reliability of scientific communities. To contribute to this debate from a logical perspective, this paper introduces an epistemic logical framework of (...) observation, interaction and belief revision in scientific communities. The presented sound and complete system provides the formal tools for qualitative analysis of the social dynamics of scientific inquiry. Furthermore, this paper includes detailed suggestions for future applications of the framework. (shrink)

Evolutionary anthropologists and archaeologists have been considerably successful in modelling the cumulative evolution of culture, of technological skills and knowledge in particular. Recently, one of these models has been introduced in the philosophy of science by De Cruz and De Smedt (Philos Stud 157:411–429, 2012), in an attempt to demonstrate that scientists may collectively come to hold more truth-approximating beliefs, despite the cognitive biases which they individually are known to be subject to. Here we identify a major shortcoming in that (...) attempt: De Cruz & De Smedt’s mathematical model makes one particularly strong tractability assumption that causes the model to largely miss its target (namely, truth accumulation in science), and that moreover conflicts with empirical observations. The second, more constructive part of the paper presents an alternative, agent-based model, which allows one to much better examine the conditions for scientific progress and decline. (shrink)

Some scientists are happy to follow in the footsteps of others; some like to explore novel approaches. It is tempting to think that herein lies an epistemic division of labor conducive to overall scientific progress: the latter point the way to fruitful areas of research, and the former more fully explore those areas. Weisberg and Muldoon’s model, however, suggests that it would be best if all scientists explored novel approaches. I argue that this is due to implausible modeling choices, and (...) I present an alternative ‘epistemic landscape’ model that demonstrates the alleged benefits from division of labor, with one restriction. (shrink)

Recent objections to epistemic permissivism have a metaepistemic flavor. Impermissivists argue that their view best accounts for connections between rationality, planning and deference. Impermissivism is also taken to best explain the value of rational belief and normative assessment. These objections pose a series of metaepistemic explanatory challenges for permissivism. In this paper, I illustrate how permissivists might meet their explanatory burdens by developing two permissivist metaepistemic views which fare well against the explanatory challenges.

The standard epistemic justification for inclusiveness in political decision making is the Condorcet Jury Theorem, which states that the probability of a correct decision using majority rule increases in group size (given certain assumptions). Informally, majority rule acts as a mechanism to pool the information contained in the judgements of individual agents. I aim to extend the explanation of how groups of political agents track the truth. Before agents can pool the information, they first need to find truth-conducive information. Increasing (...) group size is also important in the initial search for truth-conducive information. (shrink)

This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

A theme of much work taking an ““economic approach”” to the study of science is the interaction between the norms of individual scientists and those of society at large. Though drawing from the same suite of formal methods, proponents of the economic approach offer what are in substantive terms profoundly different explanations of various aspects of the structure of science. The differences are illustrated by comparing Strevens's explanation of the scientific reward system (the ““priority rule””) with Max Albert's explanation of (...) the prevalence of ““high methodological standards”” in science. Some objections to the economic approach as a whole are then briefly considered. (shrink)

A concept of diversity is an understanding of what makes a group diverse that may be applicable in a variety of contexts. We distinguish three diversity concepts, show that each can be found in discussions of diversity in science, and explain how they tend to be associated with distinct epistemic and ethical rationales. Yet philosophical literature on diversity among scientists has given little attention to distinct concepts of diversity. This is significant because the unappreciated existence of multiple diversity concepts can (...) generate unclarity about the meaning of “diversity,” lead to problematic inferences from empirical research, and obscure complex ethical-epistemic questions about how to define diversity in specific cases. We illustrate some ethical-epistemic implications of our proposal by reference to an example of deliberative mini-publics on human tissue biobanking. (shrink)

We suggest that philosophical accounts of epistemic effects of diversity have given insufficient attention to the relationship between demographic diversity and information elaboration, the process whereby knowledge dispersed in a group is elicited and examined. We propose an analysis of IE that clarifies hypotheses proposed in the empirical literature and their relationship to philosophical accounts of diversity effects. Philosophical accounts have largely overlooked the possibility that demographic diversity may improve group performance by enhancing IE, and sometimes fail to explore the (...) relationship between diversity and IE altogether. We claim these omissions are significant from both a practical and theoretical perspective. Moreover, we explain how the overlooked explanations suggest that epistemic benefits of diversity can depend on epistemically unjust social dynamics. (shrink)

A number of formal models, including a highly influential model from Hong and Page, purport to show that functionally diverse groups often beat groups of individually high-performing agents in solving problems. Thompson argues that in Hong and Page’s model, that the diverse groups are created by a random process explains their success, not the diversity. Here, I defend the diversity interpretation of the Hong and Page result. The failure of Thompson’s argument shows that to understand the value of functional diversity, (...) we should be clearer about how we conceive of and measure that diversity. (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)

