Prediction Machines: The Simple Economics of Artificial Intelligence

Very good (5* for narrow audience) if niche book on the economics of AI/machine learning.

By narrow audience and mean for business leaders, decision makers, and people learning more on the subject, could be students or economists. It is explicitly aimed at them not a lay audience. It is not a computer science book, rather an economics book on the the impact of the new technology of cheap prediction - wonky but not overly complex or jargon filled. Well structured, some may just read for relevent sections of pushed for time.

It is very good in avoiding buzz and bluster around these tools, seeing them just as that, though like the computing revolution that made computation cheap, this economic change of scale will push profound changes to our lives.

It is also excellent in detailing what won't change and where these technologies have clear weaknesses. In particular better machine prediction will lead to a premium on human judgment in many spaces. That task is often seperated out with good reason - for now!

There are many real world examples and stories that enliven the text, the writers run a AI based resource for new companies so have great access. Interesting that so many start ups are predicated on a single application, though the authors explain the real value is in powering change through the entire work flow.

Interesting that the big tech companies are "AI first" meaning that they prioritize it over even short term customer satisfaction, the big goal is too important to slow development even if that means some of us switch services.

Good and balanced on the future, with the new world being changed by AI but making a clear distinction with any possible development of GAI, that would be different gravy. Good sections on privacy, China, and the EU.

As with all good books references Taversky and Khaneman :)