AI, libraries, and literacy: revisiting the Journal of the Medical Library Association's policy on the use of generative artificial intelligence in submissions
TL;DR
It is suggested that health sciences librarians, who offer expertise in approaching information systems with discernment, are well suited to be leaders in this space, and a proposed Compliance, Verifiability, and Disclosure Framework is proposed.
Abstract
In the fall of 2023, the Journal of the Medical Library Association (JMLA) introduced its policy on generative artificial intelligence (AI) submissions, predicting that these tools would become embedded within the workflows of clinicians, educators, researchers, and students. Those predictions dramatically underestimated AI's impact. On the three-year anniversary of that editorial, we revisit the issue in light of AI's unprecedentedly rapid adoption across knowledge work. We examine the educational challenges AI poses, arguing that excessive cognitive offloading threatens the deep thinking on which learning depends. We then consider the challenges AI creates for researchers, from hallucinated citations to fabricated diseases. We suggest that health sciences librarians, who offer expertise in approaching information systems with discernment, are well suited to be leaders in this space. To help prospective JMLA authors weigh whether and when to use AI, we propose the Compliance, Verifiability, and Disclosure (CVD) Framework. Throughout, we reaffirm our conviction that education and research must remain human-centered endeavors.