# Navigating the meta-crisis of generativity: adapting qualitative research quality criteria in the era of generative AI

## TL;DR

This paper explores how generative AI impacts qualitative research by introducing new ethical and methodological challenges, and proposes ways to adapt research quality criteria.

## Contribution

The paper introduces the concept of the 'meta-crisis of generativity' and offers strategic approaches to address epistemological and ethical challenges in human-AI collaboration.

## Key findings

- Generative AI blurs the boundaries of human and AI authorship in qualitative research.
- Algorithmic audits and adapted validity checklists can enhance trustworthiness in AI-assisted research.
- Posthuman ethics and participatory transparency are proposed to redefine ethical agency in AI collaboration.

## Abstract

Integrating generative AI (GenAI) in qualitative research offers innovation but intensifies core epistemological, ontological, and ethical challenges. This article conceptualizes the meta-crisis of generativity—a convergence of Denzin and Lincoln's three crises: representation (blurring human/AI authorship), legitimation (questioning trust in AI-generated claims), and praxis (ambiguity in non-human participation). We examine how human-GenAI collaboration challenges researchers' voice, knowledge validity, and ethical agency across research paradigms. To navigate this, we propose strategic approaches: preserving positionality via voice annotation and reflexive bracketing (representation); ensuring trustworthiness through algorithmic audits and adapted validity checklists (legitimation); and redefining agency via participatory transparency and posthuman ethics (praxis). Synthesizing these, we expand qualitative rigor criteria—such as credibility and reflexivity—into collaborative frameworks that emphasize algorithmic accountability. The meta-crisis is thus an invitation to reanimate the critical ethos of qualitative research through interdisciplinary collaboration, balancing the potential of GenAI with ethical accountability while preserving humanistic foundations.