I have served as instructor-of-record for two advanced undergraduate seminars at UC Berkeley that introduce students to the sociological study of technology and surveillance. See below for course descriptions. I have also been a graduate student instructor for courses in Classical and Contemporary Social Theory, Economic Sociology, and Engineering Ethics.
I am qualified to teach courses in computational social science and quantitative research methods, social demography and stratification, law and society, crime and punishment, and comparative-historical sociology.
Algorithms in Society
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.
Surveillance Cultures
The collection of personalized and statistical data is a widely used technique of state power, a prerequisite of the digital economy, and a byproduct of everyday interactions on online platforms. Through the reading of theoretical texts and empirical case studies and independent student research, the course develops a sociological perspective on what can collectively be called “surveillance cultures”. In so doing, we complicate four common claims: (1) surveillance is a distinctly (post-)modern and digitally enabled form of social control; (2) the collection of personal and statistical data has become indiscriminate and ubiquitous; (3) being watched is now a widely accepted way of life that elicits little resistance; and (4) being visible is a form of imprisonment that undermines personal freedom. Each of these claims captures something important about surveillance in the contemporary world — but each can also simplify to the point of distortion. Through critical and empirical examination, the course links the study of surveillance to questions of state power, contemporary capitalism, racial and social inequality, and the constitution of the socially situated self.