Hi, that’s me.

I study human-computer interaction - more precisely, I study how people relate to individual algorithmic systems and with algorithmically mediated social ecologies by adapting theoretical lenses and frameworks originating in the social sciences to understand these phenomena.

That’s a little dense. Let me try again…


I mostly think about problems situated in technology - how gig work disempowers workers, or why AI makes so many frustrating errors. I try to figure out ways that we can think about those problems essentially as social relationships between people and systems that do things people used to do. Most of the time I do this by adapting and extending theories from other fields - fields that mostly study relationships between people - to help frame how we make sense of these problems.

Coming up with robust framings this way does a couple of useful things. First, it makes explicit that these “technical” problems are actually social problems, and that we should study them with commensurate depth, care, and attention to the histories and lived experiences of people. Second, it gives us a rich vocabulary and body of scholarship to inform how we can make sense of these complex technical structures as cultural structures.

I think that those two things together make it harder for advocates of complex technologies like AI to argue that they (or other technical experts) are the only ones equipped to discuss these things. I ultimately hope to advance a narrative that represents these technologies as artifacts of culture, and as things that we all experience and therefore have status to think about and critique.


I’m a PhD student in Computer Science at Stanford, currently on leave. Michael Bernstein is my advisor.

I earned my B.A. in Anthropology & B.S. in Informatics, specializing in human-computer interaction, both from UC Irvine in 2014. I wrote an honors thesis on the culture of Quantified Self while I worked under Tom Boellstorff.

If this isn’t enough info, click on some links floating around this text in various places (determined mostly by the size of your browser).