Abstract
Artificial intelligence has the potential to revolutionize scientific work. At the same time, the availability of large language models, coupled with high publication pressure, often distorts the way AI tools are used. This study highlights not only the potential of selected contemporary tools, but also the traps and risks that come with using AI tools in the preparation of scientific papers. Wise use of AI techniques can improve the efficiency of work, but an unprofessional approach results in journal clogging and devaluation of the traditional form of sharing scientific achievements.
Metrics
Metrics Loading ...
References
- American Journal Experts (AJE) (2018). Peer review: How we found 15 million hours of lost time. http://www.aje.com/en/arc/peer-review-process-15-million-hours-lost-time/ (access 10.12.2024)
- Kousha, K., Thelwall, M. (2024). Artificial intelligence to support publishing and peer review: A summary and review. Learned Publishing, 37(1), 4-12. https://doi.org/10.1002/leap.1570
- Noy, S., Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381, 187 - 192. https://doi.org/10.1126/science.adh2586.
- Campero A., Vaccaro M., Song J., Wen H., Almaatouq A., Malone T. W. (2022). A test for evaluating performance in human-computer systems. arXiv:2206.12390