I think @jeffjarvis takes the right lessons from media history into the ChatGPT/LLM debates in his response to Ted Chiang

Looking back at historical technological shifts, we see folks worried about potential harms—of, say, the printing press. But our lesson isn’t "look how silly they were!" because in every case they were partly right—the press did contribute to more misinformation, even violence

https://medium.com/whither-news/journalism-is-lossy-compression-86380f0bdb50

Journalism is Lossy Compression - Whither news? - Medium

There has been much praise in human chat — Twitter — about Ted Chiang’s New Yorker piece on machine chat — ChatGPT. Because New Yorker; because Ted Chiang. He makes a clever comparison between lossy…

Whither news?
but as @jeffjarvis also shows, those same histories show it takes time & experimentation to understand what a new technology will actually change & what guardrails we need to create around it—there are zero cases where we fully understood a new medium & could manage it from the outset, because a medium’s eventual shape is completely opaque in the moment of its creation—a primary reason to study these histories is to learn to evaluate our own shifts *slightly* more efficiently
@ryancordell
Thank you, yes. I feel as if you've already read my upcoming book. ;-)
@jeffjarvis I often describe my classes as "a history of technological moral panics" so this is territory I explore quite a lot!
@ryancordell
Well, that starts to the next book I'm starting to write now. I'd love to see you syllabi and readings, if you're willing.
@jeffjarvis of course! Most of my materials online are linked from here https://ryancordell.org/teaching/ —the most pertinent classes would be "Technologies of Text" & the graduate "Reading Machines" &/or "BookLab"
teaching | Ryan C. Cordell

Course websites and OA teaching materials.