My aim in this paper is to develop and defend a novel answer to a question that has recently generated a considerable amount of controversy. The question concerns the normative significance of peer disagreement. Suppose that you and I have been exposed to the same evidence and arguments that bear on some proposition: there is no relevant consideration which is available to you but not to me, or vice versa. For the sake of concreteness, we might picture.

I begin with some familiar conceptions of epistemic relativism. One kind of epistemic relativism is descriptive pluralism. This is the simple, non-normative thesis that many different communities, cultures, social networks, etc. endorse different epistemic systems (E-systems), i.e., different sets of norms, standards, or principles for forming beliefs and other doxastic states. Communities try to guide or regulate their members’ credence-forming habits in a variety of different, i.e., incompatible, ways. Although there may be considerable overlap across cultures in certain types of (...) epistemic norms (e.g., norms for perceptual belief), there are sharp differences across groups in other types of epistemic norms. (shrink)

Helen Longino seeks to break the current deadlock in the ongoing wars between philosophers of science and sociologists of science--academic battles founded on disagreement about the role of social forces in constructing scientific knowledge. While many philosophers of science downplay social forces, claiming that scientific knowledge is best considered as a product of cognitive processes, sociologists tend to argue that numerous noncognitive factors influence what scientists learn, how they package it, and how readily it is accepted. Underlying this disagreement, however, (...) is a common assumption that social forces are a source of bias and irrationality. Longino challenges this assumption, arguing that social interaction actually assists us in securing firm, rationally based knowledge. This important insight allows her to develop a durable and novel account of scientific knowledge that integrates the social and cognitive. Longino begins with a detailed discussion of a wide range of contemporary thinkers who write on scientific knowledge, clarifying the philosophical points at issue. She then critically analyzes the dichotomous understanding of the rational and the social that characterizes both sides of the science studies stalemate and the social account that she sees as necessary for an epistemology of science that includes the full spectrum of cognitive processes. Throughout, her account is responsive both to the normative uses of the term knowledge and to the social conditions in which scientific knowledge is produced. Building on ideas first advanced in her influential book Science as Social Knowledge, Longino brings her account into dialogue with current work in social epistemology and science studies and shows how her critical social approach can help solve a variety of stubborn problems. While the book focuses on epistemological concerns related to the sociality of inquiry, Longino also takes up its implications for scientific pluralism. The social approach, she concludes, best allows us to retain a meaningful concept of knowledge in the face of theoretical plurality and uncertainty. (shrink)

Increasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its (...) members are less aware of their colleagues' experimental results. Second, there is a robust tradeoff between the reliability of a community and the speed with which it reaches a correct conclusion. ‡The author would like to thank Brian Skyrms, Kyle Stanford, Jeffrey Barrett, Bruce Glymour, and the participants in the Social Dynamics Seminar at University of California–Irvine for their helpful comments. Generous financial support was provided by the School of Social Science and Institute for Mathematical Behavioral Sciences at UCI. †To contact the author, please write to: Department of Philosophy, Baker Hall 135, Carnegie Mellon University, Pittsburgh, PA 15213-3890; e-mail: [email protected]. (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)

Figuring prominently in their decisions regarding which theories to pursue are scientists' appeals to the promise or lack of promise of those theories. Yet philosophy of science has had little to say about how one is to assess theory promise. This essay identifies several indices that might be consulted to determine whether or not a theory is promising and worthy of pursuit. Various historical examples of appeals to such indices are introduced.

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly and how-actually explanations. Whereas how-possibly (...) explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims. (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.

Trust in the practice of rational deliberation is widespread and largely unquestioned. This paper uses recent work from business contexts to challenge the view that rational deliberation in a group improves decisions. Pressure to reach consensus can, in fact, lead to phenomena such as groupthink and to suppression of relevant data. Aggregation of individual decisions, rather than deliberation to a consensus, surprisingly, can produce better decisions than those of either group deliberation or individual expert judgment. I argue that dissent is (...) epistemically valuable, not because of the discussion it can provoke (Mill's and Longino's view about the benefit of dissent), but because dissenting positions often are associated with particular data or insights that would be lost in consensus formation. Social epistemologists can usefully pay attention to various methods of aggregation of individual opinion for their effectiveness at realizing epistemic goals. (shrink)

We show that previous results from epistemic network models showing the benefits of decreased connectivity in epistemic networks are not robust across changes in parameter values. Our findings motivate discussion about whether and how such models can inform real-world epistemic communities. As we argue, only robust results from epistemic network models should be used to generate advice for the real-world, and, in particular, decreasing connectivity is a robustly poor recommendation.

