Part of the reason I bought this book was to see if I can still understand current issues in computer science, 30 years after I earned my M.S. in C.S. Back then the hot book in the field was The Soul of a New Machine, by Tracy Kidder, which I very much enjoyed. But time moves on, and some issues that were hard then, such as the four color problem, have been solved since. Artificial Intelligence, on the other hand, has not. Back in 1989, I fully expected some computer to have passed the Turing Test by now, but doing so has proved more difficult than then expected, although computers now routinely trounce human experts in even the most complex games, such as Chess and Go.
Thus, I chose this book both to see why we aren't there yet, and to see if I can still even follow the current arguments.
Like The Soul of a New Machine, this book is written to both be accessible to a literate general audience and rigorous enough for specialists. In my opinion, it entirely succeeds, although my son is better than me at math, so I skimmed some of the math-heavy discussions, as my interest is more in the philosophical issues and predictions about coming developments. In that, I was completely satisfied, as just when I was thinking of docking a star because the discussion was getting too deep into the weeds of particular implementations of machine learning, the author returned to a very interesting discussion of what it all means for our current and future society, complete with useful predictions about what jobs are still likely to be around in twenty years, and the inevitability of voters eventually approving a guaranteed basic income for those no longer able to be employed due to robots and computers doing ever more of the work previously done by humans.
I was glad to see the author also explored the dark side of all this - the potential for it to control people rather than to free them, and his suggestions on how to make sure the changes achieve good for all rather than for only a few. I was particularly interested in his conclusion that we needn't worry about machines ruling over us because even the best machine learners lack will, doing only what they have been programmed to do. I also like his idea that although machine learning may be the next step in evolution, it will be one taken with rather than instead of us, with humans branching out along with computers in ways not predictable yet, but likely to be beneficial.
Overall, a very good and very hopeful read, and comforting to still be able to follow along after a full career since grad school and years of retirement.