Building Generative AI Literacy: First Steps for Faculty

I just returned from a NEH-funded workshop in NYC where a dozen leaders from language, literature, and writing organizations were charged to create guidance on Critical AI Literacies for students, educators, departments, and institutions. Fortuitously, I was assigned to the team who drafted advice for faculty. Our working paper 3 won’t be released until Summer 2024, but you will find working papers 1 and 2 and other resources by visiting the MLA-CCCC Joint Task Force on Writing and AI.

Learners are privy to increasingly sophisticated technology like generative AI (GAI), and they will be expected to employ these tools in their professional lives. Within this quickly evolving context, our move is to shape how we and our students understand and use GAI by modeling curiosity and experimenting. Cultivating our own critical GAI literacy can help us prepare for the changing landscape GAI brings with it.  

Conceding the Challenges

Before I articulate specific strides faculty can take to move from fear or frustration to the familiarity necessary to create coherent classroom practices and institutional policies about generative AI, I must concede that the challenges are real and fall disproportionately upon individual educators, most of whom are not AI experts.

• We are playing catch up in a fast-moving tech arena most of us did not choose to enter. 
• The cognitive load–and let’s not even discuss the jargon– is high.
• The stress is real, as some see generative AI as a challenge to our values and viability.
• AI detection alone is not an easy fix. While these tools “present a main bias towards classifying the output as human-written rather than detecting AI-generated content” (Weber-Wuff et al, 2023), errors occur in both directions and have weighty consequences. If you suspect AI use, talk to your student, ask questions about the process, etc. For more on how one such tool works, see e-LIS’ Copyleaks and AI Content Detection FAQs.
• Institutions are slow to provide guidelines to support instructors in adapting to the GAI world (Moorhouse et al., 2023, p. 8).

Strengthening Your Own Critical GAI Literacy

Even though we are playing catch up in the generative AI (GAI) arena, we can  strengthen our knowledge of these quickly changing tools. Articulating what you know and what you are curious about discovering is a good first step and can help you consider ways you can experiment with GAI as an individual user and as an educator. 

Be Curious about GAI 
Understanding how GAI works is paramount. Basically, GAI “refers to a class of AI models that generate seemingly new content in the form of text, images, or other media” (Susarla et al., 2023). As deep language learning models (LLMs), they are trained to simulate human language based upon patterns across the training data. More simply, GAI doesn't think and it isn’t good at filtering bias or determining quality in the face of quantity, but it does address some ideas better than others. Reading questions and answers other faculty have asked and responded to may help answer some of your questions and clarify key terms and issues about usage.  

Design Effective Prompts
Finding ways to get the desired search outcomes requires some thought about how to phrase your search question. More simply, the output that you receive really depends on the terms you type into the search bar. The input quality, just like in any field, dictates the output quality. GAIs may also not be able to provide current information, so this may influence how you design assignments or choose current topics for research. 

For example, I had my first year writers pose their research questions to ChatGPT and compare the results to what they’ve learned. Each student interviewed an expert and reviewed scholarly discussions of such topics as how the NCAA’s 2021 interim policy on name, image, and likeness (NIL) has affected college sports, particularly here at OU. What happened? Students experienced different findings. One student received results for NIL that were incomplete because ChatGPT is about a year behind (the cutoff is April 2023) and this rather new policy is still evolving. Moreover, the chatbots cannot address OU phenom Jack Gohlke and his NIL deals, so students will have to tailor their own topic to an OU context.

Think of GAI as an intern who needs specific instructions to net the desired outcomes.
If you want a summary instead of an outline, including that info in the chat box is essential. Other good suggestions for improving your prompt include the following (Arizona State Universities Libraries): 

• Give detailed instructions and state format, length, tone, etc…
• Provide some context (i.e., time period, conditions, higher education)
• Add a role (i.e., community director, biology professor, researcher) 
• Keep refining your phrasing after a reply asking the system to revise for more specifics 

Example
Initial Reply: Please act as an expert academic librarian. I am writing a paper about climate change and am looking for 10 resources about Lake Michigan pollution levels during the 1970s-1980s. Follow-up Reply: Great. Now provide me with 20 key words or phrases that I can use to look in library databases and/or through a Google search.  

Note on Student GAI Use:Before asking students to use GAI, please caution them not only about the extent to which they can appropriately use GAI and the potential for inaccurate or biased results. Students need to understand that the companies that own the tech are collecting information on users and that the information added to a chat exchange may become part of the LLM’s training set.

Experiment with GAI 
Becoming GAI literate involves more than honing your basic understanding of how it works and examining research studies on different aspects of its use. Becoming a user—if only for research purposes–is an important step in building your ethos. 

People have mixed feelings about AI usage with regard to comfort, need, and/or understanding. Some just aren’t curious about how GAI can save labor or help with writing better assignments. However, in the absence of first hand knowledge, we tend to draw inferences that may or may not be true. If we are going to hold students accountable for ethical uses of GAI, we have to consider how it works, how students can use it, and ethical issues that come into play. 

Some educators have already started experimenting with GAI in their courses. On the MLA-CCCC Joint Task Force on Writing and AI website, you can find a community collection of teaching reflections that show how faculty are experimenting with embedding GAI. One researcher investigated how GAI can assist with writing literature reviews; others explored plagiarism issues, institutional policies, teaching voice and tone, and co-learning opportunities. Experiment with a program below by using it yourself or embedding it in a course and then reflect on your findings to help you pinpoint strengths, flaws, and the possibilities of using GAI in your own courses.  

• ChatGPT
• Gemini
• Microsoft Co-pilot 
• Claude

Concluding Thoughts

Increasing our knowledge of GAI, posing questions to a chatbot, and resisting quick fixes do not equate to a policy, but these steps will position us to frame the dialogue about Critical AI. And, they just might improve our blood pressure!

References and Resources 

Generative AI in Academic Writing (A resource from my colleagues at UNC that you could share with your students or tailor to your own needs.)
Generative AI tools and assessment: Guidelines of the World’s Top-Ranking Universities (Weber-Wulff et al., 2023)
The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly Activities in Information Systems (This article by Sursarla et al. (2023) also addresses the role that GAI might play in the academic research process.)
MLA-CCCC Joint Task Force on Writing and AI
Testing of Detection Tools for AI-Generated Text (Moorhouse et al., 2023)

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About the Author

Sherry Wynn Perdue is the Director of the Writing Center at OU and President of the International Writing Centers Association. Her research publications address dissertation supervision, graduate research support, and RAD research. When not teaching, consulting, or writing, Sherry enjoys hiking with her husband Don and their Standard Poodle Pike, both who admittedly spend too much time waiting for her to finish a sentence or a paragraph.

Edited by Rachel Smydra, Faculty Fellow in the Center for Excellence in Teaching and Learning at Oakland University. Others may share and adapt under Creative Commons License CC BY-NC. 

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