Many people are experimenting with chatbots to enhance their daily lives, but scientists are ahead of the curve. Currently, over 10% of scientific paper abstracts are partially written by large language models (LLMs), with this figure reaching 20% in computer science and a third among Chinese researchers.

Benefits and Concerns
The rapid adoption of AI in academia has sparked debate. Critics worry about an influx of low-quality papers, potential biases, and plagiarism. Some journals, like those in the Science family, have implemented strict disclosure requirements for AI usage, but these measures may be misguided. Policing AI use is challenging, and many scientists find significant benefits in using these tools.

Enhancing Efficiency and Accessibility

LLMs help scientists by speeding up the writing process, allowing more time for research, collaboration, and error-checking. Additionally, these models can level the playing field for non-native English speakers, enabling them to publish in prestigious journals without language barriers.

Potential Risks
Despite their advantages, LLMs pose risks. They could facilitate the creation of fraudulent papers and inadvertently perpetuate plagiarism by mimicking past work. The reliance on AI might also weaken scientists’ ability to develop and clarify their ideas through writing.

Embracing AI’s Potential
Instead of restricting AI, the focus should be on strengthening safeguards against misuse. Peer review must be enhanced, possibly by compensating reviewers. Encouraging replication of experiments and rewarding quality over quantity in research will help mitigate risks. With proper measures, AI can significantly benefit the scientific community.