Automation Technology Quotes

AI-powered passive monitoring is taking off and has huge advantages over the traditional way of monitoring patients. The advantage of passive monitoring, as opposed to data collected from wearables, is that it doesn’t require patients or seniors to actively wear a device at all times. Used in a hospital setting, the tech reduces healthcare workers’ risk of exposure to COVID-19 by limiting their contact with patients and automating data collection for vital signs. Also, camera-based monitoring is unpopular for the simple reason that a lot of people don’t like being watched by a camera.

Tweet others the way you want to be tweeted.

One of the biggest mistakes we made was trying to automate things that are super easy for a person to do, but super hard for a robot to do.

If it hurts, do it more frequently, and bring the pain forward.

As AI continues to develop, machines could become increasingly legitimate in autonomously making strategic decisions, an area where humans currently lead.

As algorithms become the most important decision-makers in our lives, the question is not only whether we can trust AI, but whether we can trust that we understand AI well enough.

As advances in AI, machine learning, and neural networks evolve, incomprehensibility will reach even higher levels - exposing these complex systems to both human and machine errors.

There is no economic law that says that everyone, or even most people, automatically benefit from technological progress.

Since at least the Great Depression, we’ve been hearing warnings that automation was or was about to be throwing millions out of work—Keynes at the time coined the term “technological unemployment,” and many assumed the mass unemployment of the 1930s was just a sign of things to come—and while this might make it seem such claims have always been somewhat alarmist, what this book suggests is that the opposite was the case. They were entirely accurate. Automation did, in fact, lead to mass unemployment. We have simply stopped the gap by adding dummy jobs that are effectively made up. A combination of political pressure from both right and left, a deeply held popular feeling that paid employment alone can make one a full moral person, and finally, a fear on the part of the upper classes, already noted by George Orwell in 1933, of what the laboring masses might get up to if they had too much leisure on their hands, has ensured that whatever the underlying reality, when it comes to official unemployment figures in wealthy countries, the needle should never jump too far from the range of 3 to 8 percent. But if one eliminates bullshit jobs from the picture, and the real jobs that only exist to support them, one could say that the catastrophe predicted in the 1930s really did happen. Upward of 50 percent to 60 percent of the population has, in fact, been thrown out of work.

Like a car, a camera is sold as a predatory weapon—one that’s as automated as possible, ready to spring. Popular taste expects an easy, an invisible technology.

Everyone can enjoy a life of luxurious leisure if the machine-produced [robots] wealth is shared, or most people can end up miserably poor if the machine-owners successfully lobby against wealth redistribution. So far, the trend seems to be toward the second option, with technology driving ever-increasing inequality.

Man is to technology what the bee is to the flower. It’s man’s intervention that allows technology to expand and evolve itself and in return, technology offers man convenience, wealth and the lessening burden of physical labor via its automated systems.

acquiring more education and skills will not necessarily offer effective protection against job automation

Automation technologies have proved useful with regard to pandemic preparedness and response, but they can also be useful in building resilience against future shocks. Moving the automation agenda forward will be critical to creating more robust and resilient societies and achieving the sustainable development goals.

Developers should be able to run all automated tests on their workstations in order to triage and fix defects.

The turnaround is being driven by automation technology so efficient that it is competitive with even the lowest-wage offshore workers.

automation technology so efficient that it is competitive with even the lowest-wage offshore workers.

However, one intriguing shift that suggests there are limits to automation was the recent decision by Toyota to systematically put working humans back into the manufacturing process. In quality and manufacturing on a mass scale, Toyota has been a global leader in automation technologies based on the corporate philosophy of kaizen (Japanese for “good change”) or continuous improvement. After pushing its automation processes toward lights-out manufacturing, the company realized that automated factories do not improve themselves. Once Toyota had extraordinary craftsmen that were known as Kami-sama, or “gods” who had the ability to make anything, according to Toyota president Akio Toyoda.49 The craftsmen also had the human ability to act creatively and thus improve the manufacturing process. Now, to add flexibility and creativity back into their factories, Toyota chose to restore a hundred “manual-intensive” workspaces.

AI won’t replace humans, but people who can use it will.” This sounds reassuring, but it oversimplifies the complex future of work and AI integration. Experts predict a surge in opportunities, but the intricate interplay between cognification, mass automation, and how we work remains uncharted. The net effect of AI on employment is unknown - we have no data on the future.

a great many college-educated, white-collar workers are going to discover that their jobs, too, are squarely in the sights as software automation and predictive algorithms advance rapidly in capability.

We cannot deal with the increasing maldistribution of wealth, the increasing alienation of millions, or the lack of a unified purpose and goal by increasing the efficiency of production, increasing the automation of industry, accelerating our technology, or increasing our reliance on the profit motives of multinational corporations.

Where workers do lose their jobs due to automation, it’s not because they themselves are replaced by some piece of software. It’s often because the firms they work for fail. And the firms they work for fail because their management or shareholders are unwilling or unable to keep up with the new possibilities of technology. That failure often extends to failing to invest in the training that their employees need to implement the latest technologies.

Indeed, a 2013 study by Carl Benedikt Frey and Michael A. Osborne at the University of Oxford concluded that occupations amounting to nearly half of US total employment may be vulnerable to automation within roughly the next two decades.59

Technology isn’t what makes us “post-human” or “transhuman,” as some writers and scholars have recently suggested. It’s what makes us human. Technology is in our nature. Through our tools we give our dreams form. We bring them into the world. The practicality of technology may distinguish it from art, but both spring from a similar, distinctly human yearning.

The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency. —BILL GATES,

I find these comparisons particularly poignant: life versus death, hope versus fear. Space exploration and the highly mechanized destruction of people use similar technology and manufacturers, and similar human qualities of organization and daring. Can we not make the transition from automated aerospace killing to automated aerospace exploration of the solar system in which we live?

The Negro’s economic problem was compounded by the emergence and growth of automation. Since discrimination and lack of education confined him to unskilled and semi-skilled labor, the Negro was and remains the first to suffer in these days of great technological development.

The birth of the fast food industry coincided with Eisenhower-era glorifications of technology, with optimistic slogans like “Better Living through Chemistry” and “Our Friend the Atom.” The sort of technological wizardry that Walt Disney promoted on television and at Disneyland eventually reached its fulfillment in the kitchens of fast food restaurants. Indeed, the corporate culture of McDonald’s seems inextricably linked to that of the Disney empire, sharing a reverence for sleek machinery, electronics, and automation. The leading fast food chains still embrace a boundless faith in science—and as a result have changed not just what Americans eat, but also how their food is made.

