Fiscal Year 2023-2024
Graduate-level courses
Thomas Wood. "Applied Political Science Computing"
The proposed class, a non-mandatory complement to the existing graduate methods sequence, will meet these lacunae. The class will cover the following topics: (1) The tidyverse tools for data analysis; (2) functional programming, so that students don’t write repetitive, bug-prone code; (3) web scraping and accessing APIs (an especially relevant technology, given the number of language models with accessible APIs)” for punctuation and formatting2; (3) web scraping and accessing APIs (an especially relevant technology, given the number of language models with accessible APIs); (4) an introduction to databases and SQL, and: (5) statistical graphics for publication, and (6) integrating novel statistical and computational techniques into an existing syntactical approach.Erin Lin. "Bringing AI Tools to Qualitative Methods"
The goal of this graduate seminar is to explore when qualitative methods are appropriate for a research question and how to competently engage in such research. We will use A.I. tools to automate certain archival tasks, process ethnographic experiences, and test-run interview guides (prior to taking them to the field). Students will apply multiple A.I. tools within this practicum. In partnership with the Ohio State University Archives, Ohio Public Policy Archives, and the Byrd Polar and Climate Research Center Archival Program, students will digitize archival documents to create data sets that we feed into a deep learning tool, training it to spot key words, phrases, and images. In the second half of the semester, students will invest 3-4 hours a week tracing down interviewees, spending time at field sites, doing interviews, and writing up field notes. We will use chatbots to pilot their semi-structured interview guides (preparing students for an array of responses that may require them to be flexible in how they order and ask their questions).
Undergraduate-level courses
Zuheir Desai. "Technology in Politics: Efficiency, Accountability, and Fairness."
This course is aimed at students that are broadly interested in the nexus of Economics, Politics, and Technology from both a positive and a normative perspective. The aim is to attract students from multiple majors, including, but not limited to, Computer Science, Economics, Politics Philosophy & Economics (PPE), and Political Science. A major focus will be on evaluating whether and when simultaneously pursuing efficiency, accountability, and fairness goals results in tensions. For example,(when) do we need to sacrifice accountability and/or fairness for efficiency?
Jan Pierskalla. "Big Data, AI, and Political Control."
Revolutions in information technology have made data about our lives vastly more available. What are the implications of this change for governance? States routinely collect a lot of information about their citizens and make use of it for political ends. From birth registries, censuses, land cadasters, voter rolls, to modern biometric databases, predictive policing, AI and
the monitoring of social media, states rely on a varied array of information collection and analysis tools. What determines the kind of information states collect, how they collect it, and how it is used to make policy decisions? Do these tools empower dictators and amplify political control, or they democratize power and strengthen citizens? Who are the winners and losers when it comes to changes in the realm of information technology? The course unpacks the various ways in which states collect information about their citizens, use this information in their decision-making, and associated political conflicts. We will focus on how different types of political regimes—democracies and autocracies—make different choices about how citizen information is collected, used, and how civil society responds.
Haifeng Huang. "AI and the Politics of Information."
This undergraduate course will explore how AI and algorithmic based technologies affect the flow of political information and the formation of public opinion. Topics will include information aggregation and knowledge generation, misinformation and false news, correcting misinformation, propaganda, censorship, international influence and public diplomacy, electoral campaigns, social robots and social media, and so on. It will examine both how various actors and entities can use and have used AI technologies to generate and shape political messaging, such messaging’s effects on public opinion and other social outcomes, and how such activities can be detected and sometimes countered.