AI Agents in Online Surveys If you run online surveys today, there is a good chance your respondents come from an online recruitment platform. These platforms now sit behind a large share of behavioral research, shaping academic work in psychology, public health, economics, and political science. They also support consequential commercial decisions in product design and public communication. But the rise of large language models (LLMs) has made an old concern feel newly urg

Why GATOS Matters Qualitative data are often where social scientists go when numbers are not enough. Open-ended survey responses, interviews, and written reflections can capture forms of meaning that are difficult to reduce to numbers. As Saldaña (2011) argues, qualitative data analysis is fundamentally a process of meaning-making: researchers construct patterns, identify relationships, and move between inductive and deductive forms of reasoning. The difficulty is that this

Paradigm Shift from Traditional Coding to Conversational Analysis The rapid emergence of generative artificial intelligence (genAI) tools is fundamentally reshaping how researchers engage with unstructured data, particularly within the domain of qualitative analysis. While these technological advancements offer exciting possibilities, they also bring significant challenges. Traditional qualitative coding methods, though rigorous, are often extremely time-intensive, whereas ge

AI in Qualitative Research: Collaborative Partner or Epistemic Risk? The rise of Generative Artificial Intelligence (GenAI) has sparked a profound scholarly debate in the field of qualitative research, centered on a critical question: Do Large Language Models (LLMs) enhance the depth of qualitative exploration, or do they fundamentally threaten its epistemological foundations? Adam S. Hayes (2025) argues that LLMs are revolutionizing how scholars work with textual data by all