The book Silicon Dreams: Information, Man, and Machine by Robert Lucky is where I got mine. It’s a pop science book that explores the theoretical limits of human computer interaction using information theory. It’s written to do exactly the thing you’re asking for: Convey deep intuitions about information theory using a variety of practical examples without getting bogged down in math equations or rote exercises.
Covers topics like:
What are the bottlenecks to human information processing?
What is Shannon’s theory of information and how does it work?
What input methods exist for computers and what is their bandwidth/theoretical limit?
What’s the best keyboard layout?
How do (contemporary, the book was written in 1989) compression methods work?
How fast can a person read, and what are the limits of methods that purport to make it faster?
If an n-gram Markov chain becomes increasingly English like as it’s scaled, does that imply a sufficiently advanced Markov chain is indistinguishable from human intelligence?
A lot of his question is to what extent AI methods can bridge the fundamental gaps between human and electronic computer information processing. As a result he spends a lot of time breaking down the way that various GOFAI methods work in the context of information theory. Given the things you want to understand it for, this seems like it would be very useful to you.
The book Silicon Dreams: Information, Man, and Machine by Robert Lucky is where I got mine. It’s a pop science book that explores the theoretical limits of human computer interaction using information theory. It’s written to do exactly the thing you’re asking for: Convey deep intuitions about information theory using a variety of practical examples without getting bogged down in math equations or rote exercises.
Covers topics like:
What are the bottlenecks to human information processing?
What is Shannon’s theory of information and how does it work?
What input methods exist for computers and what is their bandwidth/theoretical limit?
What’s the best keyboard layout?
How do (contemporary, the book was written in 1989) compression methods work?
How fast can a person read, and what are the limits of methods that purport to make it faster?
If an n-gram Markov chain becomes increasingly English like as it’s scaled, does that imply a sufficiently advanced Markov chain is indistinguishable from human intelligence?
A lot of his question is to what extent AI methods can bridge the fundamental gaps between human and electronic computer information processing. As a result he spends a lot of time breaking down the way that various GOFAI methods work in the context of information theory. Given the things you want to understand it for, this seems like it would be very useful to you.