The recent surge in popularity of AI tools such as ChatGPT is forcing the science community to reckon with its place in scientific literature. Prestigious journals such as Science and Nature have attempted to restrict or prohibit AI use in submissions, but detecting machine-generated language proves difficult.
Since AI is getting more advanced at mimicking human language, researchers at the University of Chicago were interested in learning how frequently authors are using AI and how well it can produce convincing scientific articles. In a study published in JCO Clinical Cancer Informatics, Alexander Pearson, MD, PhD, Frederick Howard, MD, and colleagues evaluated text from over 15,000 published abstracts from the American Society for Clinical Oncology (ASCO) Annual Meeting from 2021 to 2023, using several commercial AI content detectors. They found that there were approximately twice as many abstracts containing AI content in 2023 as compared to 2021 and 2022—a clear signal that researchers are utilizing AI tools in scientific writing.
Interestingly, the content detectors were much better at distinguishing text generated by older versions of AI chatbots from human written text, but they were less accurate in identifying text from the newer, more accurate AI models or mixtures of human-written and AI-generated text.
Howard and colleagues warned that while AI can be used as a tool to aid in scientific writing, the author is ultimately responsible for all aspects of the submission, requiring due diligence to ensure factual and accurate representation of content with no misleading or inaccurate information.
They also concluded that because AI content detectors will never reach perfect accuracy, they should not be used as the sole means to assess AI content on scientific writing. Instead, they could be used as a screening tool to indicate that the presented content requires additional scrutiny from reviewers.