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I'm a postdoctoral associate in the Department of Science & Technology Studies at Cornell University, where I focused on research and teaching development related to the intersection of new technologies, work practices, expertise, and society. As an Engaged Cornell Faculty Fellow, I am currently designing and launching, together with Professors Stephen Hilgartner and Malte Ziewitz, a new project-based undergraduate course, the Data Science & Society Lab at Cornell.

 

My broader research interests include emerging data work practices and the invisible labor of the data society; standards and standardization; team dynamics and group decision-making; the changing landscape of human expertise in relation to machine learning and artificial intelligence; and how all of the above fit into explanations, and predictions, of technology's tendency to reproduce of existing social inequalities and sometimes produce new ones.

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One of the primary motivations of my research agenda is my belief that productive grappling with the ethics of machine learning technologies and artificial intelligence depends on our empirical understanding of the social processes that underly them in a variety of institutional contexts. My work is an ongoing effort to demonstrate that, although data analytic technologies cannot be separated from their social and material contexts, we can understand much of how they are situated in these contexts by examining how organizations and people work with and around them.