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Four Fundamentals of Workplace Automation

As the automation of physical and knowledge work advances, many jobs will be redefined rather than eliminated – at least in the short term.

by Michael Chui, James Manyika, and Mehdi Miremadi

McKinsey Quarterly (November 2015)

The potential of artificial intelligence and advanced robotics to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by the likes of IBM’s Watson, Rethink Robotics’ Baxter, DeepMind, or Google’s driverless car. Just head to an airport: automated check-in kiosks now dominate many airlines’ ticketing areas. Pilots actively steer aircraft for just three to seven minutes of many flights, with autopilot guiding the rest of the journey. Passport-control processes at some airports can place more emphasis on scanning document bar codes than on observing incoming passengers.

What will be the impact of automation efforts like these, multiplied many times across different sectors of the economy? {1} Can we look forward to vast improvements in productivity, freedom from boring work, and improved quality of life? Should we fear threats to jobs, disruptions to organizations, and strains on the social fabric? {2}

Earlier this year, we launched research to explore these questions and investigate the potential that automation technologies hold for jobs, organizations, and the future of work. {3}. Our results to date suggest, first and foremost, that a focus on occupations is misleading. Very few occupations will be automated in their entirety in the near or medium term. Rather, certain activities are more likely to be automated, requiring entire business processes to be transformed, and jobs performed by people to be redefined, much like the bank teller’s job was redefined with the advent of ATMs.

More specifically, our research suggests that as many as 45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies (for more, explore our interactive examining the potential for US jobs to be automated, on Tableau Public) {4}, {5}. In the United States, these activities represent about $2 trillion in annual wages. Although we often think of automation primarily affecting low-skill, low-wage roles, we discovered that even the highest-paid occupations in the economy, such as financial managers, physicians, and senior executives, including CEOs, have a significant amount of activity that can be automated.

The organizational and leadership implications are enormous: leaders from the C-suite to the front line will need to redefine jobs and processes so that their organizations can take advantage of the automation potential that is distributed across them. And the opportunities extend far beyond labor savings. When we modeled the potential of automation to transform business processes across several industries, we found that the benefits (ranging from increased output to higher quality and improved reliability, as well as the potential to perform some tasks at superhuman levels) typically are between three and ten times the cost. The magnitude of those benefits suggests that the ability to staff, manage, and lead increasingly automated organizations will become an important competitive differentiator.

Our research is ongoing and in 2016 we will release a detailed report. What follows here are four interim findings elaborating on the core insight that the road ahead is less about automating individual jobs wholesale, than it is about automating the activities within occupations and redefining roles and processes.

1. The Automation of Activities

These preliminary findings are based on data for the US labor market. We structured our analysis around roughly 2,000 individual work activities {6}, and assessed the requirements for each of these activities against eighteen different capabilities that potentially could be automated (Exhibit 1). Those capabilities range from fine motor skills and navigating in the physical world, to sensing human emotion and producing natural language. We then assessed the “automatability” of those capabilities through the use of current, leading-edge technology, adjusting the level of capability required for occupations where work occurs in unpredictable settings.

Exhibit 1

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(Original URL: http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights/Business%20Technology/Four%20fundamentals%20of%20workplace%20automation/svg_QWeb_Automation_and_work_ex1.ashx?mw=510 )

The bottom line is that 45 percent of work activities could be automated using already demonstrated technology. If the technologies that process and “understand” natural language were to reach the median level of human performance, an additional thirteen percent of work activities in the US economy could be automated. The magnitude of automation potential reflects the speed with which advances in artificial intelligence and its variants, such as machine learning, are challenging our assumptions about what is automatable. It’s no longer the case that only routine, codifiable activities are candidates for automation and that activities requiring “tacit” knowledge or experience that is difficult to translate into task specifications are immune to automation.

In many cases, automation technology can already match, or even exceed, the median level of human performance required. For instance, Narrative Science’s artificial-intelligence system, Quill, analyzes raw data and generates natural language, writing reports in seconds that readers would assume were written by a human author. Amazon’s fleet of Kiva robots is equipped with automation technologies that plan, navigate, and coordinate among individual robots to fulfill warehouse orders roughly four times faster than the company’s previous system. IBM’s Watson can suggest available treatments for specific ailments, drawing on the body of medical research for those diseases.