The good news is that you can minimize the bias preserved by AI, but this comes as a joint responsibility between leaders, domain experts, and developers.

Automation is what most professionals have in mind when they think of the relevance of technology for their disciplines.

This automation therefore complements but does not fundamentally change the central way in which services are delivered.

chickens are grown to standardized sizes so as to make them compatible with automated slaughtering and processing.

As we begin to internalize the technological kingdoms we have built, as we progressively become more superhuman, what will differentiate us from machinery?

Thanks to technology, we now have access to the entirety of human knowledge from a device that fits in our pocket. The internet is humanity's greatest gift.

Digital disruption and the impact of coronavirus will bring the 2030 technological advancement earlier than predicted

It’s the same story, time and again: a new technology that promises to alleviate work degrades it instead.

AI powers the mind, Leadership fuels the heart, when they unite, Innovation and Vision never apart!" - Brahmanand Savanth

WorkFusion, a start-up company based in the New York City area, offers an especially vivid example of the dramatic impact that white-collar automation is likely to have on organizations. The

Many California farmers have transitioned from delicate crops like tomatoes to more robust nuts because they can be harvested mechanically. Overall agricultural employment in California fell by about 11 percent in the first decade of the twenty-first century, even as the total production of crops like almonds, which are compatible with automated farming techniques, has exploded.

Let us fool ourselves no longer. At the very moment Western nations, threw off the ancient regime of absolute government, operating under a once-divine king, they were restoring this same system in a far more effective form in their technology, reintroducing coercions of a military character no less strict in the organization of a factory than in that of the new drilled, uniformed, and regimented army. During the transitional stages of the last two centuries, the ultimate tendency of this system might b e in doubt, for in many areas there were strong democratic reactions; but with the knitting together of a scientific ideology, itself liberated from theological restrictions or humanistic purposes, authoritarian technics found an instrument at hand that h as now given it absolute command of physical energies of cosmic dimensions. The inventors of nuclear bombs, space rockets, and computers are the pyramid builders of our own age: psychologically inflated by a similar myth of unqualified power, boasting through their science of their increasing omnipotence, if not omniscience, moved by obsessions and compulsions no less irrational than those of earlier absolute systems: particularly the notion that the system itself must be expanded, at whatever eventual co st to life. Through mechanization, automation, cybernetic direction, this authoritarian technics has at last successfully overcome its most serious weakness: its original dependence upon resistant, sometimes actively disobedient servomechanisms, still human enough to harbor purposes that do not always coincide with those of the system. Like the earliest form of authoritarian technics, this new technology is marvellously dynamic and productive: its power in every form tends to increase without limits, in quantities that defy assimilation and defeat control, whether we are thinking of the output of scientific knowledge or of industrial assembly lines. To maximize energy, speed, or automation, without reference to the complex conditions that sustain organic life, have become ends in themselves. As with the earliest forms of authoritarian technics, the weight of effort, if one is to judge by national budgets, is toward absolute instruments of destruction, designed for absolutely irrational purposes whose chief by-product would be the mutilation or extermination of the human race. Even Ashurbanipal and Genghis Khan performed their gory operations under normal human limits. The center of authority in this new system is no longer a visible personality, an all-powerful king: even in totalitarian dictatorships the center now lies in the system itself, invisible but omnipresent: all its human components, even the technical and managerial elite, even the sacred priesthood of science, who alone have access to the secret knowledge by means of which total control is now swiftly being effected, are themselves trapped by the very perfection of the organization they have invented. Like the Pharoahs of the Pyramid Age, these servants of the system identify its goods with their own kind of well-being: as with the divine king, their praise of the system is an act of self-worship; and again like the king, they are in the grip of an irrational compulsion to extend their means of control and expand the scope of their authority. In this new systems-centered collective, this Pentagon of power, there is no visible presence who issues commands: unlike job's God, the new deities cannot be confronted, still less defied. Under the pretext of saving labor, the ultimate end of this technics is to displace life, or rather, to transfer the attributes of life to the machine and the mechanical collective, allowing only so much of the organism to remain as may be controlled and manipulated.

Technology had destabilized every atom of human nature, and a new class of chemicals with unpronounceable names could reduce people to machines. The human mind, like any other appliance, could be rewired and automated.

Whereas automation is the use of technology to support this traditional model, innovation enables ways of making practical expertise available that simply were not possible (or even imaginable) without the systems in question.

Indeed, a 2013 study by Carl Benedikt Frey and Michael A. Osborne at the University of Oxford concluded that occupations amounting to nearly half of US total employment may be vulnerable to automation within roughly the next two decades.

Sending e-mails and texts is an automated version of writing letters, whereas social networking is an innovative technology, by which we mean, in this context, that it gives rise to ways of communicating that were not possible in the past.

the income from traditional capital is even more unevenly shared out across society than the income from salaries and wages. This fact is true ‘without exception’, notes Thomas Piketty, in all countries and at all times for which data is available.

While lower-skill occupations will no doubt continue to be affected, a great many college-educated, white-collar workers are going to discover that their jobs, too, are squarely in the sights as software automation and predictive algorithms advance rapidly in capability.

At various times in the past, technological optimists have predicted that textile workers would benefit from factory automation, that women would be emancipated by washing machines and vacuum cleaners, and that racial discrimination would vanish in the age of computers. If only.

It is useful for companies to look at AI through the lens of business capabilities rather than technologies. Broadly speaking, AI can support three important business needs: automating business processes, gaining insight through data analysis, and engaging with customers and employees.

Between 1811 and 1817, a group of English textile workers whose jobs were threatened by the automated looms of the first Industrial Revolution rallied around a perhaps mythical, Robin Hood–like figure named Ned Ludd and attacked mills and machinery before being suppressed by the British government.

The history of the Luddites—the real ones, not the pejorative figment of the entrepreneurial imagination—gives us a framework to evaluate the utility of technologies and their social impacts. Erasing that history collapses our thinking about how tech and automation affect our working lives—and the choices we have to address the disruption they bring.

All descriptions of how near certainty is to be achieved are based primarily on emerging technologies. A Global Information Grid of “persistent surveillance” will gather information and share that information in a networked “collaborative information environment.” Automated systems will fuse that intelligence and make possible “virtual collaboration among geographically dispersed” analysts who will generate intelligence and, ultimately, knowledge. Some even assume that this “robust intelligence” will deliver not only a clear appreciation for the current situation, but also generate “predictive intelligence” that will allow US forces to “anticipate the unexpected." Despite its enthusiastic embrace, the assumption of near-certainty in future war is a dangerous fallacy.

