The AI LIteracy Approach vs AI Detection/Policing
From predictive text in our emails to patient notes after a doctor visit, AI is prevalent in our lives. With any new technology, our first reaction could take many forms: excited curiosity, skepticism, blissful ignorance, avoidance, and fear. However, AI, and in particular generative AI, is being used heavily in industry and disciplines. It will be essential that our students develop an AI Literacy and become responsible users of AI platforms.
What is AI Literacy?
AI Literacy is a philosophical approach aimed at preparing students and our disciplines for developing an agile, ethical approach to this technology. From understanding the basic functions of generative AI to critically evaluating the use of AI and its ethical ramifications, AI Literacy seeks to educate students on the how, why, and when of ethical AI use.
Digital Promise, a global, non-profit focused on educational access, conducts research in learning sciences and educational technology. In 2024, they developed an AI Literacy Framework with corresponding resources for integrating AI Literacy skills into the curriculum.
The framework outlines three key areas of AI Literacy development: Understanding AI, Using AI, and Evaluating AI. Additionally the framework outlines specific practice areas within each area:
| Understanding AI | Using AI | Evaluating AI |
|---|---|---|
| Understanding Algorithmic thinking, abstraction and decomposition; Data Analysis and inference; Data Privacy and security; Information and mis/disinformation; Ethics and impacts; Digital Communication and Expression | Creating AI; Interacting with AI; Using AI for Problem Solving | Information and mis/disinformation; Ethics and impacts; Digital Communication and Expression; Data Privacy and security; Data Analysis and inference; Understanding Algorithmic thinking, abstraction and decomposition |
ive AI as a potential partner for learning. In the Advancing Meaningful Learning in the Age of AI, they begin answering questions about the impact of generative AI on cognition and critical thinking.
h technology, has developed an AI Literacy in Teaching and Learning Framework to help educators and students understand four concerns when using AI:
- Technical: how artificial intelligence works
- Evaluative: skills to critically evaluate an AI platform, its application, and the output
- Practical: application and implementation of AI in teaching and scholarly settings, industry and disciplinary spaces
- Ethical: the development and maintenance of institutional mechanisms that govern AI use and implementation, while limiting misuse
EDUCASE provides guidelines and criteria for developing AI Literacy specific to faculty and students.
Discussing Generative AI with Students
After exploring some generative AI tools, instructors will need to decide how to discuss this technology with their students, consider potential policies around its use and revisit some of their assessments in their courses.
Keep in mind:
- Students may lack a clear process for creating scholarly work. Consider surveying students at the beginning of the semester to share their current process for completing their coursework. For instance, how do they approach research? What’s their experience in creating citations? How do they tackle bigger projects like papers and presentations? Knowing this information can suggest relevant ways to discuss how to approach course work and ethical uses of generative AI.
- Students may be new to generative AI technology. Don’t assume that because generative AI is in the news that your students already know how to use it. If there is concern about students using this technology unethically, discuss the technology as a class. Discuss academic honesty and ethical uses of this technology. Explain what role generative AI should play in the course. Add language to the course syllabus that clarifies expectations of generative AI use.
- Students rely on instructors to develop a scholarly process. Scaffold large assignments to help students learn the process of learning and critical thinking. Use smaller, reflective assignments to help students learn and practice specific steps in the scholarly process.
- Students need to know how generative AI will be used in their field of study. Discuss with students how professionals are using this technology. Consider bringing in a guest speaker from your field to discuss this technology and ask questions.
- Students value assignments that are authentic and give students agency. Consider revisiting some assignments that encourage students to analyze the output of AI generators. For example, instead of asking students to write a paper, generate one or more papers from a generative AI source and ask students to analyze the output with some guiding questions.
- Students don’t come to college with the intention to cheat. Create a class environment that encourages students to feel comfortable approaching you and others when they need support.
Providing REsources and Guidance
Like any emerging technology, students may or may not be experienced in using GAI or understand the best approach to doing so. Moreover, information and perspectives tied to this technology are continuously evolving faster than our documentation and scholarship processes. This rapid progression is tied to the very nature of generative AI.
Students need clarity on how to use AI ethically in your courses and in their scholarly work. Harvard Business Publishing developed a Student Use Cases for AI: Start by sharing these guidelines with your class (2023) resource that can help your students understand four key uses for AI in learning: AI as feedback generator, AI as personal tutor, AI as team coach, AI as learner.
Consider when using AI in your course might be a helpful tool, and give students examples and context for its use.
Quick Videos to Share with Students
Here are two quick student-facing videos from the University of Louisville’s Citizen Library.