I introduce a case study from organization studies to argue that social epistemologists’ recommendation to cultivate diversity and dissent in science is unlikely to be welcomed in the social sciences unless it is coupled with another epistemic ideal: the norm of epistemic responsibility. The norm of epistemic responsibility enables me to show that organization scholars’ concern with the fragmentation of their discipline is generated by false assumptions: the assumption that a diversity of theoretical approaches will lead to fragmentation and the (...) assumption that an imposed consensus on a theoretical approach is needed to maintain the unity of the discipline. (shrink)

Science is a social epistemic enterprise. The complexity of research requires the division of cognitive labor. As a consequence, scientists have to present results and incorporate the results of others into their body of knowledge. This creates the possibility of strategic behavior, leading to phenomena such as publication bias. To analyze the dynamics of strategic behavior in epistemic communities, agent-based modeling suggests itself as a method. The phenomena generated by the developed agent-based simulation model reveal a diverse set of possible (...) dynamics in strategically heterogeneous groups and support the claim that there is a trade-off between a behavioral rule’s efficacy to generate accurate beliefs under optimal conditions and its robustness to variation in the composition of the epistemic environment. (shrink)

It seems obvious that a community of one thousand scientists working together to make discoveries and solve puzzles should arrange itself differently than would one thousand scientist-hermits working independently. Because of limited time, resources, and attention, an independent scientist can explore only some of the possible approaches to a problem. Working alone, each hermit would explore the most promising approaches. They would needlessly duplicate the work of others and would be unlikely to develop approaches which look unpromising but really have (...) tremendous potential. Contrariwise, a large community can more rigorously explore the space of possible approaches. Most scientists should work on the most promising approaches, but a smaller number can be committed to approaches that initially look less promising. Exploratory work can reveal if one of those initially unpromising approaches has unrealized potential, and more scientists can adopt it once its potential becomes more apparent. (shrink)

"--Richard Grandy, Rice University "This is the first compelling diagnosis of what has gone awry in the raging 'science wars.

In Studying Human Behavior, Helen E. Longino enters into the complexities of human behavioral research, a domain still dominated by the age-old debate of “nature versus nurture.” Rather than supporting one side or another or attempting..

Laudan constructs a fresh approach to a longtime problem for the philosopher of science: how to explain the simultaneous and widespread presence of both agreement and disagreement in science. Laudan critiques the logical empiricists and the post-positivists as he stresses the need for centrality and values and the interdependence of values, methods, and facts as prerequisites to solving the problems of consensus and dissent in science.

In a situation of peer disagreement, peers are usually assumed to share the same evidence. However they might not share the same evidence for the epistemic system used to process the evidence. This synchronic complication of the peer disagreement debate suggested by Goldman (In Feldman R, Warfield T (eds) (2010) Disagreement. Oxford University Press, Oxford, pp 187–215) is elaborated diachronically by use of a simulation. The Hegselmann–Krause model is extended to multiple epistemic systems and used to investigate the role of (...) consensus and difference splitting in peer disagreement. I find that the very possibility of multiple epistemic systems downgrades the epistemic value of consensus and makes difference splitting a suboptimal strategy. (shrink)

The central question addressed is: How should scientific research be conducted so as to ensure that nature is respected and the well being of everyone everywhere enhanced? After pointing to the importance of methodological pluralism for an acceptable answer and to obstacles posed by characterizing scientific methodology too narrowly, which are reinforced by the ‘commercial-scientific ethos’, two additional questions are considered: How might research, conducted in this way, have impact on—and depend on—strengthening democratic values and practices? And: What is thereby (...) implied for the responsibilities of scientists today? (shrink)

This article responds to Janet Kourany’s proposal, in Philosophy of Science after Feminism, that scientific practices be held to the ideal of ‘socially responsible science’, to produce results that are not only cognitively sound, but also significant in the light of values ‘that can be morally justified’. Kourany also urges the development of ‘contextualized philosophy of science’—of which feminist philosophy of science is exemplary—that is ‘politically engaged’ and ‘activist’, ‘informed by analyses of the actual ways in which science interacts with (...) the wider society in which it occurs, the ways in which science is shaped by and in turn shapes society’, and that can contribute to understanding both the cognitive and social dimensions of science. Although I share Kourany’s commitment to contextualized philosophy of science, I question her proposed ideal of ‘socially responsible science’ and the grounds she provides for adopting it. My argument leads me to defend rehabilitating the traditional ideal of the ‘neutrality’ of science, which I reinterpret as the ideal of ‘inclusiveness and evenhandedness’. (shrink)