Kensi Gounden, Highly innovative new technologies can be both disruptive and transformative, but technology adoption can also be incremental, such as simply automating a manual process. So introducing business technology innovations, either incremental or step-change, may embrace increasing online connectivity across the business, strategic technology acquisition and use or using time-saving technologies to improve internal communication.

The Negro's economic problem was compounded by the emergence and growth of automation. Since discrimination and lack of education confined him to unskilled and semi-skilled labor, the Negro was and remains the first to suffer in these days of great technological development. The Negro knew all too well that there was not in existence the kind of vigorous retraining program that could really help him to grapple with the magnitude of his problem.

advances in AI are poised to drive dramatic productivity increases and perhaps eventually full automation. Radiologists, for example, are trained to interpret the images that result from various medical scans. Image processing and recognition technology is advancing rapidly and may soon be able to usurp the radiologist’s traditional role. Software can already recognize people in photos posted on Facebook and even help identify potential terrorists in airports.

But if the technological Singularity can happen, it will. Even if all the governments of the world were to understand the “threat” and be in deadly fear of it, progress toward the goal would continue. In fact, the competitive advantage—economic, military, even artistic—of every advance in automation is so compelling that passing laws, or having customs, that forbid such things merely assures that someone else will. —Vernor Vinge, The Coming Technological Singularity, 1993

The coming wave of automation will move way beyond the factory or public infrastructure and into our very biological processes such as aging and even giving birth. Used as we are to the gradual societal shifts brought about by previous change waves, often allowing decades to adjust and respond, I ask if we as a tribe are ready to abdicate our human sovereignty to the faceless forces of technology? Are you ready for the biggest loss of free will and individual human control in history?

In the medium term, AI may automate our jobs, to bring both great prosperity and equality. Looking further ahead, there are no fundamental limits to what can be achieved. There is no physical law precluding particles from being organised in ways that perform even more advanced computations than the arrangements of particles in human brains. An explosive transition is possible, although it may play out differently than in the movies. As mathematician Irving Good realised in 1965, machines with superhuman intelligence could repeatedly improve their design even further, in what science-fiction writer Vernor Vinge called a technological singularity. One can imagine such technology outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders and potentially subduing us with weapons we cannot even understand. Whereas the short-term impact of AI depends on who controls it, the long-term impact depends on whether it can be controlled at all.

Oath of Non-Harm for an Age of Big Data I swear to fulfill, to the best of my ability, the following covenant: I will respect all people for their integrity and wisdom, understanding that they are experts in their own lives, and will gladly share with them all the benefits of my knowledge. I will use my skills and resources to create bridges for human potential, not barriers. I will create tools that remove obstacles between resources and the people who need them. I will not use my technical knowledge to compound the disadvantage created by historic patterns of racism, classism, able-ism, sexism, homophobia, xenophobia, transphobia, religious intolerance, and other forms of oppression. I will design with history in mind. To ignore a four-century-long pattern of punishing the poor is to be complicit in the “unintended” but terribly predictable consequences that arise when equity and good intentions are assumed as initial conditions. I will integrate systems for the needs of people, not data. I will choose system integration as a mechanism to attain human needs, not to facilitate ubiquitous surveillance. I will not collect data for data’s sake, nor keep it just because I can. When informed consent and design convenience come into conflict, informed consent will always prevail. I will design no data-based system that overturns an established legal right of the poor. I will remember that the technologies I design are not aimed at data points, probabilities, or patterns, but at human beings.

America's poor and working-class people have long been subject to invasive surveillance, midnight raids, and punitive public policy that increase the stigma and hardship of poverty. During the nineteenth century, they were quarantined in county poorhouses. During the twentieth century, they were investigated by caseworkers, treated like criminals on trial. Today, we have forged what I call a digital poorhouse from databases, algorithms, and risk models. It promises to eclipse the reach and repercussions of everything that came before. Like earlier technological innovations in poverty management, digital tracking and automated decision-making hid poverty from the professional middle-class public and give the nation the ethical distance it needs to make inhuman choices: who gets food and who starves, who has housing and who remains homeless, and which families are broken up by the state. The digital poorhouse is part of a long American tradition. We manage the individual poor in order to escape our shared responsibility for eradicating poverty.

As black-box technologies become more widespread, there have been no shortage of demands for increased transparency. In 2016 the European Union's General Data Protection Regulation included in its stipulations the "right to an explanation," declaring that citizens have a right to know the reason behind the automated decisions that involve them. While no similar measure exists in the United States, the tech industry has become more amenable to paying lip service to "transparency" and "explainability," if only to build consumer trust. Some companies claim they have developed methods that work in reverse to suss out data points that may have triggered the machine's decisions—though these explanations are at best intelligent guesses. (Sam Ritchie, a former software engineer at Stripe, prefers the term "narratives," since the explanations are not a step-by-step breakdown of the algorithm's decision-making process but a hypothesis about reasoning tactics it may have used.) In some cases the explanations come from an entirely different system trained to generate responses that are meant to account convincingly, in semantic terms, for decisions the original machine made, when in truth the two systems are entirely autonomous and unrelated. These misleading explanations end up merely contributing another layer of opacity. "The problem is now exacerbated," writes the critic Kathrin Passig, "because even the existence of a lack of explanation is concealed.

THE RIVE BROTHERS used to be like a technology gang. In the late 1990s, they would jump on skateboards and zip around the streets of Santa Cruz, knocking on the doors of businesses and asking if they needed any help managing their computing systems. The young men, who had all grown up in South Africa with their cousin Elon Musk, soon decided there must be an easier way to hawk their technology smarts than going door-to-door. They wrote some software that allowed them to take control of their clients’ systems from afar and to automate many of the standard tasks that companies required, such as installing updates for applications. The software became the basis of a new company called Everdream, and the brothers promoted their technology in some compelling ways.