2. The Redefinition of Jobs and Business Processes

According to our analysis, fewer than five percent of occupations can be entirely automated using current technology. However, about sixty percent of occupations could have thirty percent or more of their constituent activities automated. In other words, automation is likely to change the vast majority of occupations – at least to some degree – which will necessitate significant job redefinition and a transformation of business processes. Mortgage-loan officers, for instance, will spend much less time inspecting and processing rote paperwork and more time reviewing exceptions, which will allow them to process more loans and spend more time advising clients. Similarly, in a world where the diagnosis of many health issues could be effectively automated, an emergency room could combine triage and diagnosis and leave doctors to focus on the most acute or unusual cases while improving accuracy for the most common issues.

As roles and processes get redefined, the economic benefits of automation will extend far beyond labor savings. Particularly in the highest-paid occupations, machines can augment human capabilities to a high degree, and amplify the value of expertise by increasing an individual’s work capacity and freeing the employee to focus on work of higher value. Lawyers are already using text-mining techniques to read through the thousands of documents collected during discovery, and to identify the most relevant ones for deeper review by legal staff. Similarly, sales organizations could use automation to generate leads and identify more likely opportunities for cross-selling and upselling, increasing the time frontline salespeople have for interacting with customers and improving the quality of offers.

3. The Impact on High-Wage Occupations

Conventional wisdom suggests that low-skill, low-wage activities on the front line are the ones most susceptible to automation. We’re now able to scrutinize this view using the comprehensive database of occupations we created as part of this research effort. It encompasses not only occupations, work activities, capabilities, and their automatability, but also the wages paid for each occupation. {7}

Our work to date suggests that a significant percentage of the activities performed by even those in the highest-paid occupations (for example, financial planners, physicians, and senior executives) can be automated by adapting current technology. {8} For example, we estimate that activities consuming more than twenty percent of a CEO’s working time could be automated using current technologies. These include analyzing reports and data to inform operational decisions, preparing staff assignments, and reviewing status reports. Conversely, there are many lower-wage occupations such as home health aides, landscapers, and maintenance workers, where only a very small percentage of activities could be automated with technology available today (Exhibit 2).

Exhibit 2

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(Original URL: http://www.mckinsey.com/~/media/McKinsey/dotcom/Insights/Business%20Technology/Four%20fundamentals%20of%20workplace%20automation/png_QWeb_Automation_and_work_ex2.ashx?mw=510 )

4. The Future of Creativity and Meaning

Capabilities such as creativity and sensing emotions are core to the human experience and also difficult to automate. The amount of time that workers spend on activities requiring these capabilities, though, appears to be surprisingly low. Just four percent of the work activities across the US economy require creativity at a median human level of performance. Similarly, only 29 percent of work activities require a median human level of performance in sensing emotion.

While these findings might be lamented as reflecting the impoverished nature of our work lives, they also suggest the potential to generate a greater amount of meaningful work. This could occur as automation replaces more routine or repetitive tasks, allowing employees to focus more on tasks that utilize creativity and emotion. Financial advisors, for example, might spend less time analyzing clients’ financial situations, and more time understanding their needs and explaining creative options. Interior designers could spend less time taking measurements, developing illustrations, and ordering materials, and more time developing innovative design concepts based on clients’ desires.

These interim findings, emphasizing the clarity brought by looking at automation through the lens of work activities as opposed to jobs, are in no way intended to diminish the pressing challenges and risks that must be understood and managed. Clearly, organizations and governments will need new ways of mitigating the human costs, including job losses and economic inequality, associated with the dislocation that takes place as companies separate activities that can be automated from the individuals who currently perform them. Other concerns center on privacy, as automation increases the amount of data collected and dispersed. The quality and safety risks arising from automated processes and offerings also are largely undefined, while the legal and regulatory implications could be enormous. To take one case: who is responsible if a driverless school bus has an accident?

Nor do we yet have a definitive perspective on the likely pace of transformation brought by workplace automation. Critical factors include the speed with which automation technologies are developed, adopted, and adapted, as well as the speed with which organization leaders grapple with the tricky business of redefining processes and roles. These factors may play out differently across industries. Those where automation is mostly software based can expect to capture value much faster and at a far lower cost. (The financial-services sector, where technology can readily manage straight-through transactions and trade processing, is a prime example.) On the other hand, businesses that are capital or hardware intensive, or constrained by heavy safety regulation, will likely see longer lags between initial investment and eventual benefits, and their pace of automation may be slower as a result.

All this points to new top-management imperatives: keep an eye on the speed and direction of automation, for starters, and then determine where, when, and how much to invest in automation. Making such determinations will require executives to build their understanding of the economics of automation, the trade-offs between augmenting versus replacing different types of activities with intelligent machines, and the implications for human skill development in their organizations. The degree to which executives embrace these priorities will influence not only the pace of change within their companies, but also to what extent those organizations sharpen or lose their competitive edge.

