Models of Scientific Communities by Cailin O'Connor
Trends in Cognitive Science, 2024
The study of intellectual humility (IH), which is gaining increasing interest among cognitive sci... more The study of intellectual humility (IH), which is gaining increasing interest among cognitive scientists, has been dominated by a focus on individuals. We propose that IH operates at the collective level as the tendency of a collective’s members to attend to each other’s intellectual limitations and the limitations of their collective cognitive efforts. Given people’s propensity to better recognize others’ limitations than their own, IH may be more readily achievable in collectives than individuals. We describe the socio-cognitive dynamics that can interfere with collective IH and offer the solution of building intellectually humbling environments that create a culture of IH that can outlast the given membership of a collective. We conclude with promising research directions.
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The values in science literature considers deep questions around value laden aspects of inquiry l... more The values in science literature considers deep questions around value laden aspects of inquiry like: Where and when can values of different sorts legitimately influence science? What sorts of values, and related ethical practices, best promote scientific inquiry? How do individual beliefs and biases impact science? Earlier work in this area focused mostly on how values interact with individual practice. But increasingly there has been a move towards thinking about how the impacts of values can reverberate through scientific communities, and how the dynamics of social groups may lead to unexpected outcomes when values shape science. At the same time, social epistemologists and others have been using network models to think about how social network structures and group features shape knowledge generation. These models are often useful in thinking about the emergent, group-level effects of values on scientific progress. This paper will briefly survey this network literature and connect it with the literature on values in science.
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We review several topics of philosophical interest connected to misleading online content. First ... more We review several topics of philosophical interest connected to misleading online content. First we consider proposed definitions of different types of misleading content. Then we consider the epistemology of misinformation, focusing on approaches from virtue epistemology and social epistemology. Finally we discuss how misinformation is related to belief polarization, and argue that models of rational polarization present special challenges for conceptualizing fake news and misinformation.
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Philosophical Topics, 2023
Scientific curation, where scientific evidence is selected and shared, is essential to public bel... more Scientific curation, where scientific evidence is selected and shared, is essential to public belief formation about science. Yet common curation practices can distort the body of evidence the public sees. Focusing on science journalism, we employ computational models to investigate how such distortions influence public belief. We consider these effects for agents with and without confirmation bias. We find that standard journalistic practices can lead to significant distortions in public belief; that pre-existing errors in public belief can drive further distortions in reporting; that practices that appear relatively unobjectionable can produce serious epistemic harm; and that, in some cases, common curation practices related to fairness and extreme reporting can lead to polarization.
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Oxford Handbook of Cultural Evolution, 2023
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Philosophy of Science, 2024
Confirmation bias has been widely studied for its role in failures of reasoning. Individuals
exh... more Confirmation bias has been widely studied for its role in failures of reasoning. Individuals
exhibiting confirmation bias fail to engage with information that contradicts their current
beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation bias can hurt the knowledge producing capacity of the community.
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Synthese, 2023
Diversity of practice is widely recognized as crucial to scientific progress. If all scientists p... more 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 the right amount of diversity of practice in such communities?
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Collective Intelligence, 2022
Why do bad methods persist in some academic disciplines, even when they have been clearly rejecte... more Why do bad methods persist in some academic disciplines, even when they have been clearly rejected in others? What factors allow good methodological advances to spread across disciplines? In this paper, we investigate some key features determining the success and failure of methodological spread between the sciences. We introduce a model that considers factors like methodological competence and reviewer bias towards one's own methods. We show how self-preferential biases can protect poor methodology within scientific communities, and lack of reviewer competence can contribute to failures to adopt better methods. We further argue, however, that input from outside disciplines, especially in the form of peer review and other credit assignment mechanisms, can help break down barriers to methodological improvement.
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Philosophy of Science
Sometimes retracted or thoroughly refuted scientific information is used and propagated long afte... more Sometimes retracted or thoroughly refuted scientific information is used and propagated long after it is understood to be misleading. Likewise, sometimes retracted news items spread and persist, even after it has been publicly established that they are false. In this paper, we use agent-based models of epistemic networks to explore the dynamics of retraction. In particular, we focus on why false beliefs might persist, even in the face of retraction. We find that in many cases those who have received false information simply fail to receive retractions due to social dynamics. Surprisingly, we find that in some cases delaying retraction may increase its impact. We also find that retractions are most successful when issued by the original source of misinformation, rather than a separate source.
