Taming the Machine PDF Download

Author: Nell Watson
Publisher: Kogan Page Publishers
ISBN: 1398614335
Category : Computers
Languages : en
Pages : 337

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Book Description
AI promises to transform our world, supercharging productivity and driving new innovations. Taming the Machine uncovers how you can responsibly harness the power of AI with confidence. AI has the potential to become a personal assistant, a creative partner, an editor and a research tool all at once. But it also represents a threat to your livelihood, data and privacy. Taming the Machine offers the practical insights and knowledge you need to work with AI with an ethical and responsible approach. In this book, celebrated AI expert and ethicist Nell Watson offers practical insights on how you can ethically innovate with AI. It delves into the ethical issues of unbridled AI, highlighting the challenges that it will bring to society and business unless we fortify cybersecurity, safeguard our data, and understand the dangerous potential of artificial intelligence. Step into the future and supercharge your performance safely by Taming the Machine.

Author: Paul Roehrig
Publisher: John Wiley & Sons
ISBN: 1119785928
Category : Business & Economics
Languages : en
Pages : 176

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Book Description
"In their 'deliberately short book' IT analysts, management consultants and technology practitioners Roehrig and Pring explore how big a beast technology has become, and how we can tame it to maintain our freedom and privacy while still realising its benefits. The pandemic has shown just how much we rely on technology and how addictive it has become...The authors address the important questions...[and] urge us not to slay the monster but rather to leverage its power and reorient technology as a tool for good." —Financial Times Monster explains how we can responsibly engage with technology, and avoid its darker tendencies, while accepting its necessary gifts. The authors, insiders at one of the world's largest tech consulting firms, give a unique take on: The addictive nature of tech and how to fight it The growing backlash against big tech--where it's right and what it misses Crucial steps for taming technology's role in your life and in your organization--without becoming a modern Luddite Written for managers, leaders, and employees at companies of all sizes and in all industries, Monster will help you understand and take control of technology's powerful role in your life and your organization. "You must read this book." —Michael Schrage, Research Fellow, MIT Sloan School Initiative on the Digital Economy "Pithy insights and recommendations on helping tech fulfill its potential as a force for good." —Erik Brynjolfsson, Director of the Stanford Digital Economy Lab and co-author of The Second Machine Age "Making technology serve—not subvert—the public interest requires better leaders, not more engineers and coders. Monster explains how to become one of those leaders." —Rosabeth Moss Kanter, Harvard Business School Professor and author of Think Outside the Building "A bracing new book about some of the most pressing questions of our time." —Carl Benedikt Frey, Oxford Martin Citi Fellow at Oxford University and author of The Technology Trap "Provocative and concise, Monster is an important book on rescuing ourselves from technology that now feels corrosive and overwhelming." —Daniel H. Pink, author of WHEN, DRIVE, and TO SELL IS HUMAN "Clarifies a complex web of issues and provides bold steps for a healthier economy, society, and future." —Francisco D'Souza, former CEO and Vice Chairman of Cognizant "Sheds light on how we can collectively use technology for the good of all." —Soumitra Dutta, Founding Dean, SC Johnson College of Business, Cornell University "A cornucopia of pragmatic, actionable, and bold ideas." —Gary J. Beach, Publisher Emeritus, CIO magazine and author of U.S. Technology Skills Gap

Author: Marcello Pelillo
Publisher: MIT Press
ISBN: 0262362163
Category : Computers
Languages : en
Pages : 175

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Book Description
Experts from disciplines that range from computer science to philosophy consider the challenges of building AI systems that humans can trust. Artificial intelligence-based algorithms now marshal an astonishing range of our daily activities, from driving a car ("turn left in 400 yards") to making a purchase ("products recommended for you"). How can we design AI technologies that humans can trust, especially in such areas of application as law enforcement and the recruitment and hiring process? In this volume, experts from a range of disciplines discuss the ethical and social implications of the proliferation of AI systems, considering bias, transparency, and other issues. The contributors, offering perspectives from computer science, engineering, law, and philosophy, first lay out the terms of the discussion, considering the "ethical debts" of AI systems, the evolution of the AI field, and the problems of trust and trustworthiness in the context of AI. They go on to discuss specific ethical issues and present case studies of such applications as medicine and robotics, inviting us to shift the focus from the perspective of a "human-centered AI" to that of an "AI-decentered humanity." Finally, they consider the future of AI, arguing that, as we move toward a hybrid society of cohabiting humans and machines, AI technologies can become humanity's allies.