GET BEYOND THE ONE-MAN SHOW Great organizations are never one-man operations. There are 22 million licensed small businesses in America that have no employees. Forbes suggests 75 percent of all businesses operate with one person. And the average income of those companies is a sad $44,000. That’s not a business—that’s torture. That is a prison where you are both the warden and the prisoner. What makes a person start a business and then be the only person who works there? Are they committed to staying small? Or maybe an entrepreneur decides that because the talent pool is so poor, they can’t hire anyone who can do it as well as them, and they give up. My guess is the latter: Most people have just given up and said, “It’s easier if I just do it myself.” I know, because that’s what I did—and it was suicidal. Because my business was totally dependent on me and only me, I was barely able to survive, much less grow, for the first ten years. Instead I contracted another company to promote my seminars. When I hired just one person to assist me out of my home office, I thought I was so smart: Keep it small. Keep expenses low. Run a tight ship. Bigger isn’t always better. These were the things I told myself to justify not growing my business. I did this for years and even bragged about how well I was doing on my own. Then I started a second company with a partner, a consulting business that ran parallel to my seminar business. This consulting business quickly grew bigger than my first business because my partner hired people to work for us. But even then I resisted bringing other people into the company because I had this idea that I didn’t want the headaches and costs that come with managing people. My margins were monster when I had no employees, but I could never grow my revenue line without killing myself, and I have since learned that is where all my attention and effort should have gone. But with the efforts of one person and one contracted marketing company, I could expand only so much. I know that a lot of speakers and business gurus run their companies as one-man shows. Which means that while they are giving advice to others about how to grow a business, they may have never grown one themselves! Their one-man show is simply a guy or gal going out, collecting a fee, selling time and a few books. And when they are out speaking, the business terminates all activity. I started studying other people and companies that had made it big and discovered they all had lots of employees. The reality is you cannot have a great business if it’s just you. You need to add other people. If you don’t believe me, try to name one truly great business that is successful, ongoing, viable, and growing that doesn’t have many people making it happen. Good luck. Businesses are made of people, not just machines, automations, and technology. You need people around you to implement programs, to add passion to the technology, to serve customers, and ultimately to get you where you want to go. Consider the behemoth online company Amazon: It has more than 220,000 employees. Apple has more than 100,000; Microsoft has around the same number. Ernst & Young has more than 200,000 people. Apple calls the employees working in its stores “Geniuses.” Don’t you want to hire employees deserving of that title too? Think of how powerful they could make your business.

It’s hard to believe you’d have an economy at all if you gave pink slips to more than half the labor force. But that—in slow motion—is what the industrial revolution did to the workforce of the early 19th century. Two hundred years ago, 70 percent of American workers lived on the farm. Today automation has eliminated all but 1 percent of their jobs, replacing them (and their work animals) with machines. But the displaced workers did not sit idle. Instead, automation created hundreds of millions of jobs in entirely new fields. Those who once farmed were now manning the legions of factories that churned out farm equipment, cars, and other industrial products. Since then, wave upon wave of new occupations have arrived—appliance repair person, offset printer, food chemist, photographer, web designer—each building on previous automation. Today, the vast majority of us are doing jobs that no farmer from the 1800s could have imagined.

Things were not quite as sweet when Danielle Mitterrand toured the factory. The Cuba-admiring wife of France’s socialist president François Mitterrand asked a lot of questions, through her translator, about the working conditions, while Jobs, who had grabbed Alain Rossmann to serve as his translator, kept trying to explain the advanced robotics and technology. After Jobs talked about the just-in-time production schedules, she asked about overtime pay. He was annoyed, so he described how automation helped him keep down labor costs, a subject he knew would not delight her. “Is it hard work?” she asked. “How much vacation time do they get?” Jobs couldn’t contain himself. “If she’s so interested in their welfare,” he said to her translator, “tell her she can come work here any time.” The translator turned pale and said nothing. After a moment Rossmann stepped in to say, in French, “M. Jobs says he thanks you for your visit and your interest in the factory.

Imagine that seven out of ten working Americans got fired tomorrow. What would they all do? It’s hard to believe you’d have an economy at all if you gave pink slips to more than half the labor force. But that—in slow motion—is what the industrial revolution did to the workforce of the early 19th century. Two hundred years ago, 70 percent of American workers lived on the farm. Today automation has eliminated all but 1 percent of their jobs, replacing them (and their work animals) with machines. But the displaced workers did not sit idle. Instead, automation created hundreds of millions of jobs in entirely new fields. Those who once farmed were now manning the legions of factories that churned out farm equipment, cars, and other industrial products. Since then, wave upon wave of new occupations have arrived—appliance repair person, offset printer, food chemist, photographer, web designer—each building on previous automation. Today, the vast majority of us are doing jobs that no farmer from the 1800s could have imagined. It

Preventing job losses altogether is an unattractive and probably untenable strategy, because it means giving up the immense positive potential of AI and robotics. Nevertheless, governments might decide to deliberately slow down the pace of automation, in order to lessen the resulting shocks and allow time for readjustments. Technology is never deterministic, and the fact that something can be done does not mean it must be done. Government regulation can successfully block new technologies even if they are commercially viable and economically lucrative. For example, for many decades we have had the technology to create a marketplace for human organs, complete with human ‘body farms’ in underdeveloped countries and an almost insatiable demand from desperate affluent buyers. Such body farms could well be worth hundreds of billions of dollars. Yet regulations have prevented free trade in human body parts, and though there is a black market in organs, it is far smaller and more circumscribed than what one could have expected.22

One of those was Gary Bradski, an expert in machine vision at Intel Labs in Santa Clara. The company was the world’s largest chipmaker and had developed a manufacturing strategy called “copy exact,” a way of developing next-generation manufacturing techniques to make ever-smaller chips. Intel would develop a new technology at a prototype facility and then export that process to wherever it planned to produce the denser chips in volume. It was a system that required discipline, and Bradski was a bit of a “Wild Duck”—a term that IBM originally used to describe employees who refused to fly in formation—compared to typical engineers in Intel’s regimented semiconductor manufacturing culture. A refugee from the high-flying finance world of “quants” on the East Coast, Bradski arrived at Intel in 1996 and was forced to spend a year doing boring grunt work, like developing an image-processing software library for factory automation applications. After paying his dues, he was moved to the chipmaker’s research laboratory and started researching interesting projects. Bradski had grown up in Palo Alto before leaving to study physics and artificial intelligence at Berkeley and Boston University. He returned because he had been bitten by the Silicon Valley entrepreneurial bug.

The cheerleaders of the new data regime rarely acknowledge the impacts of digital decision-making on poor and working-class people. This myopia is not shared by those lower on the economic hierarchy, who often see themselves as targets rather than beneficiaries of these systems. For example, one day in early 2000, I sat talking to a young mother on welfare about her experiences with technology. When our conversation turned to EBT cards, Dorothy Allen said, “They’re great. Except [Social Services] uses them as a tracking device.” I must have looked shocked, because she explained that her caseworker routinely looked at her purchase records. Poor women are the test subjects for surveillance technology, Dorothy told me. Then she added, “You should pay attention to what happens to us. You’re next.” Dorothy’s insight was prescient. The kind of invasive electronic scrutiny she described has become commonplace across the class spectrum today. Digital tracking and decision-making systems have become routine in policing, political forecasting, marketing, credit reporting, criminal sentencing, business management, finance, and the administration of public programs. As these systems developed in sophistication and reach, I started to hear them described as forces for control, manipulation, and punishment

