Who Owns the Future? is such a book. I think it is a must-read for anyone working with technology or data in the 21st century (i.e. all of us). Unlike most books which have one idea that is repeated over and over again, this one has new ideas on every page.
Who Owns the Future is probably at heart an economics book. It is about how big data infrastructure, and specifically what he calls siren servers - hugely powerful cloud computing infrastructures like Amazon and Google. These siren servers become monopolies that everything else - people and things - revolve around. They can do this because data is now becoming more important than things - and perhaps even people. The answer to the title of the book then becomes apparent - those who own the future are those who have access to the most powerful computation to leverage the most from data.
How can this be? A good example is in healthcare. If you've been to the doctor recently, you'll have noticed that the nurses and usually the doctors spend more time talking to their laptop than to you. Doctors are arguably becoming data entry clerks - or at best a small part in a computation process that converts patients' symptoms into diagnosis codes and treatment plans. The real value comes from those who can sum over all of the doctors making all of their decisions in aggregate and optimize accordingly - for example, which treatment plans work for certain kinds of patients. Perhaps we can even replace the doctor with a machine learning model that learns from tens of thousands of real doctors. The doctors give up their value to the "server", and then the one who owns the server (a large provider network, a health insurance company, or maybe even ultimately Google) reaps the value.
There are many other examples of this we see around us. One recent example was when Amazon opened a bricks-and-mortar bookstore in Seattle. The bookstore can probably beat Barnes and Noble, because Amazon knows exactly what books people want to buy in that square mile of Seattle; they use customer reviews and ratings (given online for free by all of us!) to guide and add value to customers. Lanier goes on to a fascinating journey questioning whether this is desirable, the economic impacts, and impacts on the value of people, and how the issues it brings up have been addressed through philosophy. Lanier ultimately recommends a micropayments system - where the value of data is shared among all of us.
If you just read one book this year, I think this should be the one you read. There are many ways you can use it to impact your thinking. For instance, you could ask: "what would it look like if my company stopped being a [fill in the blank] company, and became a data company?"; you could use it to inform your ethics and the decisions you make in your data science career; you can use it to position your career for the world ten years from now. But make sure you read it sooner rather than later.