As Nobel Prize-winning economist Ronald Coase once cynically observed, "If you torture data long enough, it will confess." Lying with statistics is a time-honored con. In Standard Deviations, economics professor Gary Smith walks us through the various tricks and traps that people use to back up their own crackpot theories. Sometimes, the unscrupulous deliberately try to mislead us. Other times, the well-intentioned are blissfully unaware of the mischief they are committing.

Freakonomics showed how economic calculations can explain seemingly counterintuitive decision-making. Thinking, Fast and Slow helped listeners identify a host of small cognitive errors that can lead to miscalculations and irrational thought. In What the Luck?, statistician and author Gary Smith sets himself a similar goal, and explains - in clear, understandable, and witty prose - how a statistical understanding of luck can change the way we see just about every aspect of our lives.

Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be. Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there.

From the best-selling author of Thinking, Fast and Slow, the co-author of Nudge, and the author of You Are About to Make a Terrible Mistake! comes Noise, a revolutionary exploration of why people make bad judgments, and how to control both noise and cognitive bias.

Today we think statistics are the enemy, numbers used to mislead and confuse us. That’s a mistake, Tim Harford says in The Data Detective. We shouldn’t be suspicious of statistics - we need to understand what they mean and how they can improve our lives: they are, at heart, human behavior seen through the prism of numbers and are often “the only way of grasping much of what is going on around us”.

Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the 17th-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it.

"Correlation does not imply causation". This mantra has been invoked by scientists for decades and has led to a virtual prohibition on causal talk. But today, that taboo is dead. The causal revolution, sparked by Judea Pearl and his colleagues, has cut through a century of confusion and placed causality - the study of cause and effect - on a firm scientific basis.

Today's "machine-learning" systems, trained by data, are so effective that we've invited them to see and hear for us - and to make decisions on our behalf. But alarm bells are ringing. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole - and appear to assess black and white defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And autonomous vehicles on our streets can injure or kill.

For over three decades, Ray Kurzweil has been one of the most respected and provocative advocates of the role of technology in our future. In his classic The Age of Spiritual Machines, he argued that computers would soon rival the full range of human intelligence at its best. Now he examines the next step in this inexorable evolutionary process: The union of human and machine, in which the knowledge and skills embedded in our brains will be combined with the vastly greater capacity, speed, and knowledge-sharing ability of our creations.

This audiobook is about luck, or more precisely, how we perceive and deal with luck in life and business. It is already a landmark work, and its title has entered our vocabulary. In its second edition, Fooled by Randomness is now a cornerstone for anyone interested in random outcomes.

The guru to the gurus at last shares his knowledge with the rest of us. Nobel laureate Daniel Kahneman's seminal studies in behavioral psychology, behavioral economics, and happiness studies have influenced numerous other authors, including Steven Pinker and Malcolm Gladwell. In Thinking, Fast and Slow, Kahneman at last offers his own, first book for the general public. It is a lucid and enlightening summary of his life's work. It will change the way you think about thinking. Two systems drive the way we think and make choices, Kahneman explains....

Richard H. Thaler has spent his career studying the radical notion that the central agents in the economy are humans - predictable, error-prone individuals. Misbehaving is his arresting, frequently hilarious account of the struggle to bring an academic discipline back down to earth - and change the way we think about economics, ourselves, and our world.

From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger - all by the time he was 30. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight. Drawing on his own groundbreaking work, Silver examines the world of prediction, investigating how we can distinguish a true signal from a universe of noisy data.

By the end of on average day in the early 21st century, human beings searching the Internet will amass eight trillion gigabytes of data. This staggering amount of information - unprecedented in history - can tell us a great deal about who we are - the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than 20 years ago seemed unfathomable.

Today, number crunching affects your life in ways you might never imagine. In this lively and groundbreaking new audiobook, economist Ian Ayres shows how today's best and brightest organizations are analyzing massive databases at lightening speed to provide greater insights into human behavior. They are the Super Crunchers.

From the simple to the intricate and the audacious to the absurd, Adam Kucharski reveals the long and tangled history between betting and science and explains why gambling continues to generate insights into luck and decision making today. Covering exploits and ideas from across the globe, he meets the teams behind hedge funds that capitalize on inaccurate sports betting odds and explains how PhD-level pundits are using methods originally developed for the US nuclear program to predict sports results.

The widening gap between rich and poor means dealing with one big, uncomfortable truth: If you're not at the top, you're at the bottom. The global labor market is changing radically thanks to growth at the high end and the low. About three quarters of the jobs created in the United States since the great recession pay only a bit more than minimum wage. Still, the United States has more millionaires and billionaires than any country ever, and we continue to mint them.

A fascinating guided tour of the complex, fast-moving, and influential world of algorithms - what they are, why they’re such powerful predictors of human behavior, and where they’re headed next. Algorithms exert an extraordinary level of influence on our everyday lives - from dating websites and financial trading floors, through to online retailing and internet searches - Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola.

