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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: Phoebe V. Moore
Publisher: Springer
ISBN: 3319582321
Category : Social Science
Languages : en
Pages : 270
Get Book Here
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: 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: Jamie Merisotis
Publisher: Rosetta Books
ISBN: 194812260X
Category : Business & Economics
Languages : en
Pages : 208
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Book Description
A public policy leader addresses how artificial intelligence is transforming the future of labor—and what we can do to protect the role of workers. As computer technology advances with dizzying speed, human workers face an ever-increasing threat of obsolescence. In Human Work In the Age of Smart Machines, Jamie Merisotis argues that we can—and must—rise to this challenge by preparing to work alongside smart machines doing that which only humans can: thinking critically, reasoning ethically, interacting interpersonally, and serving others with empathy. The president and CEO of Lumina Foundation, Merisotis offers a roadmap for the large-scale, radical changes we must make in order to find abundant and meaningful work for ourselves in the 21st century. His vision centers on developing our unique capabilities as humans through learning opportunities that deliver fair results and offer a broad range of credentials. By challenging long-held assumptions and expanding our concept of work, Merisotis argues that we can harness the population’s potential, encourage a deeper sense of community, and erase a centuries-long system of inequality.
Author: Thomas H. Davenport
Publisher: MIT Press
ISBN: 0262371197
Category : Business & Economics
Languages : en
Pages : 312
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Book Description
Two management and technology experts show that AI is not a job destroyer, exploring worker-AI collaboration in real-world work settings. 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. These cases include a digital system for life insurance underwriting that analyzes applications and third-party data in real time, allowing human underwriters to focus on more complex cases; an intelligent telemedicine platform with a chat-based interface; a machine learning-system that identifies impending train maintenance issues by analyzing diesel fuel samples; and Flippy, a robotic assistant for fast food preparation. For each one, Davenport and Miller describe in detail the work context for the system, interviewing job incumbents, managers, and technology vendors. Short “insight” chapters draw out common themes and consider the implications of human collaboration with smart systems.
Author: Jan Büssers
Publisher: Verlag Barbara Budrich
ISBN: 3847416464
Category : Business & Economics
Languages : en
Pages : 306
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Book Description
In numerous fields of science, work, and everyday life, humans and machines have been increasingly entangled, developing an ever-growing toolbox of interactions. These entanglements affect our daily lives and pose possibilities as well as restrictions, chances as well as challenges. The contributions of this volume tackle related issues by adopting a highly interdisciplinary perspective. How do digitalization and artificial intelligence affect gender relations? How can intersectionality be newly understood in an increasingly internationally networked world? This volume is a collection of contributions deriving from the “Interdisciplinary Conference on the Relations of Humans, Machines and Gender” which took place in Braunschweig (October 16–19, 2019). It also includes the keynotes given by Cecile Crutzen, Galit Wellner and Helen Verran.
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: Kevin Roose
Publisher: Hachette UK
ISBN: 152930475X
Category : Technology & Engineering
Languages : en
Pages : 256
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Book Description
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.
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: J. Mark Munoz
Publisher: Anthem Press
ISBN: 1785279947
Category : Business & Economics
Languages : en
Pages : 168
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Book Description
The book highlights expert interviews, stories, news events, and academic research impacting our contemporary world in the era of artificial intelligence. This book aims to be a thought-provoking reference guide for corporate executives looking to lead in a world of AI. It is poised to provide readers with game-changing insights on leadership and management in an artificial intelligence economy. Written with an equally educational and fun approach, the book covers practical business strategies that will help managers succeed in an AI world.
Author: Robert Munro
Publisher: Simon and Schuster
ISBN: 1617296740
Category : Computers
Languages : en
Pages : 422
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Book Description
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. 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 dreate 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.