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Synthese
Why do people who disagree about one subject tend to disagree about other subjects as well? In th... more Why do people who disagree about one subject tend to disagree about other subjects as well? In this paper, we introduce a network epistemology model to explore this phenomenon of "epistemic factionization". Agents attempt to discover the truth about multiple beliefs by testing the world and sharing evidence gathered. But agents tend to mistrust evidence shared by those who do not hold similar beliefs. This mistrust leads to the endogenous emergence of factions of agents with multiple, highly correlated, polarized beliefs.
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Synthese, 2020
NOTE - this v. updated in 2023 to correct a small error.
Scientists are generally subject to s... more NOTE - this v. updated in 2023 to correct a small error.
Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents' beliefs about which of two (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world.
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British Journal for Philosophy of Science, 2018
In their recent book Merchants of Doubt [New York:Bloomsbury 2010], Naomi Oreskes and Erik Conway... more In their recent book Merchants of Doubt [New York:Bloomsbury 2010], Naomi Oreskes and Erik Conway describe the "tobacco strategy" , which was used by the tobacco industry to influence policy makers regarding the health risks of tobacco products. The strategy involved two parts, consisting of (1) promoting and sharing independent research supporting the industry's preferred position and (2) funding additional research, but selectively publishing the results. We introduce a model of the Tobacco Strategy, and use it to argue that both prongs of the strategy can be extremely effective—even when policy makers rationally update on all evidence available to them. As we elaborate, this model helps illustrate the conditions under which the Tobacco Strategy is particularly successful. In addition, we show how journalists engaged in "fair" reporting can inadvertently mimic the effects of industry on public belief.
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European Journal for the Philosophy of Science, 2018
Contemporary societies are often " polarized " , in the sense that subgroups within these societi... more Contemporary societies are often " polarized " , in the sense that subgroups within these societies hold stably opposing beliefs, even when there is a fact of the matter. Extant models of polarization do not capture the idea that some beliefs are true and others false. Here we present a model, based on the network epistemology framework of Bala and Goyal [ " Learning from neighbors " , Rev. Econ. Stud. 65(3), 784-811 (1998)], in which polarization emerges even though agents gather evidence about their beliefs, and true belief yields a pay-off advantage. The key mechanism that generates polarization involves treating evidence generated by other agents as uncertain when their beliefs are relatively different from one's own.
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Philosophy of Science, 2017
We show that previous results from epistemic network models (Zollman, 2007, 2010; Kummerfeld and ... more We show that previous results from epistemic network models (Zollman, 2007, 2010; Kummerfeld and Zollman, 2015) 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.
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Social epistemologists have argued that high risk, high reward science has an important role to p... more Social epistemologists have argued that high risk, high reward science has an important role to play in scientific communities. Nonetheless, it has been argued that various scientific fields seem to be trending towards conservatism—the increasing production of what Kuhn (1970) might have called 'normal science'. This paper will explore a possible explanation for this trend: that the process by which scientific research groups form, grow, and dissolve might be inherently hostile to high risk, high reward science. In particular, I employ a paradigm developed by Smaldino and McElreath (2016) that treats a scientific community as a population undergoing selection. I will explore two possibilities. The first is that the chance of failure for high risk science means that fewer scientific mavericks will influence the next crop of successful scientists. The second is that risky science is, in general, the sort of thing that is hard to repeat. While more conservative scientists will be able to train students capable of continuing their successful projects, and so create thriving lineages, successful risky science may not be the sort of thing one can easily pass on. In such cases, the structure of scientific communities should select against risky projects.
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Dynamics and Diversity by Cailin O'Connor
Australasian Journal of Philosophy, 2020
Standard accounts of convention include notions of arbitrariness. But many have conceived of conv... more Standard accounts of convention include notions of arbitrariness. But many have conceived of conventionality as an all or nothing affair. In this paper, I develop a framework for thinking of conventions as coming in degrees of arbitrariness. In doing so, I introduce an information the-oretic measure intended to capture the degree to which a solution to a certain social problem could have been otherwise. As the paper argues, this framework can help improve explanation aimed at the cultural evolution of social traits. Good evolutionary explanations recognize that most functional traits are also conventional, at least to some degree, and vice versa.
