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Generative Artificial Intelligence in Social Research and Teaching offers a timely and critical examination of how GenAI is reshaping social science research, teaching and learning. Bringing together 14 contributors from five continents, the volume moves beyond both technological hype and pessimistic doom to provide nuanced empirical and theoretical analysis of GenAI’s uses, risks and possibilities across diverse institutional, cultural and geographic contexts.
Drawing on original surveys, focus group research and interdisciplinary perspectives from sociology, Science and Technology Studies, education research, public policy, critical theory and futures research, chapters explore how GenAI is being adopted across different phases of the research process and in the teaching of social sciences. It considers questions of scientific integrity, inequality, authorship, learning, institutional governance and the changing competencies required of researchers, educators and students.
At a moment when GenAI adoption is rapidly outpacing policy, pedagogy and scholarly reflection, Generative Artificial Intelligence in Social Research and Teaching provides an essential foundation for informed debate. It is a valuable resource for researchers, postgraduate students, educators, research leaders, university administrators and policy professionals seeking to understand and critically shape the role of GenAI in social research and higher education.
Chapter 1. Generative Artificial Intelligence (AI) in Social Research and Teaching: An Introduction; Markus S. Schulz and Inga Gaižauskaitė
Markus S. Schulz is researcher at Max Weber Center for Advanced Cultural and Social Studies and New School for Social Research.
Inga Gaižauskaitė is a sociologist, affiliated with Institute of Sociology at the Lithuanian Centre for Social Sciences and V. Kavolis Transdisciplinary Research Institute at the Vytautas Magnus University, Lithuania.