This critique highlights ethical failures in AI plagiarism detection systems, suggesting a need for human-centered oversight.
This article critiques the ethical authority granted to AI plagiarism detection systems, using humor to expose a serious contradiction in these algorithms. Through a case in which an original ethics manuscript is labeled 40.7% “non-original,” the authors argue that similarity scores are mistaken for judgments of misconduct. They introduce the concept of “epistemic substitution” to describe how tools that both judge originality and offer AI rewrites replace human authorship while mandating human accountability. The paper contends that this collapse of roles undermines scholarly integrity, conflates disciplinary fluency with plagiarism, and shifts ethical responsibility from humans to procedures. The authors call for contextual, human-centered oversight of AI-assisted evaluation.
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Ostler et al. (2026) studied this question.
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