Shining a spotlight on the robots all around us
Artificial intelligence is all around us: in our phones, our cars, our refrigerators. Although the moral implications of AI are much debated, there is no doubt that humans are reaping the benefits of a robotic-driven world. How else would we know the forecast if we weren’t able to ask our voice assistants?
For AI Appreciation Day, we have gathered texts all about our intelligent friends, from their inner workings to their potential dangers. Read on to explore more on AI, and sign up for our newsletter to hear more updates from the Press.
Code to Joy: Why Everyone Should Learn a Little Programming by Michael L. Littman
In this informative, accessible, and very funny book, Michael L. Littman inspires readers to learn how to tell machines what to do for us. Rather than give in to the fear that computers will steal our jobs, spy on us and control what we buy and whom we vote for, we can improve our relationship with them just by learning basic programming skills. Our devices will help us, Littman writes, if we can say what we want in a way they can understand.
“This is an important and timely book about us, the machines we have come to depend on, and the new world that creates.” —Charles Isbell, Georgia Tech
Evolutionary Intelligence: How Technology Will Make Us Smarter by W. Russell Neuman
It is natural for us to fear artificial intelligence. But does Siri really want to kill us? Perhaps we are falling into the trap of projecting human traits onto the machines we might build. In Evolutionary Intelligence, Neuman offers a surprisingly positive vision in which computational intelligence compensates for the well-recognized limits of human judgment, improves decision making, and actually increases our agency. In artful, accessible, and adventurous prose, Neuman takes the reader on an exciting, fast-paced ride, all the while making a convincing case about a revolution in computationally augmented human intelligence.
“Coming precisely at the right moment, Evolutionary Intelligence shows how humans can use technology to extend our intelligence not in isolation but to create a more human world.” —John Markoff, author of Machines of Loving Grace
Machines like Us: Toward AI with Common Sense by Ronald J. Brachman and Hector J. Levesque
It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefinitely. Its obstacle-avoidance, lane-following, and route-calculation capacities are all irrelevant; it fails to act because it lacks the common sense of a human driver, who would quickly figure out what’s happening and find a workaround. In Machines like Us, Ron Brachman and Hector Levesque—both leading experts in AI—consider what it would take to create machines with common sense rather than just the specialized expertise of today’s AI systems.
“Machines Like Us provides a fresh perspective on potential areas of research, courtesy of two scientists who have been deeply involved in artificial intelligence since the 1970s.” —Ben Dickson, TechTalks
The Little Learner: A Straight Line to Deep Learning by Daniel P. Friedman and Anurag Mendhekar
The Little Learner introduces deep learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The Little Typer, this kindred text explains the workings of deep neural networks by constructing them incrementally from first principles using little programs that build on one another. Starting from scratch, the reader is led through a complete implementation of a substantial application: a recognizer for noisy Morse code signals. Example-driven and highly accessible, The Little Learner covers all of the concepts necessary to develop an intuitive understanding of the workings of deep neural networks, including tensors, extended operators, gradient descent algorithms, artificial neurons, dense networks, convolutional networks, residual networks, and automatic differentiation.
“Friedman’s ‘Little Books’ are famous for teaching important topics in bite-sized, easily-digestible pieces. Now Friedman and Mendhekar have turned their attention to machine learning, and they have succeeded masterfully.” —Mitchell Wand, Northeastern University; coauthor of Essentials of Programming Languages
Artificial Intelligence, The Illustrated Edition: Modern Magic or Dangerous Future? by Yorick A. Wilks
Artificial intelligence has long been a mainstay of science fiction, and increasingly it feels as if AI is entering our everyday lives, with virtual personal assistants such as Apple’s Siri now ubiquitous and self-driving cars almost upon us. But what do we actually mean when we talk about artificial intelligence? In this comprehensive, beautifully illustrated account, AI expert Yorick Wilks traces the history of artificial intelligence back to its origins, examining not only how it works and why it was designed but also its controversies and achievements.
Living with Robots: What Every Anxious Human Needs to Know by Ruth Aylett and Patricia A. Vargas
There’s a lot of hype about robots; some of it is scary and some of it utopian. In this accessible book, two robotics experts reveal the truth about what robots can and can’t do, how they work, and what we can reasonably expect their future capabilities to be. It will not only make you think differently about the capabilities of robots; it will make you think differently about the capabilities of humans. Living with Robots equips readers to look at robots concretely—as human-made artifacts rather than placeholders for our anxieties.
“Well-researched, this survey makes for an in-depth review of the present state of robotics.” —Publishers Weekly
Robots are a curious sort of thing. On the one hand, they are technological artifacts—and thus, things. On the other hand, they seem to have social presence, because they talk and interact with us, and simulate the capabilities commonly associated with personhood. In Person, Thing, Robot, David J. Gunkel sets out to answer the vexing question: What exactly is a robot? Rather than try to fit robots into the existing categories by way of arguing for either their reification or personification, however, Gunkel argues for a revolutionary reformulation of the entire system, developing a new moral and legal ontology for the twenty-first century and beyond.
“In this thoughtful and engaging examination of a heated Western philosophy debate, Gunkel throws the entire premise on its head.” —Kate Darling, MIT Research Scientist; author of The New Breed
Awkward Intelligence: Where AI Goes Wrong, Why It Matters, and What We Can Do about It by Katharina A. Zweig
Before we know it, artificial intelligence (AI) will work its way into every corner of our lives, making decisions about, with, and for us. Is this a good thing? There’s a tendency to think that machines can be more “objective” than humans—can make better decisions about job applicants, for example, or risk assessments. In Awkward Intelligence, AI expert Katharina Zweig offers readers the inside story, explaining how many levers computer and data scientists must pull for AI’s supposedly objective decision making. She presents the good and the bad: AI is good at processing vast quantities of data that humans cannot—but it’s bad at making judgments about people.
“In an accessible and approachable way, Zweig engages with important issues ranging from technical AI to ethics.” —Arthur I. Miller, University College London; author of The Artist in the Machine
Working with AI: Real Stories of Human-Machine Collaboration by Thomas H. Davenport and Steven M. Miller
This book breaks through both the hype and the doom-and-gloom surrounding automation and the deployment of artificial intelligence-enabled—“smart”—systems at work. Management and technology experts Thomas Davenport and Steven Miller show that, contrary to widespread predictions, prescriptions, and denunciations, AI is not primarily a job destroyer. Rather, AI changes the way we work—by taking over some tasks but not entire jobs, freeing people to do other, more important and more challenging work. By offering detailed, real-world case studies of AI-augmented jobs in settings that range from finance to the factory floor, Davenport and Miller also show that AI in the workplace is not the stuff of futuristic speculation. It is happening now to many companies and workers.
“Read this book if you want reassurance on the positive potential outcomes of AI versus the ominous view that artificial intelligence is a job stealer.” —The Enterprisers Project
Robot Ethics by Mark Coeckelbergh
Does a robot have moral agency? Can it be held responsible for its actions? Do humans owe robots anything? Will robots take our jobs? These are some of the ethical and moral quandaries that we should address now, as robots and other intelligent devices become more widely used and more technically sophisticated. In this volume in the MIT Press Essential Knowledge series, philosopher Mark Coeckelbergh does just that. He considers a variety of robotics technologies and applications—from robotic companions to military drones—and identifies the ethical implications of their use. Questions of robot ethics, he argues, are not just about robots but are, crucially, about humans as well.