“[A] rigorous yet surprisingly accessible explanation of how AI actually works, coupled with a keen interrogation of its strengths and weaknesses...As an explainer, AIQ is impeccable, brilliantly making a complicated subject understandable. And while it offers a glowing picture of how AI can get things right, it also clearly lays out how things can go wrong.” —Strategy + Business
"Entertaining and persuasive. The book’s goal is to explain how artificial intelligence delivers its incredible results, and Polson and Scott are like a pair of excitable mechanics lifting up the bonnet of a sports car. This is a passionate book, and it is a model of how to make data science accessible and exciting." —The Sunday Times (UK)
"Grounding AI in tried-and-true methods makes it seem less alien: Computers are simply faster ways to solve familiar problems. Hence the book’s title, a portmanteau of AI and IQ--the point being that we need both." —Wall Street Journal
"Nick Polson and James Scott take us under the hood of AI and data science, showing that behind most algorithms is the story of a person trying to solve a problem and make the world better. The result is an engaging, optimistic vision of an age in which computers have become a pervasive, influential presence in every aspect of life." —Michael J. Casey, senior advisor at MIT Media Lab's Digital Currency Initiative, and co-author of The Truth Machine
"At last, a book on the ideas behind AI and data science by people who really understand data. Cutting through the usual journalistic puff and myths, they clearly explain the underlying ideas behind the way that loads of data are being harnessed to build the algorithms that can carry out such extraordinary feats. But they are also clear about the limitations and potential risks of these algorithms, and the need for society to scrutinise and even regulate their use. A real page-turner, with fine stories and just enough detail: I learned a lot." —David Spiegelhalter, Winton Professor of the Public Understanding of Risk, University of Cambridge
NICK POLSON is Professor of Econometrics and Statistics at the Chicago Booth School of Business. He does research on machine intelligence and deep learning, and is a frequent speaker. Polson lives in Chicago.
JAMES SCOTT is Associate Professor of Statistics at the University of Texas at Austin. He is a statistician, data scientist, and has worked with clients across many industries to help them understand the power of data. Scott lives in Austin with his wife.