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New research · Otolaryngology (ENT)
World journal of otorhinolaryngology - head and neck surgery · 1w
AI / informaticsWorld journal of otorhinolaryngology - head and neck surgery · 2026

Clarity Without Credibility? Human Versus AI Abstracts in Otolaryngology.

Sholem Hack, Rebecca Attal, Lirit Levi … Ameen Biadsee
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Otolaryngology (ENT)AI / informatics

Otolaryngologists often could not tell human-written abstracts from AI-written ones

Clarity Without Credibility? Human Versus AI Abstracts in Otolaryngology.

Sholem Hack … Ameen Biadsee
World journal of otorhinolaryngology - head and neck surgery · 2026
Purpose

This study evaluated whether otolaryngologists can distinguish between human- and machine-written abstracts.

Methods

A blinded cross-sectional design was used.

44.7%
Results
44.7%
ear, nose, and throat doctors correctly spotted the writer less than half the time
More results

Human-written abstracts were more often misclassified as AI than AI-generated abstracts were mistaken for human.

Human abstracts received significantly higher clarity and usefulness scores than large language models abstracts, though effect sizes were small.

Confidence did not correlate with correctness, indicating miscalibration of rater judgments.

More results

Grok-generated abstracts were most easily identified as AI, whereas GPT-5 and Claude 3.5 more frequently resembled human writing.

“
Conclusion · 1 of 2

Large language models generate abstracts that increasingly resemble human scientific writing, yet still lag in perceived usefulness and credibility.

Conclusion · 2 of 2

Clinicians were only moderately successful at detecting authorship and were frequently confident in incorrect classifications. These findings highlight both the promise and risks of AI-assisted scientific communication.

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