Author: Thomas Duriez
Publisher: Springer
ISBN: 3319406248
Category : Technology & Engineering
Languages : en
Pages : 229

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Book Description
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading researchers in turbulence control (S. Bagheri, B. Batten, M. Glauser, D. Williams) and machine learning (M. Schoenauer) for a broader perspective. All chapters have exercises and supplemental videos will be available through YouTube.

Author: Cesar A. Hidalgo
Publisher: MIT Press
ISBN: 026236252X
Category : Computers
Languages : en
Pages : 257

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Book Description
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.

Author: Adrian Mackenzie
Publisher: MIT Press
ISBN: 0262036827
Category : Social Science
Languages : en
Pages : 269

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Book Description
If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought? Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking. Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures. Mackenzie's account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.

Author: Morgan G. Ames
Publisher: MIT Press
ISBN: 0262537443
Category : Technology & Engineering
Languages : en
Pages : 323

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Book Description
A fascinating examination of technological utopianism and its complicated consequences. In The Charisma Machine, Morgan Ames chronicles the life and legacy of the One Laptop per Child project and explains why—despite its failures—the same utopian visions that inspired OLPC still motivate other projects trying to use technology to “disrupt” education and development. Announced in 2005 by MIT Media Lab cofounder Nicholas Negroponte, One Laptop per Child promised to transform the lives of children across the Global South with a small, sturdy, and cheap laptop computer, powered by a hand crank. In reality, the project fell short in many ways—starting with the hand crank, which never materialized. Yet the project remained charismatic to many who were captivated by its claims of access to educational opportunities previously out of reach. Behind its promises, OLPC, like many technology projects that make similarly grand claims, had a fundamentally flawed vision of who the computer was made for and what role technology should play in learning. Drawing on fifty years of history and a seven-month study of a model OLPC project in Paraguay, Ames reveals that the laptops were not only frustrating to use, easy to break, and hard to repair, they were designed for “technically precocious boys”—idealized younger versions of the developers themselves—rather than the children who were actually using them. The Charisma Machine offers a cautionary tale about the allure of technology hype and the problems that result when utopian dreams drive technology development.

Author: Meredith Broussard
Publisher: MIT Press
ISBN: 026253701X
Category : Computers
Languages : en
Pages : 247

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Book Description
A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone.

Author: Ronald J. Brachman
Publisher: MIT Press
ISBN: 0262369222
Category : Computers
Languages : en
Pages : 320

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Book Description
How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise. 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. Using the stuck traffic light and other relatable examples, Brachman and Levesque offer an accessible account of how common sense might be built into a machine. They analyze common sense in humans, explain how AI over the years has focused mainly on expertise, and suggest ways to endow an AI system with both common sense and effective reasoning. Finally, they consider the critical issue of how we can trust an autonomous machine to make decisions, identifying two fundamental requirements for trustworthy autonomous AI systems: having reasons for doing what they do, and being able to accept advice. Both in the end are dependent on having common sense.

Author: Grant Ingersoll
Publisher: Simon and Schuster
ISBN: 1638353867
Category : Computers
Languages : en
Pages : 467

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Book Description
Summary Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built. About this Book There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook. Taming Text is a practical, example-driven guide to working withtext in real applications. This book introduces you to useful techniques like full-text search, proper name recognition,clustering, tagging, information extraction, and summarization.You'll explore real use cases as you systematically absorb thefoundations upon which they are built.Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language. Written for Java developers, the book requires no prior knowledge of GWT. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Winner of 2013 Jolt Awards: The Best Books—one of five notable books every serious programmer should read. What's Inside When to use text-taming techniques Important open-source libraries like Solr and Mahout How to build text-processing applications About the Authors Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout,Lucene, and Solr. "Takes the mystery out of verycomplex processes."—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University Table of Contents Getting started taming text Foundations of taming text Searching Fuzzy string matching Identifying people, places, and things Clustering text Classification, categorization, and tagging Building an example question answering system Untamed text: exploring the next frontier