Detecting Synthetic Text Profiles: Human Discernment Versus AI Analytics

This study evaluated human vulnerability to synthetic text profiles generated by artificial intelligence. As large language models become more sophisticated, distinguishing between human and AI-generated content grows increasingly difficult. Our findings show that humans consistently struggled to detect synthetic profiles, which highlights the importance of developing AI tools not only for detection but also for supporting human discernment. By establishing a benchmark of current human capabilities, this research offers a snapshot in time - a necessary step toward tracking how human judgment evolves alongside advancing AI systems through a direct comparison of human performance vs analytic detection approaches. Without such records, it becomes difficult to support users in keeping pace with synthetic media and maintaining control over how credibility is evaluated in digital environments.

Authors

Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Detecting Synthetic Text Profiles: Human Discernment Versus AI Analytics

Regina Luttrell, Jason Davis, Carrie Welch
ScholarSpace (University of Hawaii at Manoa)
Hate Speech and Cyberbullying Detection
article

Detecting Synthetic Text Profiles: Human Discernment Versus AI Analytics

Regina Luttrell, Jason Davis, Carrie Welch
article en

Abstract

This study evaluated human vulnerability to synthetic text profiles generated by artificial intelligence. As large language models become more sophisticated, distinguishing between human and AI-generated content grows increasingly difficult. Our findings show that humans consistently struggled to detect synthetic profiles, which highlights the importance of developing AI tools not only for detection but also for supporting human discernment. By establishing a benchmark of current human capabilities, this research offers a snapshot in time - a necessary step toward tracking how human judgment evolves alongside advancing AI systems through a direct comparison of human performance vs analytic detection approaches. Without such records, it becomes difficult to support users in keeping pace with synthetic media and maintaining control over how credibility is evaluated in digital environments.

ScholarSpace (University of Hawaii at Manoa)
Openalex Percentile: Top 18%
Hate Speech and Cyberbullying Detection
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