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Synthese
The study of social justice asks: what sorts of social arrangements are equitable ones? But also:... more The study of social justice asks: what sorts of social arrangements are equitable ones? But also: how do we derive the inequitable arrangements we often observe in human societies? In particular, in spite of explicitly stated equity norms, categorical inequity tends to be the rule rather than the exception. The cultural red king hypothesis predicts that differentials in group size may lead to inequitable outcomes for minority groups even in the absence of explicit or implicit bias. We test this prediction in an experimental context where subjects divided into groups engage in repeated play of a bargaining game. We ran 14 trials involving a total of 112 participants. The results of the experiments are significant and suggestive: individuals in minority groups do indeed end up receiving fewer resources than those in majority groups.
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Politics, Philosophy, and Economics, 2019
Many societies have state norms of equity—that those who make symmetric social contributions dese... more Many societies have state norms of equity—that those who make symmetric social contributions deserve symmetric rewards. Despite this, there are widespread patterns of social inequity, especially along gender and racial lines. It is often the case that members of certain social groups receive greater rewards per contribution than others. In this paper, we draw on evolutionary game theory to show that the emergence of this sort of inequitable convention is far from surprising. In simple cultural evolutionary models, inequity is much more likely to emerge than equity, despite the presence of stable, equitable outcomes that groups might instead learn. As we outline, social groups provide a way to break symmetry between actors in determining both contributions and rewards in joint projects.
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Ergo, 2021
We use tools from evolutionary game theory to examine how power might influence the cultural evo... more We use tools from evolutionary game theory to examine how power might influence the cultural evolution of inequitable conventions between discernible groups (such as gender or racial groups) in a population of otherwise identical individuals. Similar extant models always assume that power is homogeneous across a social group. As such, these models fail to capture situations where individuals who are not themselves disempowered nonetheless end up disadvantaged in bargaining scenarios by dint of their social group membership. Our models show that even when most individuals in two discernible sub-groups are relevantly identical, powerful individuals can affect the social outcomes for their entire group under a range of conditions; this results in power by association for their in-group and a bargaining disadvantage for their out-group
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This paper describes a class of idealized models that illuminate minimal conditions for inequity.... more This paper describes a class of idealized models that illuminate minimal conditions for inequity. Some such models will track the actual causal factors that generate real world inequity. Others may not. Whether or not these models do track these real-world factors is irrelevant to the epistemic role they play in showing that minimal commonplace factors are enough to generate inequity. In such cases, it is the fact that the model does not fit the world that makes it a particularly powerful argumentative tool. As I will argue, this epistemic role is a particularly important one when it comes to modeling inequity, because such models are often also aimed at interventions to stop it. Given this, it is crucial to know if we intervene on the current causes of inequity, what other, common social factors might continue to contribute to it.
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Models of Scientific Communities by Cailin O'Connor
exhibiting confirmation bias fail to engage with information that contradicts their current
beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation bias can hurt the knowledge producing capacity of the community.
Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents' beliefs about which of two (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world.
Dynamics and Diversity by Cailin O'Connor
exhibiting confirmation bias fail to engage with information that contradicts their current
beliefs, and, as a result, can fail to abandon inaccurate beliefs. But although most investigations of confirmation bias focus on individual learning, human knowledge is typically developed within a social structure. We use network models to show that moderate confirmation bias often improves group learning. However, a downside is that a stronger form of confirmation bias can hurt the knowledge producing capacity of the community.
Scientists are generally subject to social pressures, including pressures to conform with others in their communities, that affect achievement of their epistemic goals. Here we analyze a network epistemology model in which agents, all else being equal, prefer to take actions that conform with those of their neighbors. This preference for conformity interacts with the agents' beliefs about which of two (or more) possible actions yields the better outcome. We find a range of possible outcomes, including stable polarization in belief and action. The model results are sensitive to network structure. In general, though, conformity has a negative effect on a community's ability to reach accurate consensus about the world.