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: Brent M Eastwood
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 290
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Book Description
Are you ready for the warzones of tomorrow? Have you always been fascinated about the future of warfare? Do you want to discover the cutting-edge technology and strategies that will shape the way we solve conflicts? Offering an engaging and illuminating glimpse into the future of warfare across the world's land, sky, and sea, Humans, Machines, and Data delves into the latest military and scientific technology to explore how these advancements will impact the way nations conduct war. Covering human biotech, robotics, and even big data, you will also discover how broader social and environmental changes will impact every facet of warfare. From super soldiers and cyborgs to artificial intelligence and the emerging threats in cyberspace, warfare is changing by the second - and Humans, Machines, and Data provides you with a profound look at the evolution of combat. Here is just a little of what you will discover inside: The Sociology of Warfare How the Modern Age Has Created New Kinds of Warfare Why Artificial Intelligence and Robots Will Dominate the Warzones of Tomorrow How Social Shifts, Demographics, and Climate Change Will Define Our Future Cyborgs and Biotechnology - Why Super Soldiers Will Soon Become Reality A Breakdown of War in The Information Age Exploring Cyber Threats and Quantum Computing Deep Analysis of China, Russia, Iran, and North Korea And So Much More... Perfect for military enthusiasts, futurists, war buffs, and anyone interested in the technology of tomorrow, Humans, Machines, and Data offers you a unique and unparalleled look at how the world's militaries are evolving. Brent M. Eastwood, PhD is a Political Scientist and Emerging Threats expert. He was Founder and CEO of a tech firm that predicted world events using machine learning and artificial intelligence. He served in the U.S. Senate as a legislative fellow and advised a senator on defense and foreign policy issues. Brent has taught at George Washington University and George Mason University. He is a former U.S. Army Infantry officer. Go to brenteastwood.com for more about Brent.
Author: Paul R. Daugherty
Publisher: Harvard Business Press
ISBN: 1633693872
Category : Computers
Languages : en
Pages : 268
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Book Description
AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
Author: Phoebe V. Moore
Publisher: Springer
ISBN: 3319582321
Category : Social Science
Languages : en
Pages : 270
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Book Description
This edited collection provides a series of accounts of workers’ local experiences that reflect the ubiquity of work’s digitalisation. Precarious gig economy workers ride bikes and drive taxis in China and Britain; call centre workers in India experience invasive tracking; warehouse workers discover that hidden data has been used for layoffs; and academic researchers see their labour obscured by a ‘data foam’ that does not benefit them. These cases are couched in historical accounts of identity and selfhood experiments seen in the Hawthorne experiments and the lineage of automation. This book will appeal to scholars in the Sociology of Work and Digital Labour Studies and anyone interested in learning about monitoring and surveillance, automation, the gig economy and the quantified self in the workplace.
Author: Malcolm Frank
Publisher: John Wiley & Sons
ISBN: 111927866X
Category : Business & Economics
Languages : en
Pages : 262
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Book Description
“Refreshingly thought-provoking...” – The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars, diagnose medical patients, and manage our finances more effectively than humans it raises profound questions on the future of work and how companies compete. Illustrated with real-world cases, data, and insight, the authors provide clear strategic guidance and actionable steps to help you and your organization move ahead in a world where exponentially developing new technologies are changing how value is created. Written by a team of business and technology expert practitioners—who also authored Code Halos: How the Digital Lives of People, Things, and Organizations are Changing the Rules of Business—this book provides a clear path to the future of your work. The first part of the book examines the once in a generation upheaval most every organization will soon face as systems of intelligence go mainstream. The authors argue that contrary to the doom and gloom that surrounds much of IT and business at the moment, we are in fact on the cusp of the biggest wave of opportunity creation since the Industrial Revolution. Next, the authors detail a clear-cut business model to help leaders take part in this coming boom; the AHEAD model outlines five strategic initiatives—Automate, Halos, Enhance, Abundance, and Discovery—that are central to competing in the next phase of global business by driving new levels of efficiency, customer intimacy and innovation. Business leaders today have two options: be swallowed up by the ongoing technological evolution, or ride the crest of the wave to new profits and better business. This book shows you how to avoid your own extinction event, and will help you; Understand the untold full extent of technology's impact on the way we work and live. Find out where we're headed, and how soon the future will arrive Leverage the new emerging paradigm into a sustainable business advantage Adopt a strategic model for winning in the new economy The digital world is already transforming how we work, live, and shop, how we are governed and entertained, and how we manage our money, health, security, and relationships. Don't let your business—or your career—get left behind. What To Do When Machines Do Everything is your strategic roadmap to a future full of possibility and success. Or peril.
