AI Ideas Transformed into Priorities at the University of Maryland
A working group of faculty members at the University of Maryland, Baltimore turned 24 ideas in the field of artificial intelligence into three core institutional priorities and a peer-reviewed study.
The artificial intelligence working group, consisting of representatives from seven schools within the University of Maryland, Baltimore, carried out a comprehensive process to manage the burden of innovation across the university and integrate artificial intelligence responsibly.
Formation and Scope of the Working Group
Meeting between January and March, the University of Maryland, Baltimore Artificial Intelligence Teaching and Learning Working Group brought together representatives from seven different schools.
This interdisciplinary structure enabled the identification of responsible artificial intelligence opportunities that reflect the diversity and needs of the university's professional education programs.
Prioritization of Artificial Intelligence Ideas
The process started with 24 artificial intelligence use cases, which were initially too numerous to evaluate.
The group developed a five-stage pipeline based on transparent scoring and consensus to synthesize the ideas and settle on three institutional priorities.
Three Institutional Priorities Identified
The resulting proposals included an institutional virtual assistant, an interdisciplinary virtual practice laboratory, and an educator resource providing pedagogical guidance.
These proposals aim to balance the workload of faculty members while providing continuous support to students.
First Implementation Step and Peer-Reviewed Study
As a result of the evaluation conducted in August, the educator resource project was selected as the first implementation priority in the mission area of teaching and learning.
The working group also turned this process into an academic paper, presenting a model that can serve as an example for other universities.