Generative Artificial Intelligence (GenAI): Learning GenAI

Five Key Skills Students Need to Harness Generative AI

• Problem formulation is the thinking you do before you attempt to prompt the AI; it’s outlining the focus, scope, and boundaries of a problem. Simply put, without a deep understanding of the problem to be solved, your prompts won’t be effective—no matter how well they’re phrased for AI. 
• Exploration. With so many new AI products emerging every week, it is increasingly important and difficult to identify the most suitable tool for the task at hand. To be able to do this, students must be familiar with major generative AI tools such as ChatGPT and Stable Diffusion, and remain motivated and curious to keep up with whatever generative AI tools and enhancements are coming next.

• Experimentation. Given the ever-evolving nature of these tools, one effective way to keep up is to just continue experimenting with them. Experimentation involves a hands-on interaction with the AI, a process of trial and error, and an assessment of the outcomes.

• Critical thinking. Generative AI tools sometimes produce inaccurate or biased content—arguably their greatest limitation. Critical thinking helps identify and mitigate this limitation. It’s about applying a disciplined, objective lens to evaluate the information or arguments generated, which also deepens students’ learning.

• Willingness to reflect. Engaging with generative AI systems can sometimes stir emotions, particularly when the tools are used for tasks closely tied to one’s identity or self-worth. Adopting a reflective practice can help students understand these emotional reactions. Although it shares certain elements with critical thinking, reflection focuses on examining one’s personal thoughts, feelings, beliefs, and actions, as opposed to the AI’s output.

A Framework to Develop These Key Generative AI Skills: PAIR

1. Problem formulation: Students define the problem or challenge they want to solve.

2. AI tool selection: Students choose the best generative AI tools to help them with their problem. They learn how to explore, compare, and evaluate different generative AI tools and their features.

3. Interaction: Students use the generative AI tools to solve their problem. They experiment with different inputs and outputs and see how the generative AI tools affect their problem-solving process and outcome.

4. Reflection: Students assess and report their experiences with the generative AI tools