Contributors to the recent disagreement debate have sought to provide a uniform response to cases in which epistemic peers disagree about the epistemic import of a shared body of evidence, no matter what kind of evidence they are disagreeing about. The varied cases addressed in the literature have included examples of disagreement about restaurant bills, court verdicts, weather forecasting, chess, morality, religious beliefs, and even disagreements about philosophical disagreements. The equal treatment of these varied cases has motivated the search for (...) a uniform response to peer disagreement wherever it is encountered. In this article I challenge this prevalent approach in the literature. I grant the notion of epistemic peer and accept that being a peer may amount to the same thing in different domains; nonetheless I contend that different domains appear to call for different responses to disagreement. I argue that the appropriate response to finding out about a disagreement with a peer is different in different domains. (shrink)

Much recent discussion in social epistemology has focussed on the question of whether peers can rationally sustain a disagreement. A growing number of social epistemologists hold that the answer is negative. We point to considerations from the history of science that favor rather the opposite answer. However, we also explain how the other position can appear intuitively attractive.

A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and others’, in (...) order to get a firmer grasp on precisely which features of scientific communities interact with which features of scientific questions in order to influence epistemic outcomes. (shrink)

In this paper we examine the epistemic value of highly idealized agent-based models of social aspects of scientific inquiry. On the one hand, we argue that taking the results of such simulations as informative of actual scientific inquiry is unwarranted, at least for the class of models proposed in recent literature. Moreover, we argue that a weaker approach, which takes these models as providing only “how-possibly” explanations, does not help to improve their epistemic value. On the other hand, we suggest (...) that if ABMs of science underwent two types of robustness analysis, they could indeed have a clear epistemic function, namely by providing evidence for philosophical and historical hypotheses. In this sense, ABMs can obtain evidential and explanatory properties and thus be a useful tool for integrated history and philosophy of science. We illustrate our point with an example of a model—building on the work by Kevin Zollman—which we apply to a concrete historical case study. (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)

It is valuable for inquiry to have researchers who are committed advocates of their own theories. However, in light of pervasive disagreement, such a commitment is not well explained by the idea that researchers believe their theories. Instead, this commitment, the rational attitude to take toward one’s favored theory during the course of inquiry, is what I call endorsement. Endorsement is a doxastic attitude, but one which is governed by a different type of epistemic rationality. This inclusive epistemic rationality is (...) sensitive to reasons beyond those to think the particular proposition in question is true. Instead, it includes extrinsic epistemic reasons, which concern the health of inquiry more generally. Such extrinsic reasons include the distribution of cognitive labor that a researcher will contribute to by endorsing a particular theory. Recognizing endorsement and inclusive epistemic rationality thus allows us to smooth a tension between individual rationality and collective rationality. It does so by showing how it can be epistemically rational to endorse a theory on the basis of the way this endorsement will benefit collective inquiry. I provide a decision theoretic treatment for inclusive epistemic rationality and endorsement which illustrates how this can be accomplished. (shrink)

I argue that recognizing a distinct doxastic attitude called endorsement, along with the epistemic norms governing it, solves the self-undermining problem for conciliationism about disagreement. I provide a novel account of how the self-undermining problem works by pointing out the auxiliary assumptions the objection relies on. These assumptions include commitment to certain epistemic principles linking belief in a theory to following prescriptions of that theory. I then argue that we have independent reason to recognize the attitude of endorsement. Endorsement is (...) the attitude of resilient and committed advocacy which is appropriate for researchers to have toward their own theory. Recognizing the importance of endorsement, and of its resiliency, gives us reason to deny the epistemic principles that serve as auxiliary assumptions in the self-undermining objection. This defuses the objection, and provides additional support for the theory of endorsement. (shrink)

We argue that the analysis of cognitive attitudes should play a central role in developing more sophisticated accounts of the proper roles for values in science. First, we show that the major recent efforts to delineate appropriate roles for values in science would be strengthened by making clearer distinctions among cognitive attitudes. Next, we turn to a specific example and argue that a more careful account of the distinction between the attitudes of belief and acceptance can contribute to a better (...) understanding of the proper roles for values in a case study from paleoanthropology. (shrink)

How should you take into account the opinions of an advisor? When you completely defer to the advisor's judgment, then you should treat the advisor as a guru. Roughly, that means you should believe what you expect she would believe, if supplied with your extra evidence. When the advisor is your own future self, the resulting principle amounts to a version of the Reflection Principle---a version amended to handle cases of information loss. When you count an advisor as an epistemic (...) peer, you should give her conclusions the same weight as your own. Denying that view---call it the ``equal weight view''---leads to absurdity: the absurdity that you could reasonably come to believe yourself to be an epistemic superior to an advisor simply by noting cases of disagreement with her, and taking it that she made most of the mistakes. Accepting the view seems to lead to another absurdity: that one should suspend judgment about everything that one's smart and well-informed friends disagree on, which means suspending judgment about almost everything interesting. But despite appearances, the equal weight view does not have this absurd consequence. Furthermore, the view can be generalized to handle cases involving not just epistemic peers, but also epistemic superiors and inferiors. (shrink)