Notes:
{1} Leading perspectives on the changes under way include Erik Brynjolfsson and Andrew McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, New York: W W Norton, 2014; Carl Benedikt Frey and Michael A Osborne, “The future of employment: How susceptible are jobs to computerisation?”, Oxford Martin School Programme on the Impacts of Future Technology, September 17 2013, futuretech.ox.ac.uk; and David H Autor, “Why are there still so many jobs? The history and future of workplace automation”, Journal of Economic Perspectives, Summer 2015, Volume 29, Number 3, pp. 3–30, aeaweb.org/jep.

{2} For a proposed agenda to examine some of these topics, see “Research priorities for robust and beneficial artificial intelligence: An open letter”, Future of Life Institute, January 11 2015, futureoflife.org.

{3}  This initiative builds on earlier McKinsey Global Institute (MGI) work describing a range of disruptive technologies, which could multiply the capacity of companies to automate physical and intellectual tasks. For the full MGI report, see “Disruptive technologies: Advances that will transform life, business, and the global economy”, May 2013. This research has examined the economic potential of disruptive technologies that can automate physical work (for example, advanced robotics, 3-D printing, and autonomous vehicles) as well as those that can automate knowledge work requiring intellectual effort and the ability to interact with others (for example, various types of artificial intelligence, machine learning, and deep learning).

{4} http://www.mckinsey.com/MGI/automationdataviz

{5} We define “currently demonstrated technologies” as ones that have already exhibited the level of performance and reliability needed to automate one or more of the eighteen capabilities required for carrying out work activities. In some cases, that performance has been demonstrated in a commercially available product and in others as part of a research project.

{6}  Our analysis used “detailed work activities,” as defined by O*NET, a program sponsored by the US Department of Labor, Employment and Training Administration.

{7} In addition to analyzing the relationship between automatability and compensation levels, the inclusion of wages allows us to compare the potential costs to implement automation with labor costs, which inherently reflect supply, demand, and elasticity dynamics.

{8} Using a linear model, we find the correlation between wages and automatability (the percentage of time spent on activities that can be automated by adapting currently demonstrated technology) in the US economy to be significant (p-value < 0.01), but with a high degree of variability (r2 = 0.19).

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Michael Chui is a principal at the McKinsey Global Institute, where James Manyika is a director; Mehdi Miremadi is a principal in McKinsey’s Chicago office.

The authors wish to thank McKinsey’s Rick Cavolo, Martin Dewhurst, Katy George, Andrew Grant, Sean Kane, Bill Schaninger, Stefan Spang, and Paul Willmott for their contributions to this article.

http://www.mckinsey.com//Insights/Business_Technology/Four_fundamentals_of_workplace_automation

Categories: Uncategorized

Automation Doesn’t Just Destroy Jobs

It Destroys Profits, Too

by Charles Hugh Smith

Of Two Minds (November 08 2015)

The idea that taxing the owners of robots and software will fund guaranteed incomes for all is not anchored in reality.

Automation is upending the global order by eliminating human labor on an unprecedented scale – and the status quo has no reality-based solution to this wholesale loss of jobs.

Two recent articles highlighted the profound consequences of advances in robotics and AI (artificial intelligence) on employment {1, 2}.

The status quo apologists/punditry have offered two magical-thinking solutions to the sweeping destruction of jobs across the entire spectrum of paid work:

1. Tax the robots (or owners of robots) and use the revenues to pay a guaranteed income to everyone who is unemployed or underemployed.

2. Let the price of labor fall to the point that everyone has a job of some sort, even if the pay is minimal.

Neither one is remotely practical, for reasons I will explain today and tomorrow.

Today, let’s examine the misguided fantasy that automation/robotics will generate enormous profits for the owners of robots. Here’s the problem in a nutshell:

As automation eats jobs, it also eats profits, since automation turns labor, goods and services into commodities. When something is commoditized, the price drops because the goods and services are interchangeable and can be produced almost anywhere.

Owners must move commoditized production to low-tax regions if they want to retain any profit at all.

Big profits flow from scarcity, that is, when demand exceeds supply. If supply exceeds demand, prices fall and profits vanish.

(Monopoly is a state-enforced scarcity. In our state-cartel economy, there are many monopolies or quasi-monopolies. While eliminating these would lower costs, that wouldn’t reverse the wholesale destruction of jobs and profits – it would only speed the process up.)

The other problem the “tax the robots and everything will be funded” crowd overlooks is the falling cost of software and robots lowers the barriers to competition: nothing destroys profits like wave after wave of hungry competitors entering a field.

