Automating Humanity

Automating Humanity is the shocking and eye-opening new manifesto from international award-winning designer Joe Toscano that unravels and lays bare the power agendas of the world's greatest tech titans in plain language, and delivers a fair warning to policymakers, civilians, and industry professionals alike: we need a strategy for the future, and we need it now. Automating Humanity is an insider's perspective on everything Big Tech doesn't want the public to know-or think about-from the addictions installed on a global scale to the profits being driven by fake news and disinformation, to the way they're manipulating the world for profit and using our data to train systems that will automate jobs at an explosive, unprecedented scale. Toscano provides a critique of modern regulation, including parts of the new European Union's General Data Proctection Regulation (GDPR) suggesting how we can create proactive, adaptable regulation that satisfies both the needs of consumer safety and commercial success in the international economy. The content touches on everything from technology, economics, and public policy to psychology, history, and ethics, and is written in a way that is accessible to everyone from the average reader to the technical expert.

Automating technologies threaten to usher in a workless future, but John Danaher argues that this can be a good thing. A world without work may be a kind of utopia, free of the misery of the job and full of opportunities for creativity and exploration. If we play our cards right, automation could be the path to idealized forms of human flourishing.

For readers of Sapiens and Homo Deus and viewers of The Social Dilemma, psychologist Tomas Chamorro-Premuzic tackles one of the biggest questions facing our species: Will we use artificial intelligence to improve the way we work and live, or will we allow it to alienate us? It's no secret that AI is changing the way we live, work, love, and entertain ourselves. Dating apps are using AI to pick our potential partners. Retailers are using AI to predict our behavior and desires. Rogue actors are using AI to persuade us with bots and misinformation. Companies are using AI to hire us—or not. In I, Human psychologist Tomas Chamorro-Premuzic takes readers on an enthralling and eye-opening journey across the AI landscape. Though AI has the potential to change our lives for the better, he argues, AI is also worsening our bad tendencies, making us more distracted, selfish, biased, narcissistic, entitled, predictable, and impatient. It doesn't have to be this way. Filled with fascinating insights about human behavior and our complicated relationship with technology, I, Human will help us stand out and thrive when many of our decisions are being made for us. To do so, we'll need to double down on our curiosity, adaptability, and emotional intelligence while relying on the lost virtues of empathy, humility, and self-control. This is just the beginning. As AI becomes smarter and more humanlike, our societies, our economies, and our humanity will undergo the most dramatic changes we've seen since the Industrial Revolution. Some of these changes will enhance our species. Others may dehumanize us and make us more machinelike in our interactions with people. It's up to us to adapt and determine how we want to live and work. The choice is ours. What will we decide?

This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term "A.I." is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether "human" or "A.I."

WINNER: The 2018 McGannon Center Book Prize and shortlisted for the Goddard Riverside Stephan Russo Book Prize for Social Justice The New York Times Book Review: "Riveting." Naomi Klein: "This book is downright scary." Ethan Zuckerman, MIT: "Should be required reading." Dorothy Roberts, author of Killing the Black Body: "A must-read." Astra Taylor, author of The People's Platform: "The single most important book about technology you will read this year." Cory Doctorow: "Indispensable." A powerful investigative look at data-based discrimination—and how technology affects civil and human rights and economic equity The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years—because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely.

For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind "autonomous" processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of "the human" at the heart of automation claims. But labor is socially stratified and so automation's fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don't) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the "future of work."

AI is poised to disrupt our work and our lives. We can harness these technologies rather than fall captive to them—but only through wise regulation. Too many CEOs tell a simple story about the future of work: if a machine can do what you do, your job will be automated. They envision everyone from doctors to soldiers rendered superfluous by ever-more-powerful AI. They offer stark alternatives: make robots or be replaced by them. Another story is possible. In virtually every walk of life, robotic systems can make labor more valuable, not less. Frank Pasquale tells the story of nurses, teachers, designers, and others who partner with technologists, rather than meekly serving as data sources for their computerized replacements. This cooperation reveals the kind of technological advance that could bring us all better health care, education, and more, while maintaining meaningful work. These partnerships also show how law and regulation can promote prosperity for all, rather than a zero-sum race of humans against machines. How far should AI be entrusted to assume tasks once performed by humans? What is gained and lost when it does? What is the optimal mix of robotic and human interaction? New Laws of Robotics makes the case that policymakers must not allow corporations or engineers to answer these questions alone. The kind of automation we get—and who it benefits—will depend on myriad small decisions about how to develop AI. Pasquale proposes ways to democratize that decision making, rather than centralize it in unaccountable firms. Sober yet optimistic, New Laws of Robotics offers an inspiring vision of technological progress, in which human capacities and expertise are the irreplaceable center of an inclusive economy.

There are a lot of great advertising books, but none that get down in the dirt with you quite like this one. Thomas Kemeny made a career at some of the best ad agencies in America. In this book he shows how he got in, how he's stayed in, and how you can do it too. He breaks apart how to write fun, smart, and effective copy-everything from headlines to scripts to experiential activations-giving readers a lesson on a language we all thought we already knew. This book is not a retrospective from some ad legend. It's a book that should be instantly useful for people starting out. A guide for the first few years at a place you'd actually want to work. Traditionally, advertising books have been written by people with established careers, big offices and letters like VP in their titles. They have stories from the old days when people could start in the mailroom. They are talented. That's been done. Who wants another book filled with seasoned wisdom? This is a book written by somebody still getting his bearings. Someone who has made an extraordinary number of errors in a still short career. Someone who has managed to hang onto his job despite these shortcomings.

A New York Times bestselling author and tech columnist's counter-intuitive guide to staying relevant - and employable - in the machine age by becoming irreplaceably human. It's not a future scenario any more. We've been taught that to compete with automation and AI, we'll have to become more like the machines themselves, building up technical skills like coding. But, there's simply no way to keep up. What if all the advice is wrong? And what do we need to do instead to become futureproof? We tend to think of automation as a blue-collar phenomenon that will affect truck drivers, factory workers, and other people with repetitive manual jobs. But it's much, much broader than that. Lawyers are being automated out of existence. Last year, JPMorgan Chase built a piece of software called COIN, which uses machine learning to review complicated contracts and documents. It used to take the firm's lawyers more than 300,000 hours every year to review all of those documents. Now, it takes a few seconds, and requires just one human to run the program. Doctors are being automated out of existence, too. Last summer, a Chinese tech company built a deep learning algorithm that diagnosed brain cancer and other diseases faster and more accurately than a team of 15 top Chinese doctors. Kevin Roose has spent the past few years studying the question of how people, communities, and organisations adapt to periods of change, from the Industrial Revolution to the present. And the insight that is sweeping through Silicon Valley as we speak -- that in an age dominated by machines, it's human skills that really matter - is one of the more profound and counter-intuitive ideas he's discovered. It's the antidote to the doom-and-gloom worries many people feel when they think about AI and automation. And it's something everyone needs to hear. In nine accessible, prescriptive chapters, Roose distills what he has learned about how we will survive the future, that the way to become futureproof is to become incredibly, irreplaceably human.