Williams Ryan Thomas
Teesside University International Business School, TU Online, Teesside University, Middlesbrough, United Kingdom.
Front Res Metr Anal. 2024 Dec 5;9:1331589. doi: 10.3389/frma.2024.1331589. eCollection 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 analyze 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 rigor in data analysis, concerns remain about its alignment with interpretivism.
在定性研究中,技术大多受到欢迎,因为它与定性方法的范式基础没有直接冲突。然而,人工智能(AI),尤其是定性研究分析自动化的过程,有可能与解释主义的假设产生冲突。这篇短文旨在探讨诸如自然语言处理(NLP)等人工智能技术是如何开始被用于分析定性数据的。虽然这可以加快分析过程,但也引发了诠释范式内关于这些方法的有效性和伦理问题的辩论。我认为,基于人类研究者进行情境理解和最终解释的研究,大多仍应由研究者来完成。人工智能可能会忽略人类交流的微妙之处。这是因为具有明确规则和公式的自动化程序在解释主义的假设下效果不佳。尽管如此,在定性研究中,可以在部分自动化过程中采用人工智能,使研究人员能够进行严谨、快速的研究,更轻松地融入定性研究的诸多益处。人工智能和其他技术进步有可能导致新的研究范式,更好地支撑当代数字研究者。例如,我们可能会看到“计算”范式的兴起。虽然人工智能有望提高数据分析的效率和严谨性,但人们仍对其与解释主义的契合度存在担忧。