Generative Artificial Intelligence in Social Research and Teaching
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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
- Chapter 2. Artificial Intelligence in Research and Higher Education: Implications for Future Graduates; Lutfun Nahar Lata
- Chapter 3. The Great Amplifier: Research Integrity in Human-AI Co-Creation; Jens Peter Andersen
- Chapter 4. Use and Assessment of Generative AI in the Academic Community of the Latin American Faculty of Social Sciences, Mexico; Oscar Fontanelli, Markus S. Schulz, Jackeline Alba Udave, Danay Quintana Nedelcu, Ligia Tavera Fenollosa, Martín de los Heros Rondenil, and Mauricio I. Dussauge Laguna
- Chapter 5. How ChatGPT Is Just a New Tool for Old Practices: The Democratization of Learning and Cheating Practices among University Students through AI Chatbots; Michael Grothe-Hammer and Svenja Hammer
- Chapter 6. Generative AI in Graduate Education: How Cognitive Mediation Reshapes Learning, Inequality, and Teaching of Quantitative Methods in the Social Sciences; Ligia Tavera Fenollosa, Markus S. Schulz, Danay Quintana Nedelcu, Oscar Fontanelli, and Mauricio I. Dussauge Laguna
- Chapter 7. Educational Research in the Age of Generative AI: Possibilities, Risks, and a Human-Centered Framework; Aisha Naz Ansari
- Chapter 8. Critic of Society, Academic Technician or Withering Scholar? Generative AI, Knowledge Production and Alienation in Contemporary Higher Education; Dirk Michel-Schertges
- Chapter 9. The Prospects of Generative AI in Social Research and Teaching; Markus S. Schulz and Inga Gaižauskaitė
GenAI is transforming our world at a pace and in ways we have never experienced before. As sociologists, we are affected by this in many respects, for AI not only has a massive impact on society – and thus on the subject of our research – but also on the way we conduct our research and the methods we employ. It is therefore of the utmost importance for us to engage with these developments, to recognise their possibilities and limitations, and to convey this to our students. This book makes an important contribution to doing so. It is to be hoped that it will reach a wide readership and thus play a key role in raising awareness amongst scholars and students.
Generative Artificial Intelligence in Social Research and Teaching makes a compelling contribution by connecting empirical studies of GenAI with critical questions about how social scientists produce knowledge and train future researchers. The focus on research integrity and inequality adds value for method teachers and practitioners. Schulz and Gaižauskaitė bring together perspectives that make clear the implications of GenAI for institutional choices and scholarly practices. Read this book to review research protocols and assessment and establish transparent standards for responsible GenAI use.
Generative Artificial Intelligence is reshaping how we research, write, teach, evaluate, and access information and scholarly literature, while raising fundamental questions about knowledge production, academic integrity, inequality, and the future of scholarly work. Yet, debates about its implications for the social sciences are too often shaped by limited experience, social media narratives, or preconceived assumptions. This volume, edited by Markus Schulz and Inga Gaižauskaitė, makes an important contribution by bringing together empirical research, diverse disciplinary perspectives, and experiences from different regions of the world. It moves beyond both technological hype and pessimistic doom to offer a nuanced and informed analysis of one of the most profound transformations of modern social sciences.
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.