I have served as a Graduate Student Instructor at Berkeley for 4+ semesters, during which I taught social theory (with Michael Burawoy and Christopher Muller) and economic sociology (with Neil Fligstein) and won two university-wide teaching awards: the Outstanding GSI Award and the Teaching Effectiveness Award. In addition, I have also designed and twice taught my own research seminar. See below for a summary of the course.

Algorithms in Society (Fall 2018/ Fall 2019)

Sociologists frequently study how people and things are sorted into different categories according to race, gender, income, education, political allegiance, or criminal records. In the contemporary world, such classification often relies on technologies that process large amounts of behavioral, economic, or demographic data to determine credit scores, calculate the recidivism risk of criminal defendants, structure access to welfare services, allocate police officers to urban neighborhoods, write and curate news, personalize shopping recommendations, determine prices and driving directions, or select matches on dating websites. Each of us is examined by countless algorithms every day, often without realizing it.

Despite their prevalence and significance, algorithmic technologies are commonly relegated to the domain of computer science and regarded as inscrutable pieces of software. Yet they are not just complex technological objects: Algorithms have social histories and tangible consequences in the world. They affect the structure of the social order, facilitate market exchanges, influence politics, and shape our sense of self. They can be studied with the tools of sociology; and studying them sociologically can illuminate the intricate links between technology and society.

In this course, we will (1) explore the links between technology and familiar sociological topics like power, race, gender, and capitalism and (2) familiarize ourselves with sociological theories that aim to make sense of such links. The course does not assume any specific technical knowledge.