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[DRAFT] Course Catalog 2026-2027 [ARCHIVED CATALOG]
Critical AI Studies Minor
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The minor consists of a minimum of 5 full courses (or the equivalent) and 1 culminating reflection.
Note: Students must earn minimum grades of C- or P for all courses that apply toward the minor.
Critical AI studies is an emerging interdisciplinary field that draws from the critical methods of the humanities and social sciences but orients toward understanding and addressing the impact of AI technologies, including but not limited to generative AI, supervised and reinforcement machine learning, and autonomous decision making. As new tools, capabilities, and claims about AI emerge at an increasing pace, it is imperative that students be equipped with the ability to critically evaluate AI tools: their usefulness, appropriateness, ethical implications, and limitations within the context of the societies and power structures in which they operate. A liberal arts education—drawing on the humanities, social and natural sciences, and the arts—uniquely cultivates students’ ability to do this important work.
Within the interdisciplinary critical AI studies minor, students examine how AI poses important challenges for society, as well as how some AI technologies can be made to serve the public interest and used to address society’s important problems. The goal is to prepare students for thoughtful leadership in a world in which AI is increasingly prevalent.
Students pursuing the critical AI studies minor address four core questions:
- What is meant by the term “artificial intelligence”? How is this similar to and different from our understanding of human intelligence and creativity, and how do AI systems actually function?
- How have social and historical factors shaped the underlying theories, concepts, and technologies that support AI systems, and how do these influences affect current sociotechnical challenges?
- How is AI being used across domains, and how should it be?
- What are the cultural, environmental, political, economic, ethical, and labor effects of AI?
 Visit the minor’s web page for more information.
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Learning Goals
Completing the critical AI studies minor will lead students to: - Develop technical knowledge of the theories and mechanisms of artificial intelligence;
- Gain insight into the relationship between technology and the social and historical context in which it has been developed and applied;
- Explore the genealogy of concepts such as intelligence, agency, the mind, the self, etc. that have traditionally been defined and employed in the context of AI;
- Acquire sufficient technical proficiency to evaluate and use AI as a tool, learning how to assess the strengths and weaknesses of different frameworks and capabilities with respect to different types of applications;
- Critically evaluate the rhetorical strategies that dominate the public and commercial discourse surrounding AI, including the anthropomorphizing tendencies and utopian/dystopian hype;
- Extend analysis of AI technologies beyond the individual point of consumption to the global chains of resources, labor, and domination from which it emerges and in which it is deployed;
- Understand the potential cultural, environmental, political, economic, and labor costs associated with the creation, use, and application of AI, as well as how and when AI tools and frameworks can be ethically applied to benefit society (and when they cannot);
- Obtain requisite intellectual background for productive interdisciplinary collaboration with peers in an array of fields across the arts, sciences, and humanities; and
- Enhance their skills in argumentation and critical analysis, demonstrated through effective oral and written communication.
Declaring the Minor
Students wishing to complete the critical AI studies minor should consult with the minor chair and complete the interdivisional or Arts and Sciences minor declaration/change form. The form requires the signature of the minor chair. Chair
Adam D. Eck, David H. and Margaret W. Barker Associate Professor of Computer Science and Business Curriculum Overview
- The required courses in technical foundations and methods of critique aim to provide students with an understanding of the field of critical AI studies and ensure that students are equipped with fundamental knowledge to understand and critique the technology.
- CAIS 100 bridges STEM and humanities/humanistic social sciences, making sure that all students, regardless of their major, have the necessary tools to understand the nature and social implications of AI technologies.
- With the distribution elective courses, students broaden their knowledge through greater understanding of the history of science and technology and the mechanism for decision making, opportunities to apply AI, or exploring societal impacts.
Detailed Minor Requirements
Critical AI Studies Minor Course Lists
Technical Foundations Courses
Return to the summary of requirements. Technical foundations courses provide students with the technical background necessary to study how AI is constructed and functions as a computational system. Note: The required technical foundations course must be taken before CAIS 100. Methods of Critique Courses
Return to the summary of requirements. Methods of critique courses expose students to a range of critical methodologies, which aim to illuminate the shrouded epistemological, ethical, and political commitments underlying seemingly neutral and self-evident concepts and social forms such as intelligence and technology. By equipping students with a “hermeneutics of suspicion,” these courses will foster a critical engagement with the pressing questions of power, ethics, and human self-estrangement lurking behind AI systems in the age of techno-scientific capital. Distribution Elective Courses
Return to the summary of requirements. The two full distribution elective courses - must come from different home departments and
- must be taken in two different areas.
Applications of AI Courses
Return to the top of the list of distribution elective courses. Applications of AI courses provide additional depth in exploring how AI has been applied across disciplines and is currently being put into practice. Students practice developing algorithmic systems or solutions for intellectual tasks and critically evaluate the quality and usefulness of their outcomes. Note: Senior capstones and honors projects may fulfill this requirement with permission of the minor chair. Decision Making and Learning Courses
Return to the top of the list of distribution elective courses. Decision making and learning courses provide additional depth in studying different mechanisms and approaches for decision making. Students explore what it means to reason and learn, supporting their development of comparing and contrasting human reasoning with decision making in machines. Epistemology and History of Science Courses
Return to the top of the list of distribution elective courses. Epistemology and history of science courses provide context of the history of technology and knowledge production, as well as how they have been applied historically to societal challenges. This context supports students in understanding how we’ve arrived at the present moment and how the future might progress, and in thinking about the societal impacts of AI. Societal Impacts Courses
Return to the top of the list of distribution elective courses. Societal impacts courses provide disciplinary frameworks for theorizing societal impact as well as investigate the cultural, environmental, political, economic, ethical, and labor effects of AI. Students study theories of the societal impacts of AI systems, illustrated through case studies of historical and/or potential applications. |
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