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This presentation introduces “Classics Meet AI,” an innovative, multi stage project designed to help students apply classical sociological theory to the rapidly evolving landscape of artificial intelligence. The project bridges foundational works of Marx, Weber, Durkheim, and other theorists with contemporary questions about automation, rationalization, and digital inequality. Its core pedagogical objective is to cultivate critical AI literacy while deepening students’ theoretical fluency and sociological imagination.
The assignment guides students through a structured process: topic selection, manual literature review, and use of research AI tools, e.g. SciSpace, Elicit, and ResearchRabbit. Students then compare and critically evaluate the human driven and AI generated literature reviews. This comparison becomes the foundation for applying classical theory to AI technologies: Marx’s concepts of alienation, surplus value, and ideology; Durkheim’s ideas on social facts, solidarity, and anomie; and Weber’s analyses of rationalization, bureaucracy, and authority. These theoretical frames enable students to interrogate how AI reshapes labor, knowledge production, social cohesion, and power structures in contemporary society.
The presentation will demonstrate how this assignment fosters analytical depth, reflexive thinking, and responsible use of AI in sociological research. Attendees will gain access to assignment materials, scaffolding strategies, assessment rubrics, and examples of student insights. The session will be useful for instructors seeking to 1) integrate AI into sociology classrooms without losing theoretical rigor, 2) teach students to evaluate AI tools critically rather than passively adopt them, and 3) connect classical theory to issues students find immediate and relevant. This assignment offers a replicable model for teaching sociological theory in the age of emerging technologies while supporting the discipline’s broader goals of critical inquiry and engaged learning.