The cost of automation and robotics is falling dramatically. This lowers the cost of entry for smaller, hungrier, more nimble competitors, and lowers the cost of increasing production. When virtually any small manufacturer can buy robots for less than the wages of a human laborer, where’s the scarcity necessary to generate profits?

The parts needed to assemble a $45 tablet [computer] are dropping in price, and the profit margins on those parts is razor-thin because they’re commodities. Software such as the Android operating system is free, and many of the software libraries needed to assemble new software are also free.

Automation increases supply and lowers costs. Both are deadly to profits.

Here’s the core problem with the idea that taxing the owners of robots and software will fund guaranteed incomes for all: the more labor, goods and services are automated/commoditized, the lower the profits.

The current narrative assumes more wealth will be created by the digital destruction of industries and jobs, but real-world examples suggest the exact opposite: the music industry has seen revenues fall in half as digital technology ate its way through the sector.

A $14 billion industry is now a $7 billion industry. Profits and payroll taxes collected from the industry have plummeted. So much for the fantasy that technology always creates more jobs than it destroys.

As subscription music services replace sales of songs and albums, revenues will continue to decline even as consumers have greater access to more products. In other words, the destruction of sales, employment and profits is far from over.

Examples of such radical reductions in paid labor abound in daily life. To take one small example, our refrigerator recently failed. The motor was running but the compartment wasn’t being cooled. Rather than replace the appliance for hundreds of dollars or hire a high-cost repair service, I looked online, diagnosed the problem as a faulty sensor, watched a tutorial on YouTube (what I call YouTube University), ordered a new sensor for less than $20 online and completed the repair at no cost beyond a half-hour of labor, which cost me nothing in terms of cash spent.

The profit earned by YouTube was minimal, as was the profit of the firms that manufactured the sensor and shipped it. The sales and profits that were bypassed by using nearly-free digital tools were an order of magnitude higher.

I was recently interviewed via Skype by an online journalist with millions of views of his YouTube channel. A decade ago when he worked in mainstream TV journalism, an interview required costly, time-consuming travel (for the crew or the subject), a sound engineer, a camera operator, the talent (interviewer), editor and managerial review. These six jobs have been rolled into one with digital tools, and travel has been eliminated entirely.

Some will argue that the quality of the video and sound isn’t as high, but the quality of the user experience is ultimately based on the viewer’s display, which is increasingly a phone or tablet. So in terms of utility, value and impact, the product (that is, output) produced by one person replaces the conventional media product that required six people.

My own solo digital content business would have required a handful of people (if not more) only a decade ago. With digital tools and services, it now requires just one person. Those of us who must work with digital tools to survive know firsthand that what once required a handful of workers must now be produced by one person if we hope to earn even a marginally middle-class income.

Multiply an appliance that doesn’t need to be replaced and a repair service that doesn’t need to be hired, a half-dozen positions replaced by one part-time job, a fully functional commodity tablet that costs ten percent of the high-profit brand and you understand why profits will plummet as software eats the world.

These are not starry-eyed examples based on projections; these are real-world examples of widely available digital technologies destroying costs, sales and profits on a massive scale.

Some observers have suggested taxing wealth rather than profits to fund the super welfare state of guaranteed income for all. But the value of assets ultimately rests on their ability to generate a profit. As profits fall, wealth may be more chimerical than these observers believe.

Tomorrow we’ll look at the rising costs of human labor and explore why this trend will persist even as labor becomes increasingly surplus.

This entry was drawn from my new book A Radically Beneficial World: Automation, Technology and Creating Jobs for All {3}.

Links:

{1} http://www.mckinsey.com//Insights/Business_Technology/Four_fundamentals_of_workplace_automation

{2} http://www.telegraph.co.uk/finance/economics/11978542/Robots-may-shatter-the-global-economic-order-within-a-decade.html

{3} http://www.amazon.com/gp/product/B0178MQI1M/ref=as_li_tl?ie=UTF8&camp=1789&creative=9325&creativeASIN=B0178MQI1M&linkCode=as2&tag=charleshughsm-20&linkId=VSSCC5UY23MIZ3MX

http://charleshughsmith.blogspot.jp/2015/11/automation-doesnt-just-destroy-jobs-it.html

Categories: Uncategorized

Is This the Terminal Phase …

… of Global Capitalism 1.0?

by Charles Hugh Smith

Of Two Minds (February 08 2013)

The road for both global capital and the State is narrowing to a rocky trail that leads to a cliff.

We turn to cycles – business, solar, Kondratieff, et cetera – to understand current events. But what if this era is not just a cycle but the terminal phase of Global Capitalism 1.0?

This heretical thought arises from the school of economic history pursued by