
AI models can write convincing fraudulent peer reviews that evade current detection tools, posing a new risk for research integrity.
Key Details
- 1Chinese researchers used the AI model Claude to review 20 actual cancer research manuscripts.
- 2The AI produced highly persuasive rejection letters and requests to cite irrelevant articles.
- 3AI-detection tools misidentified over 80% of the AI-generated reviews as human-written.
- 4Malicious use could enable unfair rejections and citation manipulation within academic publishing.
- 5AI could also help authors craft strong rebuttals to unfair reviews.
- 6Authors call for guidelines and oversight to preserve scientific integrity.
Why It Matters

Source
EurekAlert
Related News

AI-Powered OCT Enables Rapid 'Optical Biopsy' for Early Endometrial Cancer Detection
A team at Washington University has developed a catheter-based 3D OCT system with AI to quickly and noninvasively detect early endometrial cancers.

AI Clinical Reasoning in Diagnostics and Digital Fatigue in Healthcare
Recent JMIR features explore large language models in clinical diagnostics and digital fatigue among healthcare professionals.

KAIST, MIT, Microsoft Develop Efficient AI Image Upsampling for Robotics
KAIST, MIT, and Microsoft have created 'Upsample Anything,' a training-free AI method to restore high-resolution visual data from compressed images with up to 16x improved GPU memory efficiency.