Optimistically, the idea could be to push prerequisites to an always-on, ever-available resource. Depending on the major, skills could include organizing papers into outlines, using Excel, or building a computer.

Professors can tailor lectures to narrower topics or advanced, current, or more specialized subjects. There may be less need to have a series of beginning or introductory courses--it's assumed learners will avail themselves.

Pessimistically, AI literacy contributes to further erosion of critical thinking, lazy auto-grading, and inability to construct book-length arguments.

> “how to talk to chat gpt course”?

it's not unrealistic to be selecting for people with strong language skills and the ability to break tasks into discrete components and assemble them into a process. or the skill of being able to define what they do not know.

a lot of what makes a person good with an llm makes them also good at general problem solving.

An AI 101 class taught the way I would want to see it taught would be only a little bit about AI, but far more about philosophy, evolutionary history, and ethics.

You need exposure to philosophical ideas because you need words to be able to think about and describe the similarities and differences between computed language output and a lived experience. You need evolutionary biology to understand that AI is not going to catch up to a billion years of evolutionary progress in the next 6 months. You need ethics because AI is an invitation to ruin yourself through cheating, bullshitting your responsibilities, and generally failing to consider that improving yourself takes work.

But none of that actually requires using AI, which is what makes me suspicious that I would not see eye to eye with Purdue.

What I suspect they're thinking is "every employer wants to hire AI-human centaur employees, so we better make sure are students are the best AI-human hybrids they can be because otherwise there will be no employers who would want them"