Idealizations and Understanding:
Much Ado About Nothing?
Forthcoming, Australasian Journal of Philosophy
with Kareem Khalifa
Can Real Social Epistemic Networks
Deliver the Wisdom of Crowds?
2019. Oxford Studies in Experimental Philosophy.
First author, with Sondag, M., Rutter, I., Meulemans, W., Cunningham, S.,
Speckmann, B., & Alfano M.
Second author, with Nava Tintarev, Dror Guldin, Sihang Qiu, and Daan Odjik
My research focuses on our practices of giving and receiving explanations or information. This includes the epistemology and structure of explanations and information sharing.
Are there ways of spreading information that promotes epistemic goods or epistemic ills? In what way does society and political beliefs impact information sharing? What is the social function of understanding?
How can falsehoods or idealizations lead to epistemic goods like understanding? At what point do scientific or social-scientific idealizations or abstractions lose their causal tether? What does this say about the sort of understanding we gain from these explanations?
(Drafts available upon request)
Epistemic Value and Understanding
I argue that the value of understanding lies in its social function as a marker of epistemic authority.
Understanding and Grasping
I survey the extent to which a theory of grasping has been put forward in the understanding literature and make progress toward building such a theory.
Causal Explanation and Universality
In this paper I argue that renormalization group explanations of critical phenomena are causal explanations.
Machine Learning and Understanding
In this paper, I explore what sort of understanding of phenomena we can receive from opaque machine learning models
Formal Network Epistemology
Working with the DHEPCAT team at TU Delft and TU/e, we argue in favor of a formal graph-theoretical approach to testimonial networks and apply this approach to discussions of vaccine safety on Twitter.
2018 Oct: "Social Network-Epistemology"
IEEE eScience; Amsterdam
2018 Nov: Commentator on "Diversity-Aware
Reccomender Systems" by Nava Tintarev
ZiF Bielefeld University; Germany
Copyright Emily Sullivan. All rights reserved.