To anyone vaguely aware of Feyerabend, the title of this paper would appear as an oxymoron. For Feyerabend, it is often thought, science is an anarchic practice with no discernible structure. Against this trend, I elaborate the groundwork that Feyerabend has provided for the beginnings of an approach to organizing scientific research. Specifically, I argue that Feyerabend’s pluralism, once suitably modified, provides a plausible account of how to organize science. These modifications come from C.S. Peirce’s account of the economics of (...) theory pursuit, which has since been corroborated by empirical findings in the social sciences. I go on to contrast this approach with the conception of a ‘well-ordered science’ as outlined by Kitcher (Science, truth, and democracy, Oxford University Press, New York, 2001), Cartwright (Philos Sci 73(5):981–990, 2006), which rests on the assumption that we can predict the content of future research. I show how Feyerabend has already given us reasons to think that this model is much more limited than it is usually understood. I conclude by showing how models of resource allocation, specifically those of Kitcher (J Philos 87:5–22, 1990), Strevens (J Philos 100(2):55–79, 2003) and Weisberg and Muldoon (Philos Sci 76(2):225–252, 2009), unwittingly make use of this problematic assumption. I conclude by outlining a proposed model of resource allocation where funding is determined by lottery and briefly examining the extent to which it is compatible with the position defended in this paper. (shrink)

Computational modeling should play a central role in philosophy. In this introduction to our topical collection, we propose a small topology of computational modeling in philosophy in general, and show how the various contributions to our topical collection fit into this overall picture. On this basis, we describe some of the ways in which computational models from other disciplines have found their way into philosophy, and how the principles one found here still underlie current trends in the field. Moreover, we (...) argue that philosophers contribute to computational modeling not only by building their own models, but also by thinking about the various applications of the method in philosophy and the sciences. In this context, we note that models in philosophy are usually simple, while models in the sciences are often more complex and empirically grounded. Bridging certain methodological gaps that arise from this discrepancy may prove to be challenging and fruitful for the further development of computational modeling in philosophy and beyond. (shrink)

The ecosystem approach to computer system development is similar to management of biodiversity. Instead of modeling machines after a successful individual, it models machines after successful teams. It includes measuring the evaluative diversity of human teams (i.e. the disparity in ways members conduct the evaluative aspect of decision-making), adding similarly diverse machines to those teams, and monitoring the impact on evaluative balance. This article reviews new research relevant to this approach, especially the validation of a survey instrument for measuring computational (...) evaluative differences in humans (the GRINSQ). The research confirms the existence of all four known machine types among humans. (shrink)

Supposedly, stubbornness on the part of scientists—an unwillingness to change one’s position on a scientific issue even in the face of countervailing evidence—helps efficiently divide scientific labor. Maintaining disagreement is important because it keeps scientists pursuing a diversity of leads rather than all working on the most promising, and stubbornness helps preserve this disagreement. Planck’s observation that “Science progresses one funeral at a time” might therefore be an insight into epistemically beneficial stubbornness on the part of researchers. In conversation with (...) extant formal models, recent empirical research, and a novel agent-based model of my own I explore whether the epistemic goods which stubbornness can secure—disagreement and diversity—are attainable through less-costly methods. I make the case that they are, at least in part, and also use my modeling results to show that if stubbornness is scientifically valuable, it still involves a willingness to change one’s mind. (shrink)

This article contributes to the revision of the procedure of robustness analysis of mathematical models in epistemic democracy using the systematic review method. It identifies the drawbacks of robustness analysis in epistemic democracy in terms of sample universality and inference from samples with the same results. To exemplify the effectiveness of systematic review, this article conducted a pilot review of diversity trumps ability theorem models, which are mathematical models of deliberation often cited by epistemic democrats. A review of nine models (...) extracted from 352 papers exemplifies the effectiveness of robustness analysis supplemented by systematic review in epistemic democracy. (shrink)

Social movements possess transformative and progressive power. In this paper, I argue that how this is so, or even if this is so, depends on one's explanatory framework. I consider three such explanatory frameworks for social movements: methodological individualism, collectivism, and complexity theory. In evaluating the various appeals and weaknesses of these frameworks, I show that complexity theory is uniquely poised to capture the complex and dynamic reality of the social world.

