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A team of 416 qualitative researchers from 38 nations, headed by Prof. Tanisha Jowsey from Bond University in Australia, has opted against employing generative artificial intelligence tools in reflexive qualitative research, such as reflexive thematic analysis and several phenomenological methods.

Academics, in a “global statement opposing GenAI,” stated their choice stemmed from “methodological and ethical issues.”

They stated, “Simulated intelligence through GenAI is unable to create meaning; qualitative research must continue to be a uniquely human activity; there are well-documented various harms caused by GenAI, particularly to the environment and workers in the Global South.”

A statement released on Monday mentioned that the decision, made during a gathering of over 400 academics from more than 30 nations in October 2025, will be officially shared during a webinar planned for December 11.

Other academics who are advocating against the use of GenAI in reflexive qualitative research are Dr. Virginia Braun from the University of Auckland; Dr. Victoria Clarke from the University of the West of England; Professor Deborah Lupton of the University of Canberra; and Professor Michelle Fine of the City University of New York.

They claim that GenAI, as a simulated type of intelligence based on statistical prediction, challenges the core of reflexive thematic analysis, which relies on profound meaning creation and human understanding.

They also cautioned that since GenAI functions through algorithmic patterns, it often reinforces prevailing narratives, possibly leading to the further suppression of underrepresented perspectives.

The text stated, “GenAI is still just simulated intelligence, relying on statistical predictive algorithms without any true comprehension of the world, or the significance of the language used in the data being examined, or even the meaning behind the themes generated during the simulation of qualitative analysis.”

Although GenAI combined with human input could generate something that appears to mimic reflexive qualitative analysis (by imitating the methodological process), it cannot truly be reflexive, as reflexive qualitative analysis is, by nature, a meaning-driven approach.

Neglecting to acknowledge these constraints of GenAI can lead to analyses that support prevailing paradigms and biases. In other words, the algorithmic structures that GenAI relies on tend to cause it to detect, copy, and strengthen dominant linguistic patterns, potentially leading to the suppression of marginalized voices and practices, including those of critical scholars. The perspectives and ways of life of individuals who experience, feel, imagine, and create knowledge within the margins of life… could be overlooked or even sacrificed.

They also highlighted that social science research is a “uniquely human activity” focused on comprehending individuals and societal mechanisms, arguing that AI is unsuitable for every phase of reflective qualitative analysis, including the first stage of coding.

The statement added, “Reflexive qualitative research is a uniquely human endeavor, carried out by people, involving or relating to people (such as via interviews, focus groups, or written materials), and aimed at benefiting people.”

The core principle of social science research is to gain a more profound understanding of individuals and societal processes, as well as to examine and question the creation of meaning. We believe that only humans are capable of performing reflective qualitative analysis, making the use of GenAI unsuitable at every stage of reflexive qualitative analysis, including the initial coding process.

They also expressed worries regarding the negative effects of AI on both people and the environment, such as exposure to e-waste, water and energy consumption, soil deterioration, and carbon emissions from data centers.

“We highlight the troubling exploitative, colonial, and extractive methods used by major AI companies, which negatively affect people and the environment. We are worried about these significant ethical and health concerns,” the statement mentioned.

Experts also cautioned that individuals engaged in training and overseeing digital content for artificial intelligence systems encounter considerable health dangers.

Because of these factors, they stated that GenAI is not suitable for reflexive thematic analysis and other reflexive qualitative methods.

The webinar on December 11, hosted by TRAC Africa, will include presentations from Prof. Tanisha Jowsey (Bond University), Prof. Adeshina Afolayan (University of Ibadan), Prof. Daniel Doh (University of Western Australia), and Prof. Ayo Ojebode (TRAC Africa, Rwanda).

Provided by SyndiGate Media Inc.Syndigate.info).