LibGuides: NU Faculty Resources Guide: Artificial Intelligence

National University AI Support

Artificial Intelligence Council
The AI Council at NU has a series of committees working on AI strategy for the university. Learn more and find resources on their SharePoint site.
Student-Faculty AI Usage Guidelines
NU encourages faculty and students to embrace the innovative use of Artificial Intelligence to enhance the educational experience. The NU Student-Faculty AI Usage Guidelines aim to facilitate the responsible and ethical use of AI in the classroom.
Fundamentals of AI at NU
This WES/PACE course offers the opportunity to consider ways to use AI to enhance collaboration, manage classrooms, and provide personalized feedback through automated grading. The course will also touch on the ethical dimensions of AI in education, emphasizing responsible use, equity, and privacy. All employees can now enroll in the Fundamentals of AI at NU course at no cost.
GAiIT Framework
The GAiIT Framework, developed by faculty in SCOE, is a useful resource for faculty looking to incorporate guidance for students in their courses on the appropriate use of generative AI.
Citing AI in Academic Work
This guide for students and all members of the NU community provides details on how to use and cite AI in academic work.
AI LibGuide
This guide, developed by the NU Library, is designed to help answer questions and provide resources regarding AI, ChatGPT, Large Language Models, and their relationship to academics.

AI Capabilities

Artificial Intelligence (AI), including generative AI, has shown significant advances in the last few years. The following are some of the many current capabilities of Artificial Intelligence: Creative writing, Content recommendations, Tutoring, Code writing, Technical help - context aware, Content evaluation and recommendations, Automated email responses, Question answering / Google search alternative, Summarization (text, transcripts, video captions, etc.), Text completion, Text classification, Translation, Sentiment analysis, Language modeling, and Data analysis.