Who Should Use GenAI and for What?

"That's a tough question, with lots of dimensions to it*, but two key factors to answering it are: who is using GenAI and what they are doing with it. I created a graphic to illustrate these factors and provide some guidance. The y-axis is a continuum from "novice to expert." The research on expertise is clear: Most people can be an expert in only one or two areas, so for most topics, most people fall somewhere between novice and expert."

"The "learning to performance" axis is the other continuum, and it captures what kind of goal a person has. The recommended ways to use GenAI differ if my goal is to learn new knowledge or skills versus to simply perform a task I already know how to do well or one that I just need to complete (e.g., how to update my smartphone's system software), rather than learn deeply."

Two primary factors determine appropriate Generative AI use: the user's level of expertise and the user's goal along a learning-to-performance continuum. Expertise typically spans only one or two domains for most people, placing them between novice and expert across topics. Tasks aimed at performance or simple completion generally pose lower risk when assisted by GenAI, while tasks aimed at deep learning carry higher risk, particularly for novices. Errors from GenAI are especially harmful in early learning because misconceptions are difficult to correct. Responsible GenAI use requires aligning technology choices with specific learning goals and users' expertise levels.

Read at Psychology Today