This book is as old as sin, in computational terms. As such, it's obviously horribly outdated, but it's a really great snapshot of the 70s and 80s AI movement.
I read this mainly out of a sense of bloody-mindedness, having bought this over thirty years ago whilst at university when I only read the sections relevant to my course, since when it’s sat on my bookshelf. It’s a bit of a long haul through a fairly dry desert for much of the time, but it does give you a sense of how challenging producing even the first building blocks of technology like ChatGPT is. In that respect, it’s not totally redundant. The book loosens its tie, if not exactly lets its hair down, in the final section with now antique speculations about the (then) future, many of which are laughably wrong (people will become politically mute, whereas many feel disenfranchised and angry) or plain over-ambitions (a database of tacit knowledge in a few hundred entries) despite the preceding 500 pages explaining how difficult it all is.
This is one of the classics and still worth a read. The author is no lightweight and the subject is carefully dissected and considered. A part of which is how can we write programs that do symbolic knowledge and reasoning. Even the revised edition comes from the 80s. I don't think the author even mentions connectionist models and pattern recognition approaches to machine learning. Instead we get a deep analysis from a psychologist/philosopher of how programs could possibly learn and think. And a thorough coverage of some successful examples from the time. None of the more recent hype and hysteria.
I would rate this a 4.9, right after Singh's FERMAT'S LAST THEOREM.. Review of a preview copy provided at no charge.
They say if you can't make a subject understandable you don't understand it well enough. Based on what I read, Ms Boden definitely understands artificial intelligence.
The book is exactly what you would expect if you were in your teens and your parents had asked your favorite aunt/uncle (who taught at Princeton or MIT) to get you interested in a career in computer science. While the reader will probably not end up registering for a new college major, they will benefit from reading this. If they are young and starting out, they will enter the field with an excellent perspective and background with which to approach the technical material ahead of them. If they are not, they will have a much better grasp of what they are reading in the news and investment opportunities posted all the time. They will also be able to enjoy a conversation with someone in the field by better understanding and the ability to ask intelligent questions.
Really, really ancient, in technological terms. But if for some reason you wanted to know about the prevailing thought when this book was written, I can see reading it. It's written well and the prose seems engaging.