Learning and AI/LLMs - Why do we need to know or teach anything anymore?

The fall semester is about to begin at my university, and I'm going to be teaching undergraduate statistical and thermal physics.  This is a course I've taught before, last full term in 2019, and the mass availability of large language models and generative AI tools have changed the world in the interim.  We've all seen the headlines and articles about how some of these systems can be very good at solving traditional homework and exam problems.  Many of these tools are capable of summarizing written material and writing essays that are very readable.  Higher education is wrestling with the essential question:  What is the right working relationship between students, teachers, and these tools, one that benefits and actually educates students (both about subject matter and the use of these tools)?  Personalized individual AI tutoring seems like it could be great for teaching huge numbers of people.  Conversely, if all we are doing is teaching students to copy-paste assignments into the homework-answer-machine, clearly we are failing students at multiple levels.  

The quote in the image here (from Kathy Hepinstall Parks) is one that I came across this week that originates in the FAQ from a writers workshop.  For my purposes I could paraphrase:  Why should we learn physics (or any other science or engineering discipline) when a machine already knows the formalism and the answers?  On some level, this has been a serious question since the real advent of search engines.  The sum total of human knowledge is available at a few keystrokes.  Teaching students just rote recall of facts is approaching pointless (though proficiency can be hugely important in some circumstances - I want a doctor who can diagnose and treat ailments without having to google a list of my symptoms.).

My answer to this question is layered.  First, I would argue that beyond factual content we are teaching students how to think and reason.  This is and I believe will remain important, even in an era when AI tools are more capable and reliable than at present.  I like to think that there is some net good in training your brain to work hard, to reason your way through complicated problems (in the case of physics, formulating and then solving and testing models of reality).  It's hard for me to believe that this is poor long-term strategy.  Second, while maybe not as evocative as the way creative expression is described in the quote, there is real accomplishment (in your soul?) in actually learning something yourself.  A huge number of people are better at playing music than I am, but that doesn't mean it wasn't worthwhile to me to play the trumpet growing up.  Overworked as referencing Feynman is, the pleasure of finding things out is real.  

AI/LLMs can be great tools for teachers.  There are several applet-style demos that I've put off making for years because of how long it would take for me to code them up nicely.  With these modern capabilities, I've been able to make some of these now, in far less time than it would otherwise have taken, and students will get the chance to play with them.  Still, the creativity involved in what demos to make and how they should look and act was mine, based on knowledge and experience.  People still have a lot to bring to the process, and I don't think that's going to change for a very long time.