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.

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?

Robert Sapolsky’s Behave, his now classic account of why humans do good and why they do bad, pointed toward an unsettling conclusion: We may not grasp the precise marriage of nature and nurture that creates the physics and chemistry at the base of human behavior, but that doesn’t mean it doesn’t exist. Now, in Determined, Sapolsky takes his argument all the way, mounting a brilliant (and in his inimitable way, delightful) full-frontal assault on the pleasant fantasy that there is some separate self telling our biology what to do.

Machine learning is changing the world. You use machine learning every day and probably don’t know it. In this audiobook, you will learn how ML grew from a desire to make computers able to learn.

A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, "computational thinking" has become part of the K-12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview.

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we can get a job or a loan, how much we pay for health insurance—are being made not by humans, but by machines. In theory, this should lead to greater fairness: Everyone is judged according to the same rules.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

AI will be the defining development of the 21st century. Within two decades, aspects of daily human life will be unrecognizable. AI will generate unprecedented wealth, revolutionize medicine and education through human-machine symbiosis, and create brand-new forms of communication and entertainment. In liberating us from routine work, however, AI will also challenge the organizing principles of our economic and social order.

In The Unicorn Project, we follow Maxine, a senior lead developer and architect, as she is exiled to the Phoenix Project, to the horror of her friends and colleagues, as punishment for contributing to a payroll outage. She tries to survive in what feels like a heartless and uncaring bureaucracy and to work within a system where no one can get anything done without endless committees, paperwork, and approvals. One day, she is approached by a ragtag bunch of misfits who say they want to overthrow the existing order, to liberate developers, to bring joy back to technology work.

The retired four-star general and and best-selling author of My Share of the Task shares a powerful new leadership model. Former General Stanley McChrystal held a key position for much of the War on Terror, as head of the Joint Special Operations Command. In Iraq, he found that despite the vastly superior resources, manpower, and training of the US Military, Al Qaeda had an advantage because of its structure as a loose network of small, independent cells. To defeat such an agile enemy, JSOC had to change its focus from efficiency to adaptability.

Dave Thomas and Andy Hunt wrote the first edition of this influential book in 1999 to help their clients create better software and rediscover the joy of coding. These lessons have helped a generation of programmers examine the very essence of software development. Now, 20 years later, this new edition re-examines what it means to be a modern programmer. Topics range from personal responsibility and career development to architectural techniques for keeping your code flexible and easy to adapt and reuse.

Over the past 10 years, urban planners, technology companies, and governments have promoted smart cities with a somewhat utopian vision of urban life made knowable and manageable through data collection and analysis. Emerging smart cities have become both crucibles and showrooms for the practical application of the Internet of Things, cloud computing, and the integration of big data into everyday life. Are smart cities optimized, sustainable, digitally networked solutions to urban problems? Or are they neoliberal, corporate-controlled, undemocratic non-places?

Although it is among the oldest of market institutions, the auction is ubiquitous in today's economy, used for everything from government procurement to selling advertising on the Internet to course assignment at MIT's Sloan School. Yet beyond the small number of economists who specialize in the subject, few people understand how auctions really work. This concise, accessible, and engaging book explains both the theory and the practice of auctions.

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.

In their book Abundance, best-selling authors and futurists Peter Diamandis and Steven Kotler tackled grand global challenges, such as poverty, hunger, and energy. Then, in Bold, they chronicled the use of exponential technologies that allowed the emergence of powerful new entrepreneurs. Now the best-selling authors are back with The Future Is Faster Than You Think, a blueprint for how our world will change in response to the next 10 years of rapid technological disruption.

A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, "computational thinking" has become part of the K-12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview.

After discussing what an algorithm does and how its effectiveness can be measured, Louridas covers three of the most fundamental applications areas: graphs, which describe networks, from eighteenth-century problems to today's social networks; searching, and how to find the fastest way to search; and sorting, and the importance of choosing the best algorithm for particular tasks. He then presents larger-scale applications: PageRank, Google's founding algorithm; and neural networks and deep learning.

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.

In the late 1850s, a physician in New York City used a syringe and glass tube to inject half a drop of sperm into a woman's uterus, marking the first recorded instance of artificial insemination. From that day forward, doctors and scientists have turned to technology in ever more innovative ways to facilitate conception. Fertility Technology surveys this history in all its medical, practical, and ethical complexity, and offers a look at state-of-the-art fertility technology in various social and political contexts around the world.

When "metadata" became breaking news, appearing in stories about surveillance by the National Security Agency, many members of the public encountered this once-obscure term from information science for the first time. Should people be reassured that the NSA was "only" collecting metadata about phone calls - information about the caller, the recipient, the time, the duration, the location - and not recordings of the conversations themselves? Or does phone call metadata reveal more than it seems?