AI and Open Science: Implications and Library Practice Recommendations

With the increasing proliferation of artificial intelligence (AI) in higher education and science, technology, engineering, and mathematics research, what are the implications for open science? As the open science movement advocates for increased transparency and openness in the research process, where do AI and machine learning fit in? And where does that leave library and information science professionals in roles related to open science? This article explores several approaches and considerations for how AI impacts open science, including whether AI has sufficient openness and transparency to align with the goals of open science, whether AI can be used to further open science goals, and the effects of AI use on researcher and public attitudes and actions. The article provides recommendations for library practice, including knowledge-building, connections and advocacy, consultations and liaison work, licensing, and science communication and engagement.