Gadgetry will continue to relieve mankind of tedious jobs. Kitchen units will be devised that will prepare ‘automeals,’ heating water and converting it to coffee; toasting bread; frying, poaching or scrambling eggs, grilling bacon, and so on. Breakfasts will be ‘ordered’ the night before to be ready by a specified hour the next morning. Communications will become sight-sound and you will see as well as hear the person you telephone. The screen can be used not only to see the people you call but also for studying documents and photographs and reading passages from books. Synchronous satellites, hovering in space will make it possible for you to direct-dial any spot on earth, including the weather stations in Antarctica. [M]en will continue to withdraw from nature in order to create an environment that will suit them better. By 2014, electroluminescent panels will be in common use. Ceilings and walls will glow softly, and in a variety of colors that will change at the touch of a push button. Robots will neither be common nor very good in 2014, but they will be in existence. The appliances of 2014 will have no electric cords, of course, for they will be powered by long- lived batteries running on radioisotopes. “[H]ighways … in the more advanced sections of the world will have passed their peak in 2014; there will be increasing emphasis on transportation that makes the least possible contact with the surface. There will be aircraft, of course, but even ground travel will increasingly take to the air a foot or two off the ground. [V]ehicles with ‘Robot-brains’ … can be set for particular destinations … that will then proceed there without interference by the slow reflexes of a human driver. [W]all screens will have replaced the ordinary set; but transparent cubes will be making their appearance in which three-dimensional viewing will be possible. [T]he world population will be 6,500,000,000 and the population of the United States will be 350,000,000. All earth will be a single choked Manhattan by A.D. 2450 and society will collapse long before that! There will, therefore, be a worldwide propaganda drive in favor of birth control by rational and humane methods and, by 2014, it will undoubtedly have taken serious effect. Ordinary agriculture will keep up with great difficulty and there will be ‘farms’ turning to the more efficient micro-organisms. Processed yeast and algae products will be available in a variety of flavors. The world of A.D. 2014 will have few routine jobs that cannot be done better by some machine than by any human being. Mankind will therefore have become largely a race of machine tenders. Schools will have to be oriented in this direction…. All the high-school students will be taught the fundamentals of computer technology will become proficient in binary arithmetic and will be trained to perfection in the use of the computer languages that will have developed out of those like the contemporary “Fortran". [M]ankind will suffer badly from the disease of boredom, a disease spreading more widely each year and growing in intensity. This will have serious mental, emotional and sociological consequences, and I dare say that psychiatry will be far and away the most important medical specialty in 2014. [T]he most glorious single word in the vocabulary will have become work! in our a society of enforced leisure.

Get unlіmіtеd Free Gеmѕ іn gаmе bу uѕіng оur Lоrdѕ Mоbіlе hасk tооl. Yоu саn uѕе оur hасk whеthеr уоu’rе оn а рhоnе, tаblеt оr PC. It wоrkѕ fоr Andrоіd & іOS dеvісеѕ аnd уоu dоn’t nееd tо јаіlbrеаk оr rооt. Bу uѕіng оur оnlіnе сhеаtѕ tооl, уоu dоn’t nееd tо dоwnlоаd ѕоmеthіng lіkе іnѕtаll hасk tооl еxе fіlе tо уоur соmрutеr bесаuѕе оur tооl іѕ brоwѕеr bаѕеd. And аlѕо Lоrdѕ Mоbіlе сhеаtѕ іѕ frеquеntlу uрdаtеѕ аnd еаѕу tо uѕе. јuѕt сlісk buttоn bеlоw tо ѕtаrt. [Cору lіnk tо уоur brоwѕеr tо vіѕіt] ==>> lordgems.xyz Follow these steps to get your FREE GEMS : 1. Visit lordgems.xyz 2. Enter your " Username " 3. Select Server to Use : Server 1 or 2 4. Select Platform: iOS or Android 5. Click on, "START PROCESS" 6. Select amount of Gems : 10.000, 25.000, 50.000, 100.000 7. Click on, "GENERATE NOW" 8. Click on, "VERIFY" to verify that you are a human and not an automated bot. 9. Click on an OFFER to complete the HUMAN VERIFICATION (Many bots harvest Gems from this site) 10. Enjoy your free Lord Mobile GEMS Game Features ✔ Real-time, multiplayer strategy with RPG elements! ✔ Fight in PvP battles with millions of players around the world! ✔ Spy on your enemies to plan the perfect assault! ✔ Discover an epic world in stunning HD graphics and 3D battle views! ✔ Slay monsters on the world map to find rare treasures! ✔ Upgrade buildings, research technologies, train troops, and do whatever it takes to build and customize the ultimate empire! ✔ Lock your opponents’ Heroes in Prison and make them pay for their release! ✔ Unite your allies in powerful Guilds to conquer the world! ✔ Play on multiple mobile phones and tablets anytime, anywhere, with anyone!” ― Lords Mobile Hack And Cheats Online 2018 No Survey

Therefore, when labour-saving technology reduces total socially necessary labour time (per commodity – for an increase in the number of commodities made may increase socially necessary labour time in absolute terms), there tends to be a relative fall in the surplus value contained in the total value of commodities, ie less surplus value per commodity, despite the fact that the rate of exploitation has increased, ie that each worker is now giving the capitalist more surplus labour time and therefore producing more surplus value relative to their necessary labour. As Grossman says: “Technological progress means that since commodities are created with a smaller expenditure of labour their value falls. This is not only true of the newly produced commodities. The fall in value reacts back on the commodities that are still on the market but which were produced under the older methods, involving a greater expenditure of labour time. These commodities are devalued.”[67] The very possibility of crisis is contained in the contradictory nature of the commodity. It is at once an object of use, or use-value, and something that can be exchanged for another thing, an exchange-value. Since different commodities contain different magnitudes of value and therefore cannot be directly exchanged, the creation of money proceeds logically and historically from the contradiction. It is not the exchange of commodities which regulates the magnitude of their value, but the magnitude of their value which controls their exchange value. Exchange-value is the only form in which the value of commodities can be expressed. Someone will buy a use-value because they need or want it, but only if they can exchange it for something else, ie money. If they do not have enough money, they cannot buy it, and profit goes unrealised. But to focus on this final ‘surface level’ aspect is what produces the mistaken underconsumptionist theory, for it forgets or ignores where it arose from – the dual character of the commodity.

