Conor Mayo-Wilson University of Washington
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  • Faculty, University of Washington
  • PhD, Carnegie Mellon University, 2012.

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About me
I am currently an assistant professor at the University of Washington in Seattle. My philosophical interests are rather broad, spanning much of epistemology (esp. formal and social), philosophy of science, logic, and philosophy of mathematics. For copies of working papers, my teaching materials, and more, see my website:
My works
11 found

  1. Scientific Collaboration and Collective Knowledge.T. Boyer, C. Mayo-Wilson & M. Weisberg (eds.) - forthcoming
  2. Scientific Collaboration and Collective Knowledge.Thomas Boyer-Kassem, Conor Mayo-Wilson & Michael Weisberg (eds.) - forthcoming - Oxford University Press.
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  3.  63
    Structural Chaos.Conor Mayo-Wilson - 2015 - Philosophy of Science 82 (5):1236-1247.
    A dynamical system is called chaotic if small changes to its initial conditions can create large changes in its behavior. By analogy, we call a dynamical system structurally chaotic if small changes to the equations describing the evolution of the system produce large changes in its behavior. Although there are many definitions of “chaos,” there are few mathematically precise candidate definitions of “structural chaos.” I propose a definition, and I explain two new theorems that show that a set of models (...)
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    Reliability of Testimonial Norms in Scientific Communities.Conor Mayo-Wilson - 2014 - Synthese 191 (1):55-78.
    Several current debates in the epistemology of testimony are implicitly motivated by concerns about the reliability of rules for changing one’s beliefs in light of others’ claims. Call such rules testimonial norms (tns). To date, epistemologists have neither (i) characterized those features of communities that influence the reliability of tns, nor (ii) evaluated the reliability of tns as those features vary. These are the aims of this paper. I focus on scientific communities, where the transmission of highly specialized information is (...)
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    The Limits of Piecemeal Causal Inference.Conor Mayo-Wilson - 2014 - British Journal for the Philosophy of Science 65 (2):213-249.
    In medicine and the social sciences, researchers must frequently integrate the findings of many observational studies, which measure overlapping collections of variables. For instance, learning how to prevent obesity requires combining studies that investigate obesity and diet with others that investigate obesity and exercise. Recently developed causal discovery algorithms provide techniques for integrating many studies, but little is known about what can be learned from such algorithms. This article argues that there are causal facts that one could learn by conducting (...)
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  6. Wisdom of the Crowds Vs. Groupthink: Learning in Groups and in Isolation.Conor Mayo-Wilson, Kevin Zollman & David Danks - 2013 - International Journal of Game Theory 42 (3):695-723.
    We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the social context (if any) (...)
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  7.  80
    Russell on Logicism and Coherence.Conor Mayo-Wilson - 2011 - Journal of Bertrand Russell Studies 31 (1).
    According to Quine, Charles Parsons, Mark Steiner, and others, Russell's logicist project is important because, if successful, it would show that mathematical theorems possess desirable epistemic properties often attributed to logical theorems, such as a prioricity, necessity, and certainty. Unfortunately, Russell never attributed such importance to logicism, and such a thesis contradicts Russell's explicitly stated views on the relationship between logic and mathematics. This raises the question: what did Russell understand to be the philosophical importance of logicism? Building on recent (...)
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  8.  95
    The Problem of Piecemeal Induction.Conor Mayo-Wilson - 2011 - Philosophy of Science 78 (5):864-874.
    It is common to assume that the problem of induction arises only because of small sample sizes or unreliable data. In this paper, I argue that the piecemeal collection of data can also lead to underdetermination of theories by evidence, even if arbitrarily large amounts of completely reliable experimental and observational data are collected. Specifically, I focus on the construction of causal theories from the results of many studies (perhaps hundreds), including randomized controlled trials and observational studies, where the studies (...)
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  9. The Independence Thesis: When Individual and Social Epistemology Diverge.Conor Mayo-Wilson, Kevin J. S. Zollman & David Danks - 2011 - Philosophy of Science 78 (4):653-677.
    In the latter half of the twentieth century, philosophers of science have argued (implicitly and explicitly) that epistemically rational individuals might compose epistemically irrational groups and that, conversely, epistemically rational groups might be composed of epistemically irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they together imply that methodological prescriptions for scientific communities and those for individual scientists might be logically independent of one another. We develop a formal model of scientific inquiry, define four (...)
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  10.  35
    Ockham Efficiency Theorem for Stochastic Empirical Methods.Kevin T. Kelly & Conor Mayo-Wilson - 2010 - Journal of Philosophical Logic 39 (6):679-712.
    Ockham’s razor is the principle that, all other things being equal, scientists ought to prefer simpler theories. In recent years, philosophers have argued that simpler theories make better predictions, possess theoretical virtues like explanatory power, and have other pragmatic virtues like computational tractability. However, such arguments fail to explain how and why a preference for simplicity can help one find true theories in scientific inquiry, unless one already assumes that the truth is simple. One new solution to that problem is (...)
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  11. Causal Conclusions That Flip Repeatedly and Their Justification.Kevin T. Kelly & Conor Mayo-Wilson - unknown
    Over the past two decades, several consistent procedures have been designed to infer causal conclusions from observational data. We prove that if the true causal network might be an arbitrary, linear Gaussian network or a discrete Bayes network, then every unambiguous causal conclusion produced by a consistent method from non-experimental data is subject to reversal as the sample size increases any finite number of times. That result, called the causal flipping theorem, extends prior results to the effect that causal discovery (...)
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