Training students to prove they're not robots is pushing them to use more AI

Scope of the problem: AI, essays, and grading

• Many see essay-writing as already distorted by formulaic rubrics (e.g., SAT-style 5‑paragraph essays) that reward structure over insight.
• Others argue that formulaic writing is still a useful communication skill, especially for argument and analysis.
• Several commenters think traditional take‑home essays are now “non-viable” as assessments due to AI; others insist essays remain viable if done in person with unseen prompts.

AI detectors and false positives

• Multiple anecdotes of purely human writing being flagged as AI, sometimes with the detector highlighting the only genuinely human line.
• Specific quirks: detectors over-weight “big words,” em dashes, or HN/Reddit-like style, making competent or distinctive prose look “AI-like.”
• Concern that non-native speakers or neurodivergent students may be disproportionately misflagged (cited from linked summaries of external reporting).
• One side claims state-of-the-art detectors work reasonably well in a probabilistic sense; the other side counters that any nontrivial false-positive rate is unacceptable for punishment, likening it to fortune-telling or predictive policing.
• Profit incentives for vendors and black-box behavior are criticized; the cost of errors falls on students, not companies.

Behavioral and social effects

• Some people deliberately “write worse” or simplify online to avoid accusations of being AI.
• Recurrent theme: once someone yells “witch,” it’s nearly impossible to disprove; AI accusations are seen as a new witch-hunt.
• Commenters worry students are being normalized to automated surveillance and opaque systems making high-stakes judgments.

Rethinking assessment

• Proposals:
  • Move grading to proctored in-person work: timed essays, oral defenses, monitored writing sessions, or code modification exams.
  • Use take‑home work as ungraded practice/prep; rely on exams for grades.
  • Increase frequency of low‑stakes in-class tests instead of one high‑stakes final.
• Counterpoints:
  • Single end-of-term exams are seen as unfair to students with bad days, health issues, or weak time management.
  • Continuous assessment with feedback is argued to improve learning but is now more vulnerable to AI “expediency.”
  • Some suggest focusing less on “catching cheaters” and more on designing tasks requiring genuine understanding, originality, and personal engagement.

Purpose of writing in education

• Strong view that the act of writing—organizing thoughts, practicing argument—is the core skill; outsourcing to AI undercuts learning.
• Others note that well-used AI may be acceptable if a student can explain and defend the result; if teachers can’t tell, perhaps the assignment needs redesigning.