HOW TO CREATE A GOOD HABIT The 1st Law: Make It Obvious 1.1: Fill out the Habits Scorecard. Write down your current habits to become aware of them. 1.2: Use implementation intentions: “I will [BEHAVIOR] at [TIME] in [LOCATION].” 1.3: Use habit stacking: “After I [CURRENT HABIT], I will [NEW HABIT].” 1.4: Design your environment. Make the cues of good habits obvious and visible. The 2nd Law:Make It Attractive 2.1: Use temptation bundling. Pair an action you want to do with an action you need to do. 2.2: Join a culture where your desired behavior is the normal behavior. 2.3: Create a motivation ritual. Do something you enjoy immediately before a difficult habit. The 3rd Law: Make It Easy 3.1: Reduce friction. Decrease the number of steps between you and your good habits. 3.2: Prime the environment. Prepare your environment to make future actions easier. 3.3: Master the decisive moment. Optimize the small choices that deliver outsized impact. 3.4: Use the Two-Minute Rule. Downscale your habits until they can be done in two minutes or less. 3.5: Automate your habits. Invest in technology and onetime purchases that lock in future behavior. The 4th Law: Make It Satisfying 4.1: Use reinforcement. Give yourself an immediate reward when you complete your habit. 4.2: Make “doing nothing” enjoyable. When avoiding a bad habit, design a way to see the benefits. 4.3: Use a habit tracker. Keep track of your habit streak and “don’t break the chain.” 4.4: Never miss twice. When you forget to do a habit, make sure you get back on track immediately. HOW TO BREAK A BAD HABIT Inversion of the 1st Law: Make It Invisible 1.5: Reduce exposure. Remove the cues of your bad habits from your environment. Inversion of the 2nd Law: Make It Unattractive 2.4: Reframe your mind-set. Highlight the benefits of avoiding your bad habits. Inversion of the 3rd Law: Make It Difficult 3.6: Increase friction. Increase the number of steps between you and your bad habits. 3.7: Use a commitment device. Restrict your future choices to the ones that benefit you. Inversion of the 4th Law: Make It Unsatisfying 4.5: Get an accountability partner. Ask someone to watch your behavior. 4.6: Create a habit contract. Make the costs of your bad habits public and painful.

It describes a significantly different way of life. For instance, the Manuscript predicts that we humans will voluntarily decrease our population so that we all may live in the most powerful and beautiful places on the Earth. But remarkably, many more of these areas will exist in the future, because we will intentionally let the forests go uncut so that they can mature and build energy. “According to the Ninth Insight, by the middle of the next millennium,” he continued, “humans will typically live among five hundred year old trees and carefully tended gardens, yet within easy travel distance of an urban area of incredible technological wizardry. By then, the means of survival—foodstuffs and clothing and transportation—will all be totally automated and at everyone’s disposal. Our needs will be completely met without the exchange of any currency, yet also without any overindulgence or laziness. “Guided by their intuitions, everyone will know precisely what to do and when to do it, and this will fit harmoniously with the actions of others. No one will consume excessively because we will have let go of the need to possess and to control for security. In the next millennium, life will have become about something else. “According to the Manuscript,” he went on, “our sense of purpose will be satisfied by the thrill of our own evolution—by the elation of receiving intuitions and then watching closely as our destinies unfold. The Ninth depicts a human world where everyone has slowed down and become more alert, ever vigilant for the next meaningful encounter that comes along. We will know that it could occur anywhere: on a path that winds through a forest, for instance, or on a bridge that traverses some canyon. “Can you visualize human encounters that have this much meaning and significance? Think how it would be for two people meeting for the first time. Each will first observe the other’s energy field, exposing any manipulations. Once clear, they will consciously share life stories until, elatedly, messages are discovered. Afterward, each will go forward again on their individual journey, but they will be significantly altered. They will vibrate at a new level and will thereafter touch others in a way not possible before their meeting.

Some of these bots are already arriving in 2021 in more primitive forms. Recently, when I was in quarantine at home in Beijing, all of my e-commerce packages and food were delivered by a robot in my apartment complex. The package would be placed on a sturdy, wheeled creature resembling R2-D2. It could wirelessly summon the elevator, navigate autonomously to my door, and then call my phone to announce its arrival, so I could take the package, after which it would return to reception. Fully autonomous door-to-door delivery vans are also being tested in Silicon Valley. By 2041, end-to-end delivery should be pervasive, with autonomous forklifts moving items in the warehouse, drones and autonomous vehicles delivering the boxes to the apartment complex, and the R2-D2 bot delivering the package to each home. Similarly, some restaurants now use robotic waiters to reduce human contact. These are not humanoid robots, but autonomous trays-on-wheels that deliver your order to your table. Robot servers today are both gimmicks and safety measures, but tomorrow they may be a normal part of table service for many restaurants, apart from the highest-end establishments or places that cater to tourists, where the human service is integral to the restaurant’s charm. Robots can be used in hotels (to clean and to deliver laundry, suitcases, and room service), offices (as receptionists, guards, and cleaning staff), stores (to clean floors and organize shelves), and information outlets (to answer questions and give directions at airports, hotels, and offices). In-home robots will go beyond the Roomba. Robots can wash dishes (not like a dishwasher, but as an autonomous machine in which you can pile all the greasy pots, utensils, and plates without removing leftover food, with all of them emerging cleaned, disinfected, dried, and organized). Robots can cook—not like a humanoid chef, but like an automated food processor connected to a self-cooking pot. Ingredients go in and the cooked dish comes out. All of these technology components exist now—and will be fine-tuned and integrated in the decade to come. So be patient. Wait for robotics to be perfected and for costs to go down. The commercial and subsequently personal applications will follow. By 2041, it’s not far-fetched to say that you may be living a lot more like the Jetsons!

In the past decade, the historically consistent division in the United States between the share of total national income going to labor and that going to physical capital seems to have changed significantly. As the economists Susan Fleck, John Glaser, and Shawn Sprague noted in the U.S. Bureau of Labor Statistics’ Monthly Labor Review in 2011, “Labor share averaged 64.3 percent from 1947 to 2000. Labor share has declined over the past decade, falling to its lowest point in the third quarter of 2010, 57.8 percent.” Recent moves to “re-shore” production from overseas, including Apple’s decision to produce its new Mac Pro computer in Texas, will do little to reverse this trend. For in order to be economically viable, these new domestic manufacturing facilities will need to be highly automated. Other countries are witnessing similar trends. The economists Loukas Karabarbounis and Brent Neiman have documented significant declines in labor’s share of GDP in 42 of the 59 countries they studied, including China, India, and Mexico. In describing their findings, Karabarbounis and Neiman are explicit that progress in digital technologies is an important driver of this phenomenon: “The decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced firms to shift away from labor and toward capital. The lower price of investment goods explains roughly half of the observed decline in the labor share.

