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 history. In the contemporary world, such classification often relies on technologies that process large amounts of behavioral, economic, or demographic data to compute credit scores, calculate recidivism risk, determine eligibility for welfare services, allocate police resources, curate news, personalize shopping recommendations and prices, or select matches on dating websites. Those algorithms have social histories and tangible consequences in the world. They can be studied with the tools of sociology; and studying them sociologically can illuminate the intricate links between technology and society.
Surveillance Societies
Methods of Inquiry
The collection of personalized and statistical data is central to the exercise of state power and the functioning of the digital economy. It is also a de-facto reality of life, as our everyday interactions with online platforms and digital tools leave behind extensive and highly personal data imprints. In this course, we will develop an understanding of what can collectively be called “surveillance societies” by interrogating five core claims: (1) that surveillance is a distinct feature of (post-)modern and digitally native societies; (2) that the collection of personal and statistical data has become indiscriminate, ubiquitous, and inescapable; (3) that informational visibility undermines personal freedom; (4) that such visibility is nonetheless the price of convenience and efficiency; and (5) that being watched has therefore evolved into a widely accepted way of life that elicits little resistance.
What does it mean do to research that is social-scientific? This course introduces students to the epistemic logics and applied methodologies that underpin rigorous sociological research. You will learn about things like: designing research projects; collecting empirical data through qualitative and quantitative methods; evaluating the quality and (internal and external) validity of such data; reasoning from evidence; combining data with theory; and considering the ethical considerations of research that involves living, breathing human subjects.