Learning Machines: Industrial-Academic Collaboration in Russian Data Science

Ian Lowrie

This project is based upon twelve months of ethnographic research in Moscow at the National Research University – Higher School of Economics and the web-services firm Yandex, sometimes called the “Russian Google,” both leading institutions of Russian data science. It focuses on elite efforts to restructure postsecondary education in order to build a more robust Russian information economy. By investigating the novel forms of training and research emerging at key hybrid industrial-academic institutions such as, this research provides critical and timely insight into the rapidly changing organization of computer science and applied mathematics pedagogy during a time of heightened volatility within the Russian science and education system more generally. Drawing upon grounded theory, it employs qualitative data analysis techniques to code and interpret seventy-five semi-structured interviews, which are complemented by data drawn from participant observation in classrooms, academic seminars, and industrial educational programs. In so doing, it promises to broaden the existing literature on education and innovation in the computer sciences beyond inherited descriptions based primarily on studies of Silicon Valley and the American research university. In addition to providing useful comparative insight into the concrete dynamics of education in the data sciences, this dissertation promises to substantially complicate our inherited understandings of how university-industry-state relations drive developments in the global information economy. Most generally, it aims to understand the processes whereby students and trainees learn to inhabit and perform algorithmic rationality, and how this rationality operates within the extended sociotechnical systems subtending contemporary forms of capitalism.

About Ian Lowrie

Ian Lowrie is a doctoral candidate in anthropology at Rice University, and holds a bachelor’s degree in anthropology from Reed College. His current research focuses on education, work, and rationality in the Russian data sciences. This fieldwork for this research was supported by the Wenner-Gren Foundation, American Councils for International Education, and the Rice Social Science Research Institute. More generally, he is interested in how human and nonhuman cognition work together to build the sociotechnical infrastructures of our contemporary knowledge economy. As he works towards completing the dissertation, he has begun a new project studying the intersections of data science and neuroscience. Ian is the book review editor for the journal Magic, Ritual, and Witchcraft, and an associate editor at the CASTAC Blog.