In this article we focus on the concept of concept in conceptual change. We argue that (1) theories of higher learning must often employ two different notions of concept that should not be conflated: psychological and scientific concepts. The usages for these two notions are partly distinct and thus straightforward identification between them is unwarranted. Hence, the strong analogy between scientific theory change and individual learning should be approached with caution. In addition, we argue that (2) research in psychology and (...) cognitive science provides a promising theoretical basis for developing explanatory mechanistic models of conceptual change. Moreover, we argue that (3) arguments against deeper integration between the fields of psychology and conceptual change are not convincing, and that recent theoretical developments in the cognitive sciences might prove indispensable in filling in the details in mechanisms of conceptual change. (shrink)

This paper is a supplement to, and provides a proof of principle of, Kuhn vs. Popper on Criticism and Dogmatism in Science: A Resolution at the Group Level. It illustrates how calculations may be performed in order to determine how the balance between different functions in science—such as imaginative, critical, and dogmatic—should be struck, with respect to confirmation (or corroboration) functions and rules of scientific method.

At present, peer review is the most common method used by funding agencies to make decisions about resource allocation. But how reliable, efficient, and fair is it in practice? The ex ante evaluation of scientific novelty is a fundamentally uncertain endeavor; bias and chance are embedded in the final outcome. In the current study, I will examine some of the most central problems of peer review and highlight the possible benefits of using a lottery as an alternative decision-making mechanism. Lotteries (...) are driven by chance, not reason. The argument made in the study is that the epistemic landscape could benefit in several respects by using a lottery, thus avoiding all types of bias, disagreement, and other limitations associated with the peer review process. Funding agencies could form a pool of funding applicants who have minimal qualification levels and then select randomly within that pool. The benefits of a lottery would not only be that it saves time and resources, but also that it contributes to a more dynamic selection process and increases the epistemic diversity, fairness, and impartiality within academia. (shrink)

Influence theory is a systematic study of formal models of the communicative influence of one person or group of people on another person or group. In that sense influence theory is an overarching philosophical discipline that includes aspects of decision theory and game theory as sub-disciplines as well as established models of de facto segregation, cultural change, opinion polarization, and epistemic networks. What we offer here is a structured outline of formal results that have been scattered across a range of (...) disciplinary contexts from mathematics, physics and computer science to economics and political science, supplemented with a number of new models, emphasizing their place within the philosophical framework of a general theory of influence. What such an outline offers, we propose, is the prospect of new and important cross-fertilizations and expansions in formal attempts to model the diverse patterns of communicative influence. (shrink)

Scientific research is almost always conducted by communities of scientists of varying size and complexity. Such communities are effective, in part, because they divide their cognitive labor: not every scientist works on the same project. Philip Kitcher and Michael Strevens have pioneered efforts to understand this division of cognitive labor by proposing models of how scientists make decisions about which project to work on. For such models to be useful, they must be simple enough for us to understand their dynamics, (...) but faithful enough to reality that we can use them to analyze real scientific communities. To satisfy the first requirement, we must employ idealizations to simplify the model. The second requirement demands that these idealizations not be so extreme that we lose the ability to describe real-world phenomena. This paper investigates the status of the assumptions that Kitcher and Strevens make in their models, by first inquiring whether they are reasonable representations of reality, and then by checking the models' robustness against weakenings of these assumptions. To do this, we first argue against the reality of the assumptions, and then develop a series of agent-based simulations to systematically test their effects on model outcomes. We find that the models are not robust against weakenings of these idealizations. In fact we find that under certain conditions, this can lead to the model predicting outcomes that are qualitatively opposite of the original model outcomes. (shrink)

When should a scientific community be cognitively diverse? This article presents a model for studying how the heterogeneity of learning heuristics used by scientist agents affects the epistemic efficiency of a scientific community. By extending the epistemic landscapes modeling approach introduced by Weisberg and Muldoon, the article casts light on the micro-mechanisms mediating cognitive diversity, coordination, and problem-solving efficiency. The results suggest that social learning and cognitive diversity produce epistemic benefits only when the epistemic community is faced with problems of (...) sufficient difficulty. (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)

The social epistemology of science would benefit from paying more attention to the nature of argumentative exchanges. Argumentation is not only a cognitive activity but a collaborative social activity whose functioning needs to be understood from a psychological and communicative perspective. Thus far, social and organizational psychology has been used to discuss how social diversity affects group deliberation by changing the mindset of the participants. Argumentative exchanges have comparable effects, but they depend on cognitive diversity and emerge through critical interaction. (...) An example of a cognitive psychological theory is discussed that explains how mutual reasoning affects how we think, make decisions, and solve problems, as well as how cognitive biases may facilitate an efficient division of cognitive labor. These observations are compared with the existing results in the social epistemology of science. Moreover, I explicate the conceptual differences between the distributed and social processing of information. While argumentative exchanges belong to the latter domain, most existing simulations model distributed processing, which may compromise their real-world relevance and proper conceptual interpretation. However, I aim not to criticize the existing simulation methods but to promote an approach from the cognitive psychology of reasoning that complements the current use of organizational psychology and computer simulations by investigating a different set of mechanisms relating to similar phenomena of interest in the social epistemology of science. (shrink)