How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more. How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance? How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions. Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender? César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.

'Is it fair for a judge to increase a defendant's prison time on the basis of an algorithmic score that predicts the likelihood that he will commit future crimes? Many states now say yes, even when the algorithms they use for this purpose have a high error rate, a secret design, and a demonstratable racial bias. The former federal judge Katherine Forrest, in her short but incisive When Machines Can Be Judge, Jury, and Executioner, says this is both unfair and irrational ...' See full reviewJed S RakoffUnited States District Judge for the Southern District of New YorkNew York Review of Books This book explores justice in the age of artificial intelligence. It argues that current AI tools used in connection with liberty decisions are based on utilitarian frameworks of justice and inconsistent with individual fairness reflected in the US Constitution and Declaration of Independence. It uses AI risk assessment tools and lethal autonomous weapons as examples of how AI influences liberty decisions. The algorithmic design of AI risk assessment tools can and does embed human biases. Designers and users of these AI tools have allowed some degree of compromise to exist between accuracy and individual fairness.Written by a former federal judge who lectures widely and frequently on AI and the justice system, this book is the first comprehensive presentation of the theoretical framework of AI tools in the criminal justice system and lethal autonomous weapons utilized in decision-making. The book then provides a comprehensive explanation as to why, tracing the evolution of the debate regarding racial and other biases embedded in such tools. No other book delves as comprehensively into the theory and practice of AI risk assessment tools.

As technology races ahead, what will people do better than computers? What hope will there be for us when computers can drive cars better than humans, predict Supreme Court decisions better than legal experts, identify faces, scurry helpfully around offices and factories, even perform some surgeries, all faster, more reliably, and less expensively than people? It’s easy to imagine a nightmare scenario in which computers simply take over most of the tasks that people now get paid to do. While we’ll still need high-level decision makers and computer developers, those tasks won’t keep most working-age people employed or allow their living standard to rise. The unavoidable question—will millions of people lose out, unable to best the machine?—is increasingly dominating business, education, economics, and policy. The bestselling author of Talent Is Overrated explains how the skills the economy values are changing in historic ways. The abilities that will prove most essential to our success are no longer the technical, classroom-taught left-brain skills that economic advances have demanded from workers in the past. Instead, our greatest advantage lies in what we humans are most powerfully driven to do for and with one another, arising from our deepest, most essentially human abilities—empathy, creativity, social sensitivity, storytelling, humor, building relationships, and expressing ourselves with greater power than logic can ever achieve. This is how we create durable value that is not easily replicated by technology—because we’re hardwired to want it from humans. These high-value skills create tremendous competitive advantage—more devoted customers, stronger cultures, breakthrough ideas, and more effective teams. And while many of us regard these abilities as innate traits—“he’s a real people person,” “she’s naturally creative”—it turns out they can all be developed. They’re already being developed in a range of far-sighted organizations, such as: • the Cleveland Clinic, which emphasizes empathy training of doctors and all employees to improve patient outcomes and lower medical costs; • the U.S. Army, which has revolutionized its training to focus on human interaction, leading to stronger teams and greater success in real-world missions; • Stanford Business School, which has overhauled its curriculum to teach interpersonal skills through human-to-human experiences. As technology advances, we shouldn’t focus on beating computers at what they do—we’ll lose that contest. Instead, we must develop our most essential human abilities and teach our kids to value not just technology but also the richness of interpersonal experience. They will be the most valuable people in our world because of it. Colvin proves that to a far greater degree than most of us ever imagined, we already have what it takes to be great.

This book is a history of artificial intelligence, that audacious effort to duplicate in an artifact what we consider to be our most important property—our intelligence. It is an invitation for anybody with an interest in the future of the human race to participate in the inquiry.

