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- PaperApplied Linguistics16 Jul 2026
AI and the simplification of task design
Anna Mendoza
This commentary argues that Generative AI simplifies task design in academic writing and qualitative research, potentially hindering deeper learning. The author contends that AI's standardized representations of writing tasks undermine the nuanced understanding needed in EAP instruction, and its limited role in qualitative data analysis overlooks content beyond text. The piece concludes that over-reliance on AI may detract from what students and novice researchers need to learn.
Original abstract
This commentary begins by summarizing Jeon et al.’s (2025) concerns about Generative Artificial Intelligence (GenAI)’s tendency to standardize language, followed by Hu’s (2026) response, on how to bring Artificial Intelligence (AI) into teaching (academic) writing in ways that allow for negotiation of forms. My own response, given the bigger picture, is whether AI needs to be used at all. First, as a former English for Academic Purposes (EAP) writing instructor, I argue that AI represents writing tasks differently from humans, and that going along with its simplified representation is a step back after human experts have rendered more complex representations of the tasks. Second, as a qualitative researcher, I argue that AI is of limited use in qualitative data analysis, since what qualitative researchers analyze goes beyond what is in the text. I conclude that in both these cases, AI simplifies tasks and detracts from what students of academic writing or novice qualitative researchers need to learn.