AI for social science: A sociology PhD candidate's autoethnography on how LLMs are changing research work

Abstract

Will AI replace social scientists? The real issue concerns reshaping rather than replacement. Confronting the integration of large language models (LLMs) into academic training establishes “prompt engineering” as the core interface for collaboration, defining it as a method to translate sociological thinking into precise instructions. LLMs are becoming essential partners across the research spectrum. They transform qualitative analysis from a solitary craft into a dialogical coding process and assist in theoretical localization and the construction of localized measurement scales. Beyond text analysis, they provide a low-cost virtual testbed for experimental design through “silicon samples” and enable the deduction of complex social interactions via “generative agents.” In the quantitative realm, they act as translators connecting research intentions with statistical code. Ultimately, the core challenge facing researchers is not technical. It lies in proactively cultivating a critical “literacy for human-AI collaboration” to master this paradigm shift.