Credentials: Affiliate Professor (University of Wisconsin-Madison, PhD 2018)
Position title: Information/Data Ethics, Fair Machine Learning, Epistemology
Pronouns: Assistant Professor (The Information School)
4252 Helen C. White Hall
Prof. Castro’s research interests are in information/data ethics, fair machine learning, and epistemology. He is interested in ethical questions raised by the attention economy and algorithmic bias. He is also interested in working with practitioners. For instance, he is working with a group of data scientists and addiction researchers on a project, funded by the AIM-AHEAD Consortium Development Projects to Advance Health Equity, that seeks to understand algorithmic bias in opioid use disorder treatment.
His recent publications include Kantian Ethics and the Attention Economy (with Tim Aylsworth, Palgrave Macmillan 2024), “The Fair Chances in Algorithmic Fairness: A Response to Holm” (with Michele Loi, Res Publica 2023), “Egalitarian Machine Learning” (with David O’Brien and Ben Schwan, Res Publica 2023), “Just Machines” (Public Affairs Quarterly 2022), “On the Duty to be an Attention Ecologist” (with Tim Aylsworth, Philosophy & Technology 2022), Algorithms & Autonomy (with Alan Rubel and Adam Pham, Cambridge University Press 2021), “Is there a Duty to Be a Digital Minimalist?” (with Tim Aylsworth, Journal of Applied Philosophy 2021), “Is the Attention Economy Noxious?” (with Adam Pham, Philosophers’ Imprint 2020), and “What’s Wrong with Machine Bias?” (Ergo 2019).