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Why Bayesian Agents Polarize

In Fernando Broncano-Berrocal & Adam Carter (eds.), The Epistemology of Group Disagreement. Routledge (2020)

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  1. Rational Irrationality: Modeling Climate Change Belief Polarization Using Bayesian Networks.John Cook & Stephan Lewandowsky - 2016 - Topics in Cognitive Science 8 (1):160-179.
    Belief polarization is said to occur when two people respond to the same evidence by updating their beliefs in opposite directions. This response is considered to be “irrational” because it involves contrary updating, a form of belief updating that appears to violate normatively optimal responding, as for example dictated by Bayes' theorem. In light of much evidence that people are capable of normatively optimal behavior, belief polarization presents a puzzling exception. We show that Bayesian networks, or Bayes nets, can simulate (...)
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  • Knowledge in a social world.Alvin I. Goldman - 1991 - New York: Oxford University Press.
    Knowledge in a Social World offers a philosophy for the information age. Alvin Goldman explores new frontiers by creating a thoroughgoing social epistemology, moving beyond the traditional focus on solitary knowers. Against the tides of postmodernism and social constructionism Goldman defends the integrity of truth and shows how to promote it by well-designed forms of social interaction. From science to education, from law to democracy, he shows why and how public institutions should seek knowledge-enhancing practices. The result is a bold, (...)
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  • A Bayesian Simulation Model of Group Deliberation and Polarization.Erik J. Olsson - 2013 - Springer.
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  • Do computer simulations support the Argument from Disagreement?Aron Vallinder & Erik J. Olsson - 2013 - Synthese 190 (8):1437-1454.
    According to the Argument from Disagreement (AD) widespread and persistent disagreement on ethical issues indicates that our moral opinions are not influenced by moral facts, either because there are no such facts or because there are such facts but they fail to influence our moral opinions. In an innovative paper, Gustafsson and Peterson (Synthese, published online 16 October, 2010) study the argument by means of computer simulation of opinion dynamics, relying on the well-known model of Hegselmann and Krause (J Artif (...)
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  • How Good Is Your Evidence and How Would You Know?Ulrike Hahn, Christoph Merdes & Momme von Sydow - 2018 - Topics in Cognitive Science 10 (4):660-678.
    This paper examines the basic question of how we can come to form accurate beliefs about the world when we do not fully know how good or bad our evidence is. Here, we show, using simulations with otherwise optimal agents, the cost of misjudging the quality of our evidence. We compare different strategies for correctly estimating that quality, such as outcome‐ and expectation‐based updating. We also identify conditions under which misjudgment of evidence quality can nevertheless lead to accurate beliefs, as (...)
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  • Publish Late, Publish Rarely! : Network Density and Group Performance in Scientific Communication.Staffan Angere & Erik J. Olsson - 2017 - In Thomas Boyer-Kassem, Conor Mayo-Wilson & Michael Weisberg (eds.), Scientific Collaboration and Collective Knowledge. New York, USA: Oxford University Press.
    Research programs regularly compete to achieve the same goal, such as the discovery of the structure of DNA or the construction of a TEA laser. The more the competing programs share information, the faster the goal is likely to be reached, to society’s benefit. But the “priority rule”-the scientific norm according to which the first program to reach the goal in question must receive all the credit for the achievement-provides a powerful disincentive for programs to share information. How, then, is (...)
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  • A diachronic perspective on peer disagreement in veritistic social epistemology.Erik J. Olsson - 2018 - Synthese 197 (10):1-19.
    The main issue in the epistemology of peer disagreement is whether known disagreement among those who are in symmetrical epistemic positions undermines the rationality of their maintaining their respective views. Douven and Kelp have argued convincingly that this problem is best understood as being about how to respond to peer disagreement repeatedly over time, and that this diachronic issue can be best approached through computer simulation. However, Douven and Kelp’s favored simulation framework cannot naturally handle Christensen’s famous Mental Math example. (...)
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  • Inquiry and deliberation in judicial systems : the problem of jury size.Staffan Angere, Erik J. Olsson & Emmanuel Genot - unknown
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