In a paired exploratory comparison, extensive machine rewriting by a commercial humanizer materially degraded the manuscript while changing the detection score only slightly¶
Claim · All claims
Evidence · 1 study · reviewr3·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? After commercial humanizer rewriting that inserted meta-instructions at twelve points and increased word count from 4,808 to 6,227 words (a 29.5% increase), Originality.ai reported 81% Likely AI for the original and 78% Likely AI for the rewritten version. → Victor Angelier 2026
Evidence¶
Victor Angelier 2026¶
Victor Angelier. (2026). The pitfalls of AI detection in academic writing: bias, false positives, and the need for inclusive assessment. AI and Ethics. https://doi.org/10.1007/s43681-026-01376-w
q2 · i? · review · r3
A paired exploratory comparison in the audit: the human-authored manuscript was processed through a commercial humanizer, which "increased the word count from 4,808 to 6,227 words, a 29.5% increase" and degraded the text, yet the reported score changed only from 81% to 78% Likely AI.
"Originality.ai reported 81% Likely AI for the original manuscript and 78% Likely AI for the rewritten version."
Discussion¶
Related Claims¶
- In a documented exploratory audit, one human-authored manuscript received materially different classifications from five commercial detectors, spanning 0% human to Human Generated — related
- Independent evaluation found commercial AI-text detectors neither sufficiently accurate nor sufficiently reliable for high-stakes use — related
- AI-content detection tools achieve only marginally higher success than human reviewers, around 80% versus 78.4% — related
- AI language polishing alone can flip human-authored scholarly texts from human-classified to AI-classified — related
- Light AI-assisted edits to human-written abstracts are flagged by commercial detectors at 64–80% (Pangram) and 38–49% (GPTZero) rates — related
- AI text detectors can return high AI-detection scores for human-written academic text, raising fairness concerns about authenticity evaluation — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
humanizer-rewriting-small-score-change |
title |
In a paired exploratory comparison, extensive machine rewriting by a commercial humanizer materially degraded the manuscript while changing the detection score only slightly |
description |
In a paired exploratory comparison, extensive machine rewriting by a commercial humanizer materially degraded the manuscript while changing the detection score only slightly |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
recheck_by |
2029 |
generated |
by process:wiki-ingest on 2026-10-10 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — victor-angelier-2026 |
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