While I agree that ChatGPT and other similar mediums have provided users with a tremendous amount of information is it still not up to the human counterpart to distill that information down to something specific? Something usable and actionable?

Effective prompt engineering can assist with those efforts, of course, yet still the human counterpart must provide the parameter of the queries and distill the information down to a workable solution. One idea I am personally struggling with is recognizing that every thought that pops into my head may not be true. Here, too, AI generated ideas may or may not be true and further human interaction can help discard the informational flotsam.

Learning is the goal, of course. I believe strongly that if Americans are going to be employable in a global economy then we cannot leave out amazing tools like Generative AI. Other nations are doing things better. What can we learn about those educational systems that work well and we're not using? Why not? How can we make the entire system work better without leaving learners behind?

My hope, of course, is to encourage equitable educational access to all learner populations. The new ideas and new opportunities are coming in so fast we have to make sure we are scaling up systems so that a new way of learning is not rolled out every semester. I am curious to know hoe GenAI can help with that.

I found this statement to be particularly interesting. While I support AI and its collaboration in education, I also believe that some walls need to be created to help distinguish between AI generated ideas and human ones. Then I asked myself how are AI generated ideas NOT human?

There is certainly a need for a collaboration where both AI generated ideas can exist along side human ideas and perspectives. These parameters need to be in place soon as quantum computing is here already and the potential for an explosive library of new information is on the horizon, so too, the explosive potential for harm.