It used to be that to diagnose an illness, interpret legal documents, analyze foreign policy, or write a newspaper article you needed a human being with specific skills - and maybe an advanced degree or two. These days, high-level tasks are increasingly being handled by algorithms that can do precise work not only with speed but also with nuance. These "bots" started with human programming and logic, but now their reach extends beyond what their creators ever expected.

Our increasing reliance on technology and the Internet has opened a window for mathematicians and data researchers to gaze through into our lives. Using the data they are constantly collecting about where we travel, where we shop, what we buy, what interests us, they can begin to predict our daily habits, and increasingly we are relinquishing our decision making to algorithms - are we giving up this up too easily?

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.

The Money Formula takes you inside the engine room of the global economy to explore the little-understood world of quantitative finance, and show how the future of our economy rests on the backs of this all-but-impenetrable industry. Written not from a post-crisis perspective - but from a preventative point of view - this book traces the development of financial derivatives from bonds to credit default swaps, and shows how mathematical formulas went beyond pricing to expand their use to the point where they dwarfed the real economy.

Many people today are so dazzled by the long-term potential for artificial intelligence that they overlook the much clearer and more immediate potential for a new form of "collective intelligence": the intelligence of groups of people and computers working together. In Superminds, Thomas Malone explains what we need to do to take advantage of this potential. Groundbreaking and utterly fascinating, Superminds will change the way you work - both with others and with computers - for the better.

"Correlation does not imply causation". This mantra has been invoked by scientists for decades and has led to a virtual prohibition on causal talk. But today, that taboo is dead. The causal revolution, sparked by Judea Pearl and his colleagues, has cut through a century of confusion and placed causality - the study of cause and effect - on a firm scientific basis.

Picture an early scene from The Wizard of Oz: Dorothy hurries home as a tornado gathers in what was once a clear Kansas sky. Hurriedly, she seeks shelter in the storm cellar under the house, but, finding it locked, takes cover in her bedroom. We all know how that works out for her.Many investors these days are a bit like Dorothy, putting their faith in something as solid and trustworthy as a house (or, say, real estate). But market disruptions - storms - seem to arrive without warning, leaving us little time to react.

When most of us think about artificial intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that artificial intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways the future people dreamed of at the World's Fair in the 1960s is already here. We're teaching our machines how to think like humans, and they're learning at an incredible rate.

Coal, iron ore, and oil were the key productive assets that fueled the Industrial Revolution. Today data is the vital raw material of the information economy. The explosive abundance of this digital asset, more than doubling every two years, is creating a new world of opportunity and challenge. Data-ism is about this next phase, in which vast, Internet-scale data sets are used for discovery and prediction in virtually every field. It is a journey across this emerging world with people, illuminating narrative examples, and insights.

Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. Sharon Bertsch McGrayne here explores this controversial theorem and the human obsessions surrounding it.

How important is luck in economic success? No question more reliably divides conservatives from liberals. As conservatives correctly observe, people who amass great fortunes are almost always talented and hardworking. But liberals are also correct to note that countless others have those same qualities yet never earn much. In recent years, social scientists have discovered that chance plays a much larger role in important life outcomes than most people imagine.

Futurists insist that AI will soon eclipse the capacities of the most gifted human mind. What hope do we have against superintelligent machines? But we aren't really on the path to developing intelligent machines. In fact, we don't even know where that path might be. Erik Larson takes us on a tour of the landscape of AI to show how far we are from superintelligence and what it would take to get there.

In their bestselling first book, Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction, they go deeper, examining the most basic unit of analysis: the decision. The authors explain that the two key decision-making ingredients are prediction and judgment, and we perform both together in our minds, often without realizing it.

How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times best-selling author Martin Ford uncovers the truth behind these questions from some of the brightest minds in the artificial intelligence community.

High-tech innovations are created at a dazzling speed, and it all points to a world that is getting faster at a dizzying pace. Azeem Azhar knows this better than most. Over the last three decades, he has founded companies bought by Amazon and Microsoft, served as the Economist’s first ever internet correspondent, and created a leading international tech newsletter and podcast, the Exponential View. Now, Azhar offers a revelatory new model for understanding how technology is changing the world.

Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration.

In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art.

Freakonomics showed how economic calculations can explain seemingly counterintuitive decision-making. Thinking, Fast and Slow helped listeners identify a host of small cognitive errors that can lead to miscalculations and irrational thought. In What the Luck?, statistician and author Gary Smith sets himself a similar goal, and explains - in clear, understandable, and witty prose - how a statistical understanding of luck can change the way we see just about every aspect of our lives.

Artificial intelligence powers Google's search engine, enables Facebook to target advertising, and allows Alexa and Siri to do their jobs. AI is also behind self-driving cars, predictive policing, and autonomous weapons that can kill without human intervention. These and other AI applications raise complex ethical issues that are the subject of ongoing debate. This volume in the MIT Press Essential Knowledge series offers an accessible synthesis of these issues.

Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact.

The deep-learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep-learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.

There's no reason your money should be sitting in a bank account. By learning value investing, you can reap the rewards of consistent, reliable gains that can make you a millionaire by the time you retire. Don't just work for your money - put your money to work for you and retire in style.