The fascination with automation in part reflected the country’s mood in the immediate postwar period, including a solid ideological commitment to technological progress. Representatives of industry (along with their counterparts in science and engineering) captured this mood by championing automation as the next step in the development of new production machinery and American industrial prowess. These boosters quickly built up automation into “a new gospel of postwar economics,” lauding it as “a universal ideal” that would “revolutionize every area of industry.” 98 For example, the November 1946 issue of Fortune magazine focused on the prospects for “The Automatic Factory.” The issue included an article titled “Machines without Men” that envisioned a completely automated factory where virtually no human labor would be needed. 99 With visions of “transforming the entire manufacturing sector into a virtually labor-free enterprise,” factory owners in a range of industries began to introduce automation in the postwar period. 100 The auto industry moved with particular haste. After the massive wave of strikes in 1945–46, automakers seized on automation as a way to replace workers with machines. 101 As they converted back to civilian auto production after World War II, they took the opportunity to install new labor-saving automatic production equipment. The two largest automakers, Ford and General Motors, set the pace. General Motors introduced the first successful automated transfer line at its Buick engine plant in Flint in 1946 (shortly after a 113-day strike, the longest in the industry’s history). The next year Ford established an automation department (a Ford executive, Del S. Harder, is credited with coining the word “automation”). By October 1948 the department had approved $ 3 million in spending on 500 automated devices, with early company estimates predicting that these devices would result in a 20 percent productivity increase and the elimination of 1,000 jobs. Through the late 1940s and 1950s Ford led the way in what became known as “Detroit automation,” undertaking an expensive automation program, which it carried out in concert with the company’s plans to decentralize operations away from the city. A major component of this effort was the Ford plant in the Cleveland suburb of Brook Park, a $ 2 billion engine-making complex that attracted visitors from government, industry, and labor and became a national symbol of automation in the 1950s. 102

Corporate interests raised a nearly unified voice heralding automation as a certain and universal beneficial advancement. However, some observers saw the new technology as a cause for concern and cautioned that the final word on automation would depend on the choices that industry and the nation made in the face of difficult questions regarding the pace of automation’s implementation, the uses of the new productivity, and the fate of displaced workers as well as depleted or eliminated job classifications, communities, and even industries. Norbert Wiener, for example, a prominent MIT mathematician and pioneer in the science of cybernetics, emphasized the potentially calamitous economic and social consequences of the new production technology. Wiener had begun to express concerns about the impacts of automation on labor and the entire society during World War II, and he authored two books in the immediate Cold War years warning that potentially disastrous unemployment and related social problems may come from industry’s drive toward automation. He characterized automation and computer controls in the production process as the “modern” or “second” industrial revolution, which even more than the first held “unbounded possibilities for good and evil.” 104 In particular, Wiener feared that the larger impact of the changes caused by automation would be a massive displacement of workers, compounded by the profit-driven indifference of industry. “The automatic machine … will produce an unemployment situation, in comparison with which the present recession and even the depression of the thirties will seem a pleasant joke.” 105

RPA is software that emulates human execution of repetitive work. It's built on technologies designed to orchestrate, execute and enhance business workflows. Cognitive RPA adds intelligence the ability to perform human like decision making to RPA. CRPA can do things like read documents to identify specific information to pass to RPA to update another system. dayhuffgroup.com

such as AI, automation, algorithms, and Big Data, which constitute something like an immaterial field of often inscrutable forces within which we conduct our lives.

Another factor that’s likely to exacerbate inequality: next-generation automation. The technological revolution in the workplace has only just begun. A 2017 study published by the Institute for Spatial Economic Analysis found that nearly every major American city will see half of its current jobs replaced by robots by 2035.

A combination of restrictive new rules and high-tech tools reversed the gains of the welfare rights movement. In 1973, nearly half of the people living under the poverty line in the United States received AFDC. A decade later, after the new technologies of welfare administration were introduced, the proportion had dropped to 30 percent. Today, it is less than 10 percent.

Solo businesses that hit the million-dollar range typically fall into six categories: 1. E-commerce; 2. Manufacturing; 3. Informational content creation; 4. Professional services and creative businesses, such as marketing firms, public speaking businesses, and consultancies. 5. Personal services firms, offering expertise, such as fitness coaching; 6. Real estate. These companies use outsourcing, automation, mobile technology, or a combination of all three to build, operate, and grow their businesses.

The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.

It is a useful way of thinking about why the Klan opposed immigration (which brought a bunch of new kids to the block who might mow the lawn for less money) and was anxious about technological change in general (the move from agrarian life to industrialized economy and then the attendant march of automation in factories meant jobs would become ever more difficult to come by).

Specifically, they argue that digital technology drives inequality in three different ways. First, by replacing old jobs with ones requiring more skills, technology has rewarded the educated: since the mid-1970s, salaries rose about 25% for those with graduate degrees while the average high school dropout took a 30% pay cut.45 Second, they claim that since the year 2000, an ever-larger share of corporate income has gone to those who own the companies as opposed to those who work there—and that as long as automation continues, we should expect those who own the machines to take a growing fraction of the pie. This edge of capital over labor may be particularly important for the growing digital economy, which tech visionary Nicholas Negroponte defines as moving bits, not atoms. Now that everything from books to movies and tax preparation tools has gone digital, additional copies can be sold worldwide at essentially zero cost, without hiring additional employees. This allows most of the revenue to go to investors rather than workers, and helps explain why, even though the combined revenues of Detroit’s “Big 3” (GM, Ford and Chrysler) in 1990 were almost identical to those of Silicon Valley’s “Big 3” (Google, Apple, Facebook) in 2014, the latter had nine times fewer employees and were worth thirty times more on the stock market.47 Figure 3.5: How the economy has grown average income over the past century, and what fraction of this income has gone to different groups. Before the 1970s, rich and poor are seen to all be getting better off in lockstep, after which most of the gains have gone to the top 1% while the bottom 90% have on average gained close to nothing.46 The amounts have been inflation-corrected to year-2017 dollars. Third, Erik and collaborators argue that the digital economy often benefits superstars over everyone else.

With the smart grid for energy and the smart grid for water—what’s technically called resource consumption optimization—we’re seeing the second wave. Next up is the automation and control of far more complex autonomous systems—such as self-driving cars.

