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Generative AI

Information about Generative AI tools and their use in and outside of the classroom

CLEAR Framework for Prompts

Generative AI is particularly sensitive to prompts. This means that the way you frame a request can impact the type of response you'll receive. Especially when using a tool such as ChatGPT, you need to be intentional about what you're asking for. This can help reduce issues such as misinformation and hallucination. In drafting prompts, the CLEAR framework developed by Leo S. Lo is particularly helpful.

The CLEAR Framework suggests that when working with AI your prompts should be:

Concise: Adding too much information in your prompts can affect what a tool might focus on.

  • Example: “Explain the main arguments of Gender Trouble by Judith Butler” vs. “Can you please give me a detailed explanation of Judith Butler’s main arguments in their seminal book, Gender Trouble? Thank you.” 

Logical: When writing a prompt, make sure that it follows a logical flow, especially when the prompt involves relationships between concepts or sequences.

  • “Provide a list of common objections to the adoption of AI tools in education. Then, respond to these objections by discussing how AI tools can be implemented in the classroom effectively” vs. “List common objections to AI in education and how it can be used effectively.”

Explicit: Asking broad questions can lead to less precise answers. When creating a prompt, include relevant details that can help specify the type of response you want.

  • Example: “Identify five strategies for mitigating the risk of sepsis in patients admitted into the hospital.” vs “How to prevent sepsis” 

Adaptive: When a prompt doesn’t get the response, you were looking for, be willing to adapt. A great thing about generative AI tools is that they often have a memory of previous prompts. You can use this to your advantage by asking follow-up questions or correcting and critiquing the tool’s response.

Reflective: At the end of a prompt, reflect on the tool’s response. What worked? What didn’t work? Taking the time after using a tool to reflect on responses can help you draft better prompts in the future and inform what types of inquiry work best with the tool. 

Evaluating Responses

The last component of the CLEAR framework, Reflective, is key to being a responsible user of generative AI tools. Responses should be evaluated for accuracy, precision, and the potential for bias. Below are some guiding questions you can use when evaluating a tool and its response. 

  • What is the purpose of the tool? 
  • Who created the tool? 
  • What was the tool trained on? 
  • Is it free? If so, why? 
  • What is the goal of the response? 
  • In what perspective was it written from? 
  • Are sources cited? If so, are they accurate? 
  • How could bias have been introduced?