7 books to demystify Artificial Intelligence for product leaders of tomorrow

Alexander Hipp
PM Library
Published in
5 min readFeb 27, 2019

The impact of Artificial intelligence (AI) on our personal and business lives is dramatic today and will be transformative tomorrow. It enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision making — and it is already transforming every walk of life.

These 7 books demystify the complexity of AI and enable product leaders to understand what it all means. Here’s the spoiler: we don’t need to fear the robot overlords just yet, but we do need to decide how to use AI to build great products now.

Source: Unsplash.com

Prediction Machines

The Simple Economics of Artificial Intelligence
by Ajay Agrawal, Joshua Gans & Avi Goldfarb

Why read?

In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policymakers, investors, and entrepreneurs.

“What does AI mean for your business? Read this book to find out.”
— Hal Varian, Chief Economist, Google

320 pages, Belknap Press 2019

Get this book

Applied Artificial Intelligence

A Handbook For Business Leaders
by Mariya Yao, Adelyn Zhou & Marlene Jia

Why read?

Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. If you want to drive innovation by combining data, technology, design, and people to solve real problems at an enterprise scale, this is your playbook.

175 pages, Topbots 2018

Get this book

Data Smart

Using Data Science to Transform Information into Insight
by John W. Foreman

Why read?

Most people are approaching data science all wrong. Here’s how to do it right. Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that’s done within the familiar environment of a spreadsheet.

“When Mr. Foreman interviewed for a job at my company, he arrived dressed in a ‘Kentucky Colonel’ kind of suit and spoke about nonsensical things like barbecue, lasers, and orange juice pulp. Then, he explained how to de-mystify and solve just about any complex ‘big data’ problem in our company with simple spreadsheets. No server clusters, mainframes, or Hadoop-a-ma-jigs. Just Excel. I hired him on the spot. After reading this book, you too will learn how to use math and basic spreadsheet formulas to improve your business or, at the very least, how to trick senior executives into hiring you as their data scientist.”
— Ben Chestnut, Founder & CEO of MailChimp

All rights reserved John W. Foreman

432 pages, Wiley 2013

Get this book

Data Science for Business

What You Need to Know about Data Mining and Data-Analytic Thinking
by Foster Provost & Tom Fawcett

Why read?

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

“A must-read resource for anyone who is serious about embracing the opportunity of big data.”
— Craig Vaughan, Global Vice President at SAP

414 pages, O’Reilly Media 2013

Get this book

The Creativity Code

Art and Innovation in the Age of AI
by Marcus du Sautoy

Why read?

Can a well-programmed machine do anything a human can―only better? Complex algorithms are choosing our music, picking our partners, and driving our investments. They can navigate more data than a doctor or lawyer and act with greater precision. For many years we’ve taken solace in the notion that they can’t create. But now that algorithms can learn and adapt, does the future of creativity belong to machines, too?

While most recent books on AI focus on the future of work, The Creativity Code moves us to the forefront of creative new technologies and offers a more positive and unexpected vision of our future cohabitation with machines. It challenges us to reconsider what it means to be human―and to crack the creativity code.

320 pages, Belknap Press 2019

Get this book

Designing Agentive Technology

AI That Works for People
by Christopher Noessel

Why read?

Advances in narrow artificial intelligence make possible agentive systems that do things directly for their users (like, say, an automatic pet feeder). They deliver on the promise of user-centred design, but present fresh challenges in understanding their unique promises and pitfalls. Designing Agentive Technology provides both a conceptual grounding and practical advice to unlock agentive technology’s massive potential.

All rights reserved Talks at Google

240 pages, Rosenfeld Media 2017

Get this book

Data Science for Executives

Leveraging Machine Intelligence to Drive Business ROI
by Nir Kaldero

Why read?

Leaders don’t have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you’re ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.

184 pages, Lioncrest Publishing 2018

Get this book

Do you know any great data science books for product leaders that we missed? Let us know in the comments. #sharingiscaring

--

--