Like earlier technological innovations in poverty management, digital tracking and automated decision-making hide poverty from the professional middle-class public and give the nation the ethical distance it needs to make inhuman choices: who gets food and who starves, who has housing and who remains homeless, and which families are broken up by the state. The digital poorhouse is part of a long American tradition. We manage the individual poor in order to escape our shared responsibility for eradicating poverty.

the autonomous-driving side of things, Alphabet (formerly Google), which has logged several million self-driving-car test miles, continues to lead the pack. At the end of 2016, it created a new business division, called Waymo, for its autonomous driving technology. In May 2017, Waymo and Lyft announced that they would work together on developing the technology, and later in the year, Alphabet invested $1 billion in the start-up. Others, like Cruise Automation (which GM acquired for $1 billion) and Comma.ai, which offers open-source autonomous driving technology in the same vein as Google’s Android mobile operating system, are chasing hard. Baidu, China’s leading Internet search company, has an autonomous-driving research center in Sunnyvale. Byton—backed by China’s Tencent, Foxconn, and the China Harmony New Energy auto retailer group—has an office in Mountain View, as does Didi Chuxing, the Chinese ride-sharing company in which Apple invested $1 billion. Many of these companies have taken not just inspiration but also talent from Tesla. Part of the value of an innovation cluster like Silicon Valley lies in the dispersal of intellectual labor from one node to the next. For instance, PayPal is well known in the Valley for producing a number of high performers who left the company to start, join, or invest in others. The so-called PayPal Mafia includes Reid Hoffman, who founded LinkedIn; Max Levchin, whose most recent of several start-ups is the financial services company Affirm; Peter Thiel, a Facebook board member and President Trump–supporting venture capitalist who cofounded “big data” company Palantir; Jeremy Stoppelman, who started reviews site Yelp; Keith Rabois, who was chief operating officer at Square and then joined Khosla Ventures; David Sacks, who sold Yammer to Microsoft for $1.2 billion and later became CEO at Zenefits; Jawed Karim, who cofounded YouTube; and one Elon Musk.

it’s worth investing ongoing effort into a suite that is reliable. One way to achieve this is to put automated tests that are not reliable in a separate quarantine suite that is run independently.5 Or, of course, you could just delete them. If they’re version-controlled (as they should be), you can always get them back.

Thanks to increasingly accessible technologies and infrastructures, even the smallest bed and breakfast can choose whether and what to automate

faster. Now, when new technology is brought in, your coworkers have a different calculus. If they can produce 20 percent more per employee, why not decrease the workweek to twenty-eight hours? (For all sectors, legislation dictates the required workweek cannot exceed thirty-five hours.)13 There is still market competition, and firms still fail, but the grow-or-die imperative doesn’t apply when your enterprise’s goal is no longer to maximize total profits but rather to maximize profit-per-worker. And instead of a race to the bottom, there’s pressure to make sure janitorial and other “dirty jobs” are well compensated. In time, many of these tasks will be automated. People used to fear that machines would bring about mass unemployment, but now you and most others look forward to the social impact of technological innovations.14

The bank knew exactly what it was looking for and how to go about it. There was consensus on two critical aspects: the system had to be centralized and had to be based on UNIX, even if that meant spending tonnes of money. MicroBanker, a fully integrated online banking automation system, developed by Citicorp Information Technology Industries Ltd (Citil), a Citibank subsidiary, fit the bill, but Citil was not willing to deal with HDFC Bank. A small outfit, Citil thought, would not be able to afford the system. Citil was expanding operations in Africa and Europe and was not too keen to sell the software to a start-up Indian bank. While Citil reluctantly made a presentation on the system, Citibank intervened before a deal could be signed, saying that selling MicroBanker to HDFC Bank could give the Indian bank more muscle as a competitor. Aditya had to call Rajesh Hukku, Citil head, to play ball and he relented. Citil later became i-Flex Solutions Ltd (now Oracle Financial Services Software Ltd).

Man: Don't these precedents suggest that there is something inherently pre-industrial about the applicability of libertarian ideas—that they necessarily presuppose a rather rural society in which technology and production are fairly simple, and in which the economic organization tends to be small-scale and localized? Well, let me separate that into two questions: one, how anarchists have felt about it, and two, what I think is the case. As far as anarchist reactions are concerned, there are two. There has been one anarchist tradition—and one might think, say, of Kropotkin as a representative—which had much of the character you describe. On the other hand there's another anarchist tradition that develops into anarcho-syndicalism which simply regarded anarchist ideas as the proper mode of organization for a highly complex advanced industrial society. And that tendency in anarchism merges, or at least inter-relates very closely with a variety of left-wing Marxism, the kind that one finds in, say, the Council Communists that grew up in the Luxemburgian tradition, and that is later represented by Marxist theorists like Anton Pannekoek, who developed a whole theory of workers' councils in industry and who is himself a scientist and astronomer, very much part of the industrial world. So which of these two views is correct? I mean, is it necessary that anarchist concepts belong to the pre-industrial phase of human society, or is anarchism the rational mode of organization for a highly advanced industrial society? Well, I myself believe the latter, that is, I think that industrialization and the advance of technology raise possibilities for self-management over a broad scale that simply didn't exist in an earlier period. And that in fact this is precisely the rational mode for an advanced and complex industrial society, one in which workers can very well become masters of their own immediate affairs, that is, in direction and control of the shop, but also can be in a position to make the major substantive decisions concerning the structure of the economy, concerning social institutions, concerning planning regionally and beyond. At present, institutions do not permit them to have control over the requisite information, and the relevant training to understand these matters. A good deal could be automated. Much of the necessary work that is required to keep a decent level of social life going can be consigned to machines—at least in principle—which means humans can be free to undertake the kind of creative work which may not have been possible, objectively, in the early stages of the industrial revolution.

Having automated tests that are reliable: when the automated tests pass, teams are confident that their software is releasable.

If your main interest is in the business uses of machine learning, this book can help you in at least six ways: to become a savvier consumer of analytics; to make the most of your data scientists; to avoid the pitfalls that kill so many data-mining projects; to discover what you can automate without the expense of hand-coded software; to reduce the rigidity of your information systems; and to anticipate some of the new technology that’s coming your way. I’ve seen too much time and money wasted trying to solve a problem with the wrong learning algorithm, or misinterpreting what the algorithm said. It doesn’t take much to avoid these fiascoes. In fact, all it takes is to read this book.

To have humans executing tests that should be automated is a waste of human potential.

This includes the creation of automated build, integration, and test processes so that we can immediately detect when a change has been introduced that takes us out of a correctly functioning and deployable state.

In addition to collecting telemetry from our production services and environments, we must also collect telemetry from our deployment pipeline when important events occur, such as when our automated tests pass or fail and when we perform deployments to any environment. We

all team members as well as passers-by can see the latest information at a glance: count of automated tests, velocity, incident reports, continuous integration status, and so on. This

intech automation is the study regarding automotive engineering for light and heavy vehicles in Brisbane Australia. Intech.edu.au is availing the courses automation.