Courses
Technology, AI, and Ethics in Policy and Public Administration
This course examines the transformation of government operations through emerging technologies like artificial intelligence and automated decision systems. Students analyze governance strategies, policies, and administrative procedures to promote responsible technology use in government. Through case studies and research projects, participants identify best practices for implementing and auditing AI systems in public sector contexts.
Quantitative Methods in Anthropology
This course provides an introduction to the broad statistical methods used throughout the 4-fields of Anthropology. It covers elementary probability theory, basic concepts of statistical inference, and study design. The course will motivate statistical methods through data analysis and visualization. It is designed for students who intend to focus on an anthropological discipline. It would also benefit a variety of students interested in 1) quantitative science literacy and planning for graduate work, 2) joining the workforce and becoming part of the educated citizenry.
GIS and Geospatial Methods for Social Scientists
This course will introduce you to the skills of spatial thinking, basic functions of Geographic Information Systems (GIS), and spatial research methods that are relevant to humanities, social science, and related fields. The course will start with an introduction to basic GIS concepts and technology, then move onto GIS applications in the research process, including research design, data collection, management, visualization, and basic spatial analysis techniques. Practical work will be completed using ArcGIS Pro software.
Local to Global Governance of Data, AI, and Emerging Technology
This graduate-level course introduces technology governance problems related to data and AI systems in a global context. Students explore technology actors and processes crucial to global policy. The course covers an interdisciplinary body of literature from political science, history, law, policy, economics, and sociology, prioritizing in-depth reading of books on technology and global governance themes.
Introduction to Computational Linguistics
This course introduces computational linguistics, covering both theoretical and engineering topics. Students gain an understanding of the essential characteristics and differences between computational linguistics, natural language processing, machine learning, and artificial intelligence. No previous programming background is required.
AI and Technology in State and Local Government
This course provides an in-depth overview of research on artificial intelligence, technology policy, and state and local government. Students gain a solid understanding of relevant literature in political science, public policy, and public administration. The course emphasizes developing research skills and applying course material to novel research projects based on student interests.
Language Learning and AI
This practical, introductory course familiarizes students with basic concepts and computational methods used in language learning. It emphasizes the use of AI systems in answering research questions with educational, clinical, and engineering implications. Students learn how AI can assist in second language learning, help learners with language disorders, and inform the teaching process.
Philosophical Fundamentals of Machine Learning
This applied survey course explores current machine learning methods and their philosophical applications. Students gain familiarity with modern machine learning techniques, including mathematical fundamentals, decision theory, and various learning models. The course also delves into the philosophical implications of machine learning in fields such as philosophy of science, mind, politics, and ethics.
History of Artificial Intelligence: Minds & Machines
This course examines the transnational historical development of machine learning and artificial intelligence from the early 1800s to the 2020s. Students explore how problem-framing strategies in these fields shaped conceptions of justice, opportunity, fairness, democracy, diversity, and other social concepts. The course emphasizes the material infrastructures, political contingencies, and technical practices that influenced AI's development.