Detection tools unreliable
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Nature article reporting on research showing that AI detection tools are unreliable at identifying AI-generated academic content, highlighting risks to research integrity and the need for improved detection methods.
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A preprint study found that AI chatbots like ChatGPT can generate research paper abstracts that are convincing enough to fool scientists into believing they are human-written. The research, posted on bioRxiv in December 2022, demonstrates that current detection methods are unreliable at identifying AI-generated academic content. This finding has sparked debate within the scientific community about the implications for research integrity and the need for better detection tools or policies to address AI-generated submissions.
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| Page | Type | Quality |
|---|---|---|
| Scientific Knowledge Corruption | Risk | 91.0 |
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Abstracts written by ChatGPT fool scientists
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An artificial-intelligence (AI) chatbot can write such convincing fake research-paper abstracts that scientists are often unable to spot them, according to a preprint posted on the bioRxiv server in late December 1 . Researchers are divided over the implications for science.
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Nature 613 , 423 (2023)
doi: https://doi.org/10.1038/d41586-023-00056-7
References
Gao, C. A. et al. Preprint at bioRxiv https://doi.org/10.1101/2022.12.23.521610 (2022).
Blanco-Gonzalez, A. et al. Preprint at arXiv https://doi.org/10.48550/arXiv.2212.08104 (2022).
O’Connor, S. & ChatGPT Nurse Educ. Pract. 66 , 103537 (2023).
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