From production to verification: generative AI, doctoral formation, and the leadership of digital education

Summary

Interview study with 21 doctoral students across disciplines on how they negotiate GenAI in scholarly work. Two findings travel well: AI functions as an access infrastructure that lowers linguistic or technical barriers depending on disciplinary demand, and doctoral labour is shifting from PRODUCTION toward VERIFICATION, with students bearing responsibility for judging the accuracy, legitimacy, ownership and defensibility of machine-assisted work while institutional policy stays ambiguous. The 'production to verification' framing is directly usable for the deskilling / division-of-labour argument.

Contribution

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Method

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Relevance to RISE

Surfaced by the 2026-08-29 literature sweep as a high-priority candidate for the RISE knowledge base (angle: human–AI research collaboration). Verified against: Frontiers full-text article page opened 2026-08-29 (title, single author, 2026, method with 21 participants, full abstract read)

Critique / open questions

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Key quotes

Introduction Generative artificial intelligence is often framed in higher education as a problem of academic integrity, assessment security, or technology adoption. (abstract)

This framing is necessary but insufficient for doctoral education, where writing, reading, coding, synthesizing literature, and interpreting evidence are not merely academic tasks but formative practices through which students become scholars. (abstract)