AI contributions to participant psychological wellbeing and agency: A case for critical-AI research as qualitative methodology

As generative artificial intelligence (GenAI) becomes increasingly integrated into academia, methodological questions emerge regarding the role of human participants in qualitative knowledge production. This article argues that research tasks requiring participants to generate outputs—that GenAI systems can already simulate—risk reducing meaningful agency and undermining participatory research principles. Drawing on Freire’s theory of knowledge co-creation, the article conceptualizes how research can remain ethical and epistemically rigorous amid new technologies. Accordingly, a five-step iterative framework for critical GenAI-informed research methodology is proposed, which shifts participants from mechanical performers toward becoming meaning-makers who critique, reject, and refine AI-generated outputs. Participants thus function as active cocreators of knowledge and critical evaluators of GenAI systems rather than passive data sources, which may mitigate social desirability bias. Additionally, GenAI offers the potential to reduce participants’ cognitive burden and improve emotional safety, particularly in research that addresses stigmatized topics intersecting with race, gender, disability, socioeconomic status, or Indigenous ancestry. By foregrounding participants’ interpretive authority over GenAI outputs, the proposed framework aims to preserve agency while advancing equity, diversity, and inclusion (EDI) within evolving qualitative research methodologies.