Topic: Generative AI

This report presents the findings of the interviews that asked faculty to reflect on their perceptions of and experiences with generative AI in both teaching and research. Our study was driven by the following questions: To what degree are faculty adopting generative AI, and how is this changing their approaches and practices in teaching and research? What challenges are they facing in the aftermath of generative AI’s emergence? What support do they still need?…

For this report, we interviewed leaders in stakeholder communities about the potential impact of generative AI on scholarly publishing . The consensus among the individuals with whom we spoke is that generative AI will enable efficiency gains across the publication process. Writing, reviewing, editing, and discovery will all become easier and faster. Both scholarly publishing and scientific discovery in turn will likely accelerate. From that shared premise, two distinct categories of change emerged from our interviews.

Understanding how biomedical researchers are making use of generative AI is critical to informed decision making about how to support ethical adoption of the technology and assessing the risks and opportunities it presents to the research enterprise. However, most studies of the use of generative AI by academic researchers have cast a wide net rather than focusing on adoption in specific disciplines or domains. To this end, we conducted a survey of biomedical researchers.

Understanding how instructors are (or are not) using generative AI in their classrooms is vital because most college and university guidelines leave decision making about how, when, and if generative AI use is permitted to the discretion of individual instructors. To gain insight into evolving instructional practices, we included a short four-question section dedicated specifically to generative AI as part of a national survey of instructors.

Generative AI has quickly gained a significant foothold in academia, and is now used widely for teaching, learning, and research purposes. New products are appearing so rapidly that just keeping up with them is difficult, and understanding the value of individual products in a now-crowded marketplace is a major challenge for end users and for university CIOs, IT departments, and others involved in decision making about which products will be supported and/or licensed for campus users.