I study the effects of quantification on social policy. Currently, I am Postdoctoral Fellow in the Ethics of Big Data and AI in Healthcare at the NYU Department of Population Health's Division of Medical Ethics. I previously received my Ph.D. in Sociology from UCLA, where I also taught courses at the Institute for Society and Genetics and served as an Editorial Assistant for the journal Social Science & Medicine.
My current work is divided into three primary areas. My book project, Expertise and the Enigma of Policy Influence, rethinks and reframes the enormously consequential economics of U.S. social policy as a predominantly reactive enterprise, in which existing social programs and data sources constrain economists' capacity to effect policy change. I find that when it comes to topics like healthcare or education, economics is not an unchanging monolith in policy settings, and that the further one gets from the field’s disciplinary core, economic theory is less essential to the work of economists than a common methodological language (which is not always legible to policy audiences). In the wake of the COVID-19 pandemic, this analytical approach has found economists joining the fray of experts investigating issues such as 'health equity,' a state of affairs which contrasts sharply with popular critiques of the field. Research related to this project has been published in Theory and Society, the Journal of Cultural Economy, Science, Technology, & Human Values, the Journal of Education Policy, and Economy and Society.
A second project, Polygenic Prediction, turns a sociological lens on the production of new quantitative indicators in the field of behavior genetics that are beset by a host of uncertainties. While so-called polygenic scores have received critical attention primarily for their potentially eugenic implications in policy settings, this project investigates how uncertainty is inherent to research in this domain beginning with the collection of biobank data that disproportionately feature people with European ancestry, resulting in reference 'populations' that are not representative. My research on polygenic scores is a collaboration with UCLA's Aaron Panofsky and Nanibaa' Garrison that aims to empower clinicians, policymakers, and the public so that when polygenic prediction is applied, it occurs as ethically and equitably as possible.
Finally, with Kellie Owens at NYU, I am embarking on several new research projects related to the ethical and social implications of health information technologies, genomics, and AI. Overall, at the heart of my research is an abiding concern with an updated version of a classic sociological question: is the purpose of quantitative knowledge to understand the world, or to change it?