Reading the Readers Mind through Eye Tracking: Can AI Generated Texts Match Human Authors?

Chaudhary Muhammad Aqdus Ilyas; Sifat-E Noor; Ashkan  Tashk; Bart Cooreman; Sofie Beier; Per Bækgaard

doi:10.1145/3715669.3726846

Reading the Readers Mind through Eye Tracking: Can AI Generated Texts Match Human Authors?

Chaudhary Muhammad Aqdus Ilyas
, Sifat-E Noor
, Ashkan Tashk
, Bart Cooreman
, Sofie Beier
, Per Bækgaard

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Abstract

While Generative AI models like Large Language Models (LLMs)
are capable of generating extensive text, their efficacy in producing
readable content for human participants in experimental settings
remains to be evaluated. Further, eye-tracking technology is increas-
ingly utilized to study cognition and behavior, yet its application to
readers’ cognitive processes when exposed to AI-generated versus
human-authored texts remains unexplored. This study investigates
how text generated by LLMs influences reading by analyzing gaze
patterns.
The study collects gaze data from 13 participants as they read AI-
generated and human-authored passages. A comparative analysis is
conducted within subjects to assess gaze patterns between authors
and between text types based on the robust two-means clustering
(I2MC) algorithm to identify fixations. In addition, pupil dilation
and reading speed were examined.
Our findings reveal significant differences in fixation character-
istics not only between authors but also between AI-generated and
human-authored texts.

Originalsprog	Engelsk
Titel	Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (ETRA '25)
Udgivelsessted	Association for Computing Machinery
Publikationsdato	2025
Sider	1-7
Artikelnummer	113
DOI	https://doi.org/10.1145/3715669.3726846
Status	Udgivet - 2025
Begivenhed	ETRA: 2025 Symposium on Eye Tracking Research and Applications - Tokyo, Japan Varighed: 26 maj 2025 → 29 maj 2025 https://etra.acm.org/2025/

Konference

Konference	ETRA
Land/Område	Japan
By	Tokyo
Periode	26/05/2025 → 29/05/2025
Internetadresse	https://etra.acm.org/2025/

Kunstnerisk udviklingsvirksomhed (KUV)

Nej

Adgang til dokumentet

10.1145/3715669.3726846

Citationsformater

@inproceedings{aed8e407b90c4717b8b66bc8873be021,

title = "Reading the Readers Mind through Eye Tracking: Can AI Generated Texts Match Human Authors?",

abstract = "While Generative AI models like Large Language Models (LLMs) are capable of generating extensive text, their efficacy in producing readable content for human participants in experimental settings remains to be evaluated. Further, eye-tracking technology is increas- ingly utilized to study cognition and behavior, yet its application to readers{\textquoteright} cognitive processes when exposed to AI-generated versus human-authored texts remains unexplored. This study investigates how text generated by LLMs influences reading by analyzing gaze patterns. The study collects gaze data from 13 participants as they read AI- generated and human-authored passages. A comparative analysis is conducted within subjects to assess gaze patterns between authors and between text types based on the robust two-means clustering (I2MC) algorithm to identify fixations. In addition, pupil dilation and reading speed were examined. Our findings reveal significant differences in fixation character- istics not only between authors but also between AI-generated and human-authored texts.",

keywords = "Eye-tracking, Fixation detection, AI and Human authored reading patterns",

author = "Ilyas, \{Chaudhary Muhammad Aqdus\} and Sifat-E Noor and Ashkan Tashk and Bart Cooreman and Sofie Beier and Per B{\ae}kgaard",

year = "2025",

doi = "10.1145/3715669.3726846",

language = "English",

pages = "1--7",

booktitle = "Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (ETRA '25)",

note = "ETRA : 2025 Symposium on Eye Tracking Research and Applications ; Conference date: 26-05-2025 Through 29-05-2025",

url = "https://etra.acm.org/2025/",

}

Ilyas, CMA, Noor, S-E, Tashk, A, Cooreman, B , Beier, S & Bækgaard, P 2025, Reading the Readers Mind through Eye Tracking: Can AI Generated Texts Match Human Authors? i Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (ETRA '25)., 113, Association for Computing Machinery, s. 1-7, ETRA, Tokyo, Japan, 26/05/2025. https://doi.org/10.1145/3715669.3726846

Reading the Readers Mind through Eye Tracking: Can AI Generated Texts Match Human Authors? / Ilyas, Chaudhary Muhammad Aqdus; Noor, Sifat-E; Tashk, Ashkan et al.
Proceedings of the 2025 Symposium on Eye Tracking Research and Applications (ETRA '25). Association for Computing Machinery, 2025. s. 1-7 113.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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AU - Beier, Sofie

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AB - While Generative AI models like Large Language Models (LLMs) are capable of generating extensive text, their efficacy in producing readable content for human participants in experimental settings remains to be evaluated. Further, eye-tracking technology is increas- ingly utilized to study cognition and behavior, yet its application to readers’ cognitive processes when exposed to AI-generated versus human-authored texts remains unexplored. This study investigates how text generated by LLMs influences reading by analyzing gaze patterns. The study collects gaze data from 13 participants as they read AI- generated and human-authored passages. A comparative analysis is conducted within subjects to assess gaze patterns between authors and between text types based on the robust two-means clustering (I2MC) algorithm to identify fixations. In addition, pupil dilation and reading speed were examined. Our findings reveal significant differences in fixation character- istics not only between authors but also between AI-generated and human-authored texts.

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