"Hidalgo has made a bold attempt to synthesize a large body of cutting-edge work into a readable, slender volume. This is the future of growth theory." -- Financial Times What is economic growth? And why, historically, has it occurred in only a few places? Previous efforts to answer these questions have focused on institutions, geography, finances, and psychology. But according to MIT's antidisciplinarian Cér Hidalgo, understanding the nature of economic growth demands transcending the social sciences and including the natural sciences of information, networks, and complexity. To understand the growth of economies, Hidalgo argues, we first need to understand the growth of order. At first glance, the universe seems hostile to order. Thermodynamics dictates that over time, order-or information-disappears. Whispers vanish in the wind just like the beauty of swirling cigarette smoke collapses into disorderly clouds. But thermodynamics also has loopholes that promote the growth of information in pockets. Although cities are all pockets where information grows, they are not all the same. For every Silicon Valley, Tokyo, and Paris, there are dozens of places with economies that accomplish little more than pulling rocks out of the ground. So, why does the US economy outstrip Brazil's, and Brazil's that of Chad? Why did the technology corridor along Boston's Route 128 languish while Silicon Valley blossomed? In each case, the key is how people, firms, and the networks they form make use of information. Seen from Hidalgo's vantage, economies become distributed computers, made of networks of people, and the problem of economic development becomes the problem of making these computers more powerful. By uncovering the mechanisms that enable the growth of information in nature and society, Why Information Grows lays bear the origins of physical order and economic growth. Situated at the nexus of information theory, physics, sociology, and economics, this book propounds a new theory of how economies can do not just more things, but more interesting things.

A leading artificial intelligence researcher lays out a new approach to AI that will enable people to coexist successfully with increasingly intelligent machines.

Explores universal questions about humanity's capacity for living and thriving in the coming age of sentient machines and AI, examining debates from opposing perspectives while discussing emerging intellectual diversity and its potential role in enabling a positive life.

A playful, profound book that is not only a testament to one man's efforts to be deemed more human than a computer, but also a rollicking exploration of what it means to be human in the first place. “Terrific. ... Art and science meet an engaged mind and the friction produces real fire.” —The New Yorker Each year, the AI community convenes to administer the famous (and famously controversial) Turing test, pitting sophisticated software programs against humans to determine if a computer can “think.” The machine that most often fools the judges wins the Most Human Computer Award. But there is also a prize, strange and intriguing, for the “Most Human Human.” Brian Christian—a young poet with degrees in computer science and philosophy—was chosen to participate in a recent competition. This

From the Nobel Prize-winning author of Thinking, Fast and Slow and the coauthor of Nudge, a revolutionary exploration of why people make bad judgments and how to make better ones—"a tour de force” (New York Times). Imagine that two doctors in the same city give different diagnoses to identical patients—or that two judges in the same courthouse give markedly different sentences to people who have committed the same crime. Suppose that different interviewers at the same firm make different decisions about indistinguishable job applicants—or that when a company is handling customer complaints, the resolution depends on who happens to answer the phone. Now imagine that the same doctor, the same judge, the same interviewer, or the same customer service agent makes different decisions depending on whether it is morning or afternoon, or Monday rather than Wednesday. These are examples of noise: variability in judgments that should be identical. In Noise, Daniel Kahneman, Olivier Sibony, and Cass R. Sunstein show the detrimental effects of noise in many fields, including medicine, law, economic forecasting, forensic science, bail, child protection, strategy, performance reviews, and personnel selection. Wherever there is judgment, there is noise. Yet, most of the time, individuals and organizations alike are unaware of it. They neglect noise. With a few simple remedies, people can reduce both noise and bias, and so make far better decisions. Packed with original ideas, and offering the same kinds of research-based insights that made Thinking, Fast and Slow and Nudge groundbreaking New York Times bestsellers, Noise explains how and why humans are so susceptible to noise in judgment—and what we can do about it.

A call-to-arms about the broken nature of artificial intelligence, and the powerful corporations that are turning the human-machine relationship on its head. We like to think that we are in control of the future of "artificial" intelligence. The reality, though, is that we -- the everyday people whose data powers AI -- aren't actually in control of anything. When, for example, we speak with Alexa, we contribute that data to a system we can't see and have no input into -- one largely free from regulation or oversight. The big nine corporations -- Amazon, Google, Facebook, Tencent, Baidu, Alibaba, Microsoft, IBM and Apple--are the new gods of AI and are short-changing our futures to reap immediate financial gain. In this book, Amy Webb reveals the pervasive, invisible ways in which the foundations of AI -- the people working on the system, their motivations, the technology itself -- is broken. Within our lifetimes, AI will, by design, begin to behave unpredictably, thinking and acting in ways which defy human logic. The big nine corporations may be inadvertently building and enabling vast arrays of intelligent systems that don't share our motivations, desires, or hopes for the future of humanity. Much more than a passionate, human-centered call-to-arms, this book delivers a strategy for changing course, and provides a path for liberating us from algorithmic decision-makers and powerful corporations.