The aim of this paper is to offer an account of epistemic justification suitable for the context of theory pursuit, that is, for the context in which new scientific ideas, possibly incompatible with the already established theories, emerge and are pursued by scientists. We will frame our account paradigmatically on the basis of one of the influential systems of epistemic justification: Laurence Bonjour’s coherence theory of justification. The idea underlying our approach is to develop a set of criteria which indicate (...) that the pursued system is promising of contributing to the epistemic goal of robustness of scientific knowledge and of developing into a candidate for acceptance. In order to realize this we will (a) adjust the scope of Bonjour’s standards—consistency, inferential density, and explanatory power, and (b) complement them by the requirement of a programmatic character. In this way we allow for the evaluation of the “potential coherence” of the given epistemic system. (shrink)

In this paper I examine the epistemic function of agent-based models of scientific inquiry, proposed in the recent philosophical literature. In view of Boero and Squazzoni’s classification of ABMs into case-based models, typifications and theoretical abstractions, I argue that proposed ABMs of scientific inquiry largely belong to the last category. While this means that their function is primarily exploratory, I suggest that they are epistemically valuable not only as a temporary stage in the development of ABMs of science, but by (...) providing insights into theoretical aspects of scientific rationality. I illustrate my point with two examples of highly idealized ABMs of science, which perform two exploratory functions: Zollman’s ABM which provides a proof-of-possibility in the realm of theoretical discussions on scientific rationality, and an argumentation-based ABM, which provides insights into potential mechanisms underlying the efficiency of scientific inquiry. (shrink)

argumentation has been shown to be a powerful tool within many fields such as artificial intelligence, logic and legal reasoning. In this paper we enhance Dung’s well-known abstract argumentation framework with explanatory capabilities. We show that an explanatory argumentation framework (EAF) obtained in this way is a useful tool for the modeling of scientific debates. On the one hand, EAFs allow for the representation of explanatory and justificatory arguments constituting rivaling scientific views. On the other hand, different procedures for selecting (...) arguments, corresponding to different methodological and epistemic requirements of theory evaluation, can be formulated in view of our framework. (shrink)

It has been claimed that epistemic peers, upon discovering that they disagree on some issue, should give up their opposing views and ‘split the difference’. The present paper challenges this claim by showing, with the help of computer simulations, that what the rational response to the discovery of peer disagreement is—whether it is sticking to one’s belief or splitting the difference—depends on factors that are contingent and highly context-sensitive.Keywords: Peer disagreement; Computer simulations; Opinion dynamics; Hegselmann–Krause model; Social epistemology.

Epistemic peer disagreement raises interesting questions, both in epistemology and in philosophy of science. When is it reasonable to defer to the opinion of others, and when should we hold fast to our original beliefs? What can we learn from the fact that an epistemic peer disagrees with us? A question that has received relatively little attention in these debates is the value of epistemic peer disagreement—can it help us to further epistemic goals, and, if so, how? We investigate this (...) through a recent case in paleoanthropology: the debate on the taxonomic status of Homo floresiensis remains unresolved, with some authors arguing the fossils represent a novel hominin species, and others claiming that they are Homo sapiens with congenital growth disorders. Our examination of this case in the recent history of science provides insights into the value of peer disagreement, indicating that it is especially valuable if one does not straightaway defer to a peer’s conclusions, but nevertheless remains open to a peer’s evidence and arguments. (shrink)

Sometimes we get evidence of our own epistemic malfunction. This can come from finding out we’re fatigued, or have been drugged, or that other competent and well-informed thinkers disagree with our beliefs. This sort of evidence seems to seems to behave differently from ordinary evidence about the world. In particular, getting such evidence can put agents in a position where the most rational response involves violating some epistemic ideal.

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...) examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model. (shrink)

Recent studies of scientific interaction based on agent-based models suggest that a crucial factor conducive to efficient inquiry is what Zollman has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we (...) examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature, as well as some factors that have so far been neglected. This study is obtained via an argumentation-based ABM. Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model. (shrink)

Douglas proposes a new ideal in which values serve an essential function throughout scientific inquiry, but where the role values play is constrained at key points, protecting the integrity and objectivity of science.