Author: Woodrow Barfield
Publisher: Springer
ISBN: 3319250507
Category : Computers
Languages : en
Pages : 304
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Book Description
It is predicted that robots will surpass human intelligence within the next fifty years. The ever increasing speed of advances in technology and neuroscience, coupled with the creation of super computers and enhanced body parts and artificial limbs, is paving the way for a merger of both human and machine. Devices which were once worn on the body are now being implanted into the body, and as a result, a class of true cyborgs, who are displaying a range of skills beyond those of normal humans-beings, are being created. There are cyborgs which can see colour by hearing sound, others have the ability to detect magnetic fields, some are equipped with telephoto lenses to aid their vision or implanted computers to monitor their heart, and some use thought to communicate with a computer or to manipulate a robotic arm. This is not science-fiction, these are developments that are really happening now, and will continue to develop in the future. However, a range of legal and policy questions has arisen alongside this rise of artificial intelligence. Cyber-Humans provides a deep and unique perspective on the technological future of humanity, and describes how law and policy will be particularly relevant in creating a fair and equal society and protecting the liberties of different life forms which will emerge in the 21st century. Dr Woodrow (Woody) Barfield previously headed up the Sensory Engineering Laboratory, holding the position of Industrial and Systems Engineering Professor at the University of Washington. His research revolves around the design and use of wearable computers and augmented reality systems and holds both JD and LLM degrees in intellectual property law and policy. He has published over 350 articles and major presentations in the areas of computer science, engineering and law. He currently lives in Chapel Hill, NC, USA.
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: Daniel Newman
Publisher: Kogan Page Publishers
ISBN: 074948425X
Category : Business & Economics
Languages : en
Pages : 265
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Book Description
Will the workplace of the future be overrun by machines and robots? Are the new frontiers of artificial intelligence (AI) on the cusp of dethroning us in efficiency, intelligence and innovative potential? Automation and AI will augment our human world and potential. The winners of the future of work are those that harness the power of machines to their advantage. Human/Machine is the only guide you need to understand the fourth industrial revolution. It sets out a road map to the challenges ahead, but also unlocks the wondrous opportunities that it offers. Human/Machine explores how we will work symbiotically with machines, detailing how institutions, companies, individuals and education providers will evolve to integrate seamlessly with new technologies. With exclusive case studies, this book offers a glimpse into the future and details how top companies are already thriving on this very special relationship. From gamification in job training to project management teams integrated with bots and predictive technologies that fix problems in the supply chain before they happen, the authors deliver a powerful manifesto for the adoption and celebration of automation and AI. In a much more fluid, skills-based economy, we will all need to prove our worth and future-proof our skills base. This book offers a blueprint to avoid being left behind and unearth the opportunities unique to human-machine partnership ecosystems.
Author: Robert (Munro) Monarch
Publisher: Simon and Schuster
ISBN: 1638351031
Category : Computers
Languages : en
Pages : 422
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Book Description
Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. Summary Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. Human-in-the-Loop Machine Learning is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. About the book Human-in-the-Loop Machine Learning lays out methods for humans and machines to work together effectively. You’ll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You’ll learn to create training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows. What's inside Identifying the right training and evaluation data Finding and managing people to annotate data Selecting annotation quality control strategies Designing interfaces to improve accuracy and efficiency About the author Robert (Munro) Monarch is a data scientist and engineer who has built machine learning data for companies such as Apple, Amazon, Google, and IBM. He holds a PhD from Stanford. Robert holds a PhD from Stanford focused on Human-in-the-Loop machine learning for healthcare and disaster response, and is a disaster response professional in addition to being a machine learning professional. A worked example throughout this text is classifying disaster-related messages from real disasters that Robert has helped respond to in the past. Table of Contents PART 1 - FIRST STEPS 1 Introduction to human-in-the-loop machine learning 2 Getting started with human-in-the-loop machine learning PART 2 - ACTIVE LEARNING 3 Uncertainty sampling 4 Diversity sampling 5 Advanced active learning 6 Applying active learning to different machine learning tasks PART 3 - ANNOTATION 7 Working with the people annotating your data 8 Quality control for data annotation 9 Advanced data annotation and augmentation 10 Annotation quality for different machine learning tasks PART 4 - HUMAN–COMPUTER INTERACTION FOR MACHINE LEARNING 11 Interfaces for data annotation 12 Human-in-the-loop machine learning products
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.
