AI Resource for Faculty

Faculty are encouraged to add domain-specific modifications to these templates. As examples, computer science instructors may want to require or restrict code generators (e.g. Claude Code), and visual arts instructors may want to require or restrict image generators (e.g. DALL-E).

State the Course AI Status (i.e., Fully Human-Centered, Human-Directed w/AI Assistance, or AI-Produced, Human-Guided)

Fully Human-Centered 

• NO GenAI USE: GenAI is not permitted. (ADDRESS EMBEDDED AI TOOLS, LIKE GRAMMAR CHECK) 
•  For example: baseline assessments, handwritten exams, anything else as determined by faculty/managers

Human-Directed with AI Assistance 

•  SOME GenAI USE: AI may be used as a basic search engine or "sounding board" to gather information or organize thoughts. 
•  GenAI may be used as a primary collaborator but the human acts as the editor. 
•  For example: writing edits, literature reviews, assisted research, drafting emails, writing basic code, creating basic visual assets to be used within a larger project

AI-Produced, Human-Guided 

• SYSTEM-LED GenAI USE: AI may be used to perform the task with the human guiding or overseeing the process. 
• For example: automation, prediction, generation of final product, data analysis

The Use of Generative Artificial Intelligence (AI)
The Graduate School recognizes the evolving landscape of generative artificial intelligence (AI) tools and their increasing use in higher education. Certain uses of such tools may be suitable to support and enhance scholarly activities in certain disciplines or in specific courses, assignments and projects. At the same time, there are significant unresolved legal and ethical considerations about the use of these tools with respect to privacy, copyright, authorship and intellectual property that have direct academic integrity implications. Faculty and students are expected to maintain the highest standards of academic integrity and transparency in all scholarly activities, whether generative AI tools are used or not. Decisions, attribution and any guidance regarding the use of such AI tools rest with the course instructor and may vary according to the course activity within the context of a given discipline. Failure to comply with course AI policies/allowances, which includes improper citation, will result in consequences outlined in the Violations of Academic Conduct policy.

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From machine learning to natural language processing, our faculty experts are at the forefront of cutting-edge AI research. Here are a few of our faculty experts engaged in AI with their research, teaching and consulting endeavors:

• George B. Delaplaine Jr. School of Business
  David Gurzick, Ph.D. 
  Teaches AI-related badges and coursework, consults on AI projects and named a top five AI developer by CIOR magazine.
   
• Computer Science & Information Technology
  The faculty members listed below teach AI-related courses and are actively involved in AI research. 
  Shahinur Alam, Ph.D.
  Aijuan Dong, Ph.D.
  Carol Jim, Ph.D.
  Randy Johnson, Ph.D.
  Jiang Li, Ph.D.
  Jason Miller, Ph.D.
  Ahmed Salem, Ph.D.
  Cheng Qian, Ph.D.
   
• Education
  Marisel Torres-Crespo, Ph.D.
  Teaches AI-related coursework and leads faculty AI training workshops
   
• AI Related Research Grants
  • Building a Regional AI Community Through Collaborative Research and Traineeship with Lawrence Berkeley National Laboratory (DE-SC0025718), Department of Energy, $150K (PI: Aijuan Dong, Co-PI: Cheng Qian)​
  • PI, National Science Foundation (NSF) Grant, “Collaborative Research: IUSE: EDU: Curriculum Development for Edge Artificial Intelligence with Hands-on Laboratory,” $95K, (Cheng Qian)

• Tidball Center for Teaching and Learning
• Instructors' Guide to Generative AI
• Human Wisdom for the Age of AI – Teacher’s Guide Learning Modules