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Generative Artificial Intelligence Guide for Faculty

Generative Artificial Intelligence Guide for Faculty

Generative artificial intelligence (GAI) is capable of generating text, images, or other media. GAI learns the patterns and structure of input training data and then generates new data that has similar characteristics (Wikipedia). Naturally, there are many concerns about GAI, with intellectual property rights and academic dishonesty among them. However, GAI can be a useful tool and can be adapted to classroom teaching and learning once its capabilities, limitations, and programming are understood.

Hoffman (2023) urged educators to reconsider how we view technology that affects classroom learning, stating "If we decide that it's important to use [generative artificial intelligence], then by definition it becomes part of the curriculum, not cheating." Already in wide use in areas such as visual arts, programming, library and information technology, help desks, and other business sectors, GAI has become a ubiquitous element of the workforce and daily living, and thus cannot be ignored. The Bureau of Labor Statistics publishes data on the ever-growing impact of GAI in the U.S. workforce.

As the effects of AI began showing up regularly in the news cycle, Rutter and Mintz (2023) challenged us to re-evaluate how we think of intelligent technology:  

...if a program can do a job as well as a person, then humans shouldn’t duplicate those abilities; they must surpass them. The next task for higher education, then, is to prepare graduates to make the most effective use of the new tools and to rise above and go beyond their limitations. That means pedagogies that emphasize active and experiential learning, that show students how to take advantage of these new technologies and that produce graduates who can do those things that the tools can’t. 

This page offers suggestions for incorporating GAI into classroom teaching, and designing assignments that work effectively with GAI while generally discouraging cheating.

Page Contents:


What GAI Can Do

GAI has the potential to improve certain aspects of higher education. For example, Rutter and Mintz (2023) believe that GAI may be able to help students with traditionally under-funded areas of university life such as career counseling. For administrative work, GAI can act as an assistant, taking notes and providing meeting summaries. 

Generative artificial intelligence technology is currently not in FERPA compliance. Using GAI to record students is not recommended. See the GAI FAQ page for more information.

For course development and classroom work, GAI can be used to help design lessons and assignments and help students produce better work. Some ways that GAI can be used effectively in courses include:

  • Drafting of assignment prompts
  • Drafting of syllabi
  • Suggestions for project topics
  • Keywords for library database searching
  • Drafting of sections of a paper, or suggestions for improvement
  • Synthesizing and arranging recorded knowledge, so that basic facts can be learned and checked in one place instead of many
  • Solving math problems (when the student knowing the process is not critical)
  • Coding, providing code snippets, explanations of programming concepts, and debugging assistance.

Naturally, any material generated by any form of artificial intelligence should be proofread, personalized, improved, and appropriately cited. 


What GAI CANNOT Do
Despite its amazing capabilities, there are things that GAI cannot do. Understanding its limitations may help you work confidently with GAI in the classroom. Here are examples of what GAI cannot do:

  • Access Paid Content: Just like Google, GAI finds content that is popular and paid by advertising first, and it generally cannot access material behind firewalls, thus excluding premium library material. GAI can search abstracts and summaries on Google Scholar and publisher's websites, but that type of analysis is likely to be shallow.
  • Mine the Most Current Internet Content: At this time, GAI is a few years behind in the content it can mine; however this may change quickly.
  • Analyze Newer or Under-Represented Topics: Topics or subjects with minimal content on the Internet will not produce good GAI output.
  • Address Illegal Activity or Certain Sensitive Topics: Some GAI models like ChatGPT are programmed to avoid discussion of what they classify as "harmful ideologies." Questions that ask GAI to consider these concepts, no matter how carefully they are phrased, may be met with a message such as, "I'm sorry, but I cannot engage in discussions that promote or glorify harmful ideologies." When asked "What kind of material will you not research?" ChatGPT (2025, May) responded with this list that include but are not limited to:
     
    • Illegal activities
    • Violence or harm
    • Hate speech or extremism
    • Child exploitation or abuse
    • Non-consensual activities
    • Deepfakes or impersonation
    • Plagiarism or academic cheating
    • Conspiracy theories or misinformation