Human versus machine: A comparative analysis of qualitative coding by humans and ChatGPT-4.

Abstract

Generative artificial intelligence (AI) applications are becoming increasingly influential in psychology training, practice, and research. In this study, the procedures (e.g., coding process) and products (e.g., codes, categories, themes, core story) of a qualitative content analysis (QCA) conducted by Chat Generative Pre-trained Transformer (ChatGPT)-4 and novice human researchers were compared, and advantages and disadvantages of each approach were considered. Data included open-ended survey responses from trainers (<i>N</i> = 60) in school psychology programs regarding assessment practices during the COVID-19 pandemic. Findings indicated that ChatGPT-4 conducted QCA with products that were similar, overall, to human coders and in significantly less time. However, ChatGPT-4's process was not transparent, and some codes and themes were unclear. Meanwhile, human coding allowed for the selection and implementation of a purposeful, coherent methodological approach and an auditable and systematic process resulting in defensible themes. Considerations for the use of AI in qualitative research are considered and discussed, and future research directions are provided. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

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