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A consensus-shattering account of automation technologies and their effect on workplaces and the labor market In this consensus-shattering account of automation technologies, Aaron Benanav investigates the economic trends that will shape our working lives far into the future. Silicon Valley titans, politicians, techno-futurists, and social critics have united in arguing that we are on the cusp of an era of rapid technological automation, heralding the end of work as we know it. But does the muchdiscussed “rise of the robots” really explain the long-term decline in the demand for labor? Automation and the Future of Work uncovers the deep weaknesses of twenty-first-century capitalism and the reasons why the engine of economic growth keeps stalling. Equally important, Benanav goes on to salvage from automation discourse its utopian content: the positive vision of a world without work. What social movements, he asks, are required to propel us into post-scarcity if technological innovation alone can’t deliver it? In response to calls for a permanent universal basic income that would maintain a growing army of redundant workers, he offers a groundbreaking counterproposal.
For some, automation will usher in a labor-free utopia; for others, it signals a disastrous age-to-come. Yet whether seen as dream or nightmare, automation, argues Munn, is ultimately a fable that rests on a set of triple fictions. There is the myth of full autonomy, claiming that machines will take over production and supplant humans. But far from being self-acting, technical solutions are piecemeal; their support and maintenance reveals the immense human labor behind "autonomous" processes. There is the myth of universal automation, with technologies framed as a desituated force sweeping the globe. But this fiction ignores the social, cultural, and geographical forces that shape technologies at a local level. And, there is the myth of automating everyone, the generic figure of "the human" at the heart of automation claims. But labor is socially stratified and so automation's fallout will be highly uneven, falling heavier on some (immigrants, people of color, women) than others. Munn moves from machine minders in China to warehouse pickers in the United States to explore the ways that new technologies do (and don't) reconfigure labor. Combining this rich array of human stories with insights from media and cultural studies, Munn points to a more nuanced, localized, and racialized understanding of the "future of work."
After a quick glance at the plant floor, it is very easy to see the industrial automation industry interoperates with other functions within the enterprise. Trying to keep up with changing technologies, however, is never easy and the industrial automation environment is no exception. Whether you are a student just starting out or are a top-level executive or manager well-versed in one domain, but have limited knowledge of the industrial automation industry, itA's easy to find yourself adrift in this evolving industry. That is where this easy-to-read book comes in; it provides a basic functional understanding in the field of industrial automation. In an effort to understand this industry, the authors break down the barriers and confusion surrounding the technical details and terminology used in this converging field. They provide an introductory-level approach, covering most of the major industrial automation topics, such as distributed control systems (DCSs), programmable logic controllers (PLCs), manufacturing execution systems (MESs), and so on. You may even learn a recipe or two. This book is ideal for executives, business managers, information technologists, accountants, maintenance professionals, operators, production planners, just to name a few, and provides an in-depth but easy overview for people new to the field who want to quickly educate themselves.
From the global automation leaders at Accenture—the first-ever comprehensive blueprint for how to use and scale AI-powered intelligent automation in the enterprise to gain competitive advantage through faster speed to market, improved product quality, higher efficiency, and an elevated customer experience. Many companies were already implementing limited levels of automation when the pandemic hit. But the need to rapidly change business processes and how organizations work resulted in the compression of a decade’s worth of digital transformation into a matter of months. Technology suddenly became the essential element for rapid organizational change and the creation of 360-degree value benefiting all stakeholders. Businesses are faced with the imperative to embrace that change or risk being left behind. In The Automation Advantage, global enterprise technology and automation veterans Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail give business leaders and managers the action plan they need to execute a strategic agenda that enables them to quickly and confidently scale their automation and AI initiatives. This practical and highly accessible implementation guide answers leaders’ burning questions, such as: How do I identify and prioritize automation opportunities? How do I assess my legacy systems and data issues? How do I derive full value out of my technology investments and automation efforts? How can I inspire my employees to embrace change and the new opportunities presented by automation? The Automation Advantage goes beyond optimizing process to using AI to transform almost any business activity in any industry to make it faster, more streamlined, cost efficient, and customer-focused—vastly improving overall productivity and performance. Featuring case studies of successful automation solutions, this indispensable road map includes guiding principles for technology, governance, culture, and leadership change. It offers a human-centric approach to AI and automation that leads to sustainable transformation and measurable business results.
Automating technologies threaten to usher in a workless future. But this can be a good thing—if we play our cards right. Human obsolescence is imminent. The factories of the future will be dark, staffed by armies of tireless robots. The hospitals of the future will have fewer doctors, depending instead on cloud-based AI to diagnose patients and recommend treatments. The homes of the future will anticipate our wants and needs and provide all the entertainment, food, and distraction we could ever desire. To many, this is a depressing prognosis, an image of civilization replaced by its machines. But what if an automated future is something to be welcomed rather than feared? Work is a source of misery and oppression for most people, so shouldn’t we do what we can to hasten its demise? Automation and Utopia makes the case for a world in which, free from need or want, we can spend our time inventing and playing games and exploring virtual realities that are more deeply engaging and absorbing than any we have experienced before, allowing us to achieve idealized forms of human flourishing. The idea that we should “give up” and retreat to the virtual may seem shocking, even distasteful. But John Danaher urges us to embrace the possibilities of this new existence. The rise of automating technologies presents a utopian moment for humankind, providing both the motive and the means to build a better future.
The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use
Like sysadmins before them, network engineers are finding that they cannot do their work manually anymore. As the field faces new protocols, technologies, delivery models, and a pressing need for businesses to be more agile and flexible, network automation is becoming essential. This practical guide shows network engineers how to use a range of technologies and tools—including Linux, Python, JSON, and XML—to automate their systems through code. Network programming and automation will help you simplify tasks involved in configuring, managing, and operating network equipment, topologies, services, and connectivity. Through the course of the book, you’ll learn the basic skills and tools you need to make this critical transition. This book covers: Python programming basics: data types, conditionals, loops, functions, classes, and modules Linux fundamentals to provide the foundation you need on your network automation journey Data formats and models: JSON, XML, YAML, and YANG for networking Jinja templating and its applicability for creating network device configurations The role of application programming interfaces (APIs) in network automation Source control with Git to manage code changes during the automation process How Ansible, Salt, and StackStorm open source automation tools can be used to automate network devices Key tools and technologies required for a Continuous Integration (CI) pipeline in network operations
A practical guide to industrial automation concepts, terminology, and applications Industrial Automation: Hands-On is a single source of essential information for those involved in the design and use of automated machinery. The book emphasizes control systems and offers full coverage of other relevant topics, including machine building, mechanical engineering and devices, manufacturing business systems, and job functions in an industrial environment. Detailed charts and tables serve as handy design aids. This is an invaluable reference for novices and seasoned automation professionals alike. COVERAGE INCLUDES: * Automation and manufacturing * Key concepts used in automation, controls, machinery design, and documentation * Components and hardware * Machine systems * Process systems and automated machinery * Software * Occupations and trades * Industrial and factory business systems, including Lean manufacturing * Machine and system design * Applications
Chasing Automation tells the story of how a group of reform-minded politicians during the heyday of America's industrial prowess (1921–1966) sought to plan for the technological future. Beginning with Warren G. Harding and the Conference he convened in 1921, Jerry Prout looks at how the US political system confronted the unemployment caused by automation. Both liberals and conservatives spoke to the crucial role of technology in economic growth and the need to find work for the unemployed, and Prout shows how their disputes turned on the means of achieving these shared goals and the barriers that stood in the way. This political history highlights the trajectories of two premier scientists of the period, Norbert Wiener and Vannevar Bush, who walked very different paths. Wiener began quietly developing his language of cybernetics in the 1920s though its effect would not be realized until the late 1940s. The more pragmatic Bush was tapped by FDR to organize the scientific community and his ultimate success—the Manhattan Project—is emblematic of the technological hubris of the era. Chasing Automation shows that as American industrial productivity dramatically increased, the political system was at the mercy of the steady advance of job replacing technology. It was the sheer unpredictability of technological progress that ultimately posed the most formidable challenge. Reformers did not succeed in creating a federal planning agency, but they did create a enduring safety net of laws that workers continue to benefit from today as we face a new wave of automation and artificial intelligence.