Mario Malički
Editor-in-chief, RIPR Journal, Stanford UniversityUnited States
The EASE Peer Review Committee Chair, Mario Malički, hosted this discussion with panellists James Zou, Lu Sun and Mike Thelwall.
The transformative power of Large Language Models, and new AI technologies is bringing excitement for the future we might soon find ourselves living in. But it also brings worries regarding the possible mass layoffs of workers. These considerations are permeating science with aims to revolutionise the speed with which the new scientific discoveries will be made. This means that both idea generation, study conduct, writing of manuscripts and research dissemination, as well as quality control might be enhanced or completely overtaken by ‘machines’. View the recording of this EASE webinar, in which we discussed how the landscape of peer review is already changing due to these new technologies.
This EASE webinar was free and open to all.
Associate Professor of Biomedical Data Science, CS and EE, Stanford UniversityUnited States
Professor of Data Science, Information School, University of SheffieldUnited Kingdom