Generative AI in the Social Sciences: Toward Critical Integration and Methodological Innovation

This paper explores the implications of generative artificial intelligence (GenAI) for research in the social sciences. We argue that GenAI is not merely a technical tool, but an epistemic agent that transforms how knowledge is produced, interpreted, and disseminated. Drawing on recent developments in large language models, image generators, and multimodal systems, we identify four key methodological opportunities—qualitative analysis, theory-building through simulation, visual and multimodal research, and collaborative writing. We then examine the risks and tensions these opportunities present, including algorithmic bias, hallucination, and the automation of interpretive judgment. In response, we outline a pedagogical and research agenda for critical AI literacy, ethical infrastructure, and methodological pluralism. Our goal is to initiate a reflexive, interdisciplinary conversation about how GenAI can be responsibly and creatively integrated into the social sciences.