AI research assistant helping with coding and data analysis In recent years, large language models, coding agents, and automation tools have gradually entered research practice. They can assist researchers with literature organization, code implementation, experiment orchestration, result aggregation, and even drafting. But this does not mean that the research process will naturally become more rigorous. On the contrary, if clear boundaries, evaluation, and process control ar

Human–AI Delegation in Social Science Codifiable Tasks vs. Tacit Knowledge, Theoretical Originality, and Field Judgment In an age where everyone is talking about AI, social science research finds itself at a delicate crossroads. Recently, Yongjun Zhang (2026)  from Stony Brook University raised a provocative question in his latest paper, " Vibe Researching as Wolf Coming ": what parts of your research can only you  do, and what can the machines never replace? Is it running te

Generative AI democratization in consumer research: broader participation brings new voices into the data ecosystem. Today, a consumer researcher beginning a new project may start not with a database, but with a generative AI system. Within seconds, a structured framework emerges. Literature streams are synthesized, research questions are articulated, and potential hypotheses are outlined. The efficiency is undeniable. Yet Huang and Rust argue that efficiency is not the centr

How GenAI Transforms Qualitative Data Analysis Generative Artificial Intelligence (GenAI) is reshaping qualitative consumer culture research by introducing new efficiencies while raising epistemological tradeoffs across theoretical, embodied, empirical, and historical dimensions. In other words, when consumer culture researchers upload interview transcripts, fieldnotes, or archival materials into large language models (LLMs), what changes is not merely research efficiency. Ep