My institution recently began using an AI detector that gives a percentage score for AI-generated content. If the score is high, the work is immediately questioned. There is no discussion of uncertainty or margin of error. When did these scores start being treated as proof rather than estimates?
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Overconfidence in AI Detection Scores and Ethical Misuse of Results
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Jan 23, 2026 10:06 am
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Jan 23, 2026 10:07 am
This shift happened when institutions began prioritizing scalability over judgment. AI detection scores were designed as indicators, not evidence. Treating them as proof ignores the probabilistic nature of these systems and undermines principles of fairness and due process.
Jan 23, 2026 10:07 am
Percentages create a false sense of precision. In reality, detection accuracy varies widely depending on writing style, subject matter, and language proficiency. When this uncertainty is ignored, tools are elevated from advisory roles to decision-makers.
