Paradigm shifts: exploring AI's influence on qualitative inquiry and analysis - Williams, Ryan Thomas (Frontiers in Research Metrics and Analytics, 2024)
Technology has mostly been embraced in qualitative research as it has not directly conflicted with qualitative methods' paradigmatic underpinnings. However, Artificial Intelligence (AI), and in particular the process of automating the analysis of qualitative research, has the potential to be in conflict with the assumptions of interpretivism. The short article aims to explore how AI technologies, such as Natural Language Processing (NLP), have started to be used to analyse qualitative data. While this can speed up the analysis process, it has also sparked debates within the interpretive paradigm about the validity and ethics of these methods. I argue that research underpinned by the human researcher for contextual understanding and final interpretation should mostly remain with the researcher. AI might overlook the subtleties of human communication. This is because automated programmes with clear rules and formulae do not work well under interpretivism's assumptions. Nevertheless, AI may be embraced in qualitative research in a partial automation process that enables researchers to conduct rigorous, rapid studies that more easily incorporate the many benefits of qualitative research. It is possible that AI and other technological advancements may lead to new research paradigms that better underpin the contemporary digital researcher. For example, we might see the rise of a ‘computational’ paradigm. While AI promises to enhance efficiency and rigour in data analysis, concerns remain about its alignment with interpretivism.