警告：生成式AI在质性研究中不可靠，可能破坏研究可信度。
Generative Artificial Intelligence in Qualitative Research Methods: Between Hype and Risks?
- 质疑生成式AI在质性编码中的方法论有效性
- 指出其输出错误、缺乏透明度且无法溯源
- 适合关注研究严谨性的学者警惕技术炒作
随着人工智能在质性研究中被广泛推广和使用，其引发的方法论问题也日益凸显。本文批判性地审视生成式AI（genAI）在质性编码方法中的角色。尽管存在效率提升的宣传，但本文主张，genAI在质性研究中不具备方法论正当性，其使用可能损害研究的稳健性与可信度。缺乏有意义的记录、商业机密的不透明性，以及genAI系统固有的生成错误倾向，均削弱了方法论严谨性。总体而言，风险大于收益，本文呼吁研究者应将科学方法置于技术新奇性之前。
原文摘要 · Abstract (English)
As Artificial Intelligence (AI) is increasingly promoted and used in qualitative research, it also raises profound methodological issues. This position paper critically interrogates the role of generative AI (genAI) in the context of qualitative coding methodologies. Despite widespread hype and claims of efficiency, we propose that genAI is not methodologically valid within qualitative inquiries, and its use risks undermining the robustness and trustworthiness of qualitative research. The lack of meaningful documentation, commercial opacity, and the inherent tendencies of genAI systems to produce incorrect outputs all contribute to weakening methodological rigor. Overall, the balance between risk and benefits does not support the use of genAI in qualitative research, and our position paper cautions researchers to put sound methodology before technological novelty.
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