In fall 2023, 49 percent of students reported using Generative AI during their learning experience.1 That figure is only expected to balloon. So how do you meaningfully incorporate AI into your course? Dr. Jesse Stommel has a solution. The award-winning faculty member and author of Undoing the Grade: Why We Grade, and How to Stop, offers a valuable exercise to help students critically analyze the limitations and opportunities of AI in education. His six-step activity won’t only help students better grasp how AI intersects with algorithmic bias and ethical data use. It’ll also help you host a set of timely conversations with students about the future of teaching and learning. Here’s how to get started.
Step 1: Ensure all students are familiar with Generative AI
ChatGPT. Bard. WALL-E. Many students are likely familiar with at least one of these Generative AI tools. Ask learners to engage with a platform of their choice to better grasp the functionality that AI can offer. In turn, this process will allow students to critically evaluate the affordances—and shortcomings—of such platforms. Stommel advises educators to not require students to create accounts when exploring on their own. His rationale as to why will become increasingly evident after reviewing any Generative AI platform’s Terms of Service.
Step 2: Read and discuss Generative AI’s Terms of Service
When was the last time you read the Terms of Service after signing up for a new technology? Most of us just bypass the legalese, and there’s a good chance your students do the same. But taking a closer look can be illuminating. Have students review the T’s and C’s for a given platform in small groups and ask them to report out on anything they find striking—a great exercise to help them become more conscious digital citizens.
Consider asking students to respond to the following questions when engaging in their exploration.
- How does generated content get stored?
- Does user data get harnessed by AI platforms to improve their language models?
- Am I able to claim ownership of AI-generated work?
- Is the content generated considered my intellectual property?
- What happens to data in the event of a breach?
- What’s one thing that surprised you when reviewing the Terms of Service?
The answers to the questions above can be deeply complex. It’s why it’s so crucial to have an open discussion with students on how these platforms function from a technical lens.
Step 3: Input a research prompt or question
Let students formulate a research question or prompt to ask Generative AI that’s relevant to their coursework. Before students input their prompts, ask them to reflect on what type of response they expect to receive from Generative AI. What might they do to improve the value of the output? Now’s a great time to remind students that the strongest AI prompts are fairly robust, offering clear instructions and providing plenty of supporting context. Here are some examples of strong and weak AI prompts.
| Strong AI prompts | Weak AI prompts |
|---|---|
| Explain the process of economic supply and demand in simple terms. | Tell me about photosynthesis. |
| Create a short story about an aspiring journalist attending a film festival. | Write a paragraph about the importance of water. |
| From the point of view of Apple CEO Tim Cook, describe the innovation behind the latest Apple Watch. | Write a press release for a new e-commerce service. |
| Create a social media post for a HIV / AIDS fundraiser hosted by New York University. | Rewrite the paragraph below. |
Step 4: Consider the generated results
Ask students to analyze the responses that Generative AI spits out. This works well as an individual or small group exercise. What do they notice? Does the work appear as though it was created by a human? Why or why not? Are there proper references? How would they assess the voice and tone or level of subject matter expertise? Who does the intellectual property belong to? You might also encourage students to consider how they would adjust their prompt to improve the output.
Step 5: Consider how AI fuels ethical risks
Host a discussion with students to address questions related to bias, plagiarism, intellectual property, and fair access. For example, since Generative AI is trained on vast amounts of existing data, how might existing biases affect the outputs we see? How would they handle attribution when using Generative AI for coursework? If students regularly use AI for assignments, how will future employers have confidence in their own knowledge and capabilities? How would they manage fair use knowing that many of the latest tools require paying for a subscription? Or, as the theorist and cultural critic Neil Postman suggests, how does this technology privilege or marginalize students at the intersection of identity (i.e. race, language, culture, disability, age)?
Looking harder at the company’s developing AI tools, Stommel suggests the following questions to get students thinking critically in evaluating the technologies they use.
- Who owns the tool? What is the name of the company and the CEO? What are their politics?
- What does the tool say it does? What does it actually do?
- What flexibility do we have to be anonymous, or to protect our data? Where is data housed and who owns it? What are the implications for in-class use? Will others be able to own our work on these platforms? How might this affect workers at companies where protecting intellectual property is essential?
- How accessible is the tool? For a blind student? For a hearing-impaired student? For a student with a learning disability? For introverts? For extroverts?
Step 6: Determine your path forward
You might consider using the outputs to co-create a Standard of Conduct similar to this list shared by Harvard Business School to guide students in their approach to using AI. This could include recommendations on citing work students generate using AI as well as managing confidential information in line with your school’s Information Security Policy.
Stommel’s vision is that the rise of Generative AI encourages educators to host a larger set of conversations with students. The process of evaluating Generative AI is a journey—not a destination. It’s Stommel’s hope that the steps above will help you transition from the passenger seat to the driver’s seat when using AI in your course. So buckle up: there may be some turbulence on your journey, but we promise it’ll be worth it.
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References
- GenAI In Higher Education: Fall 2023 Update Time for Class Study (2023). Tyton Partners. https://tytonpartners.com/app/uploads/2023/10/GenAI-IN-HIGHER-EDUCATION-FALL-2023-UPDATE-TIME-FOR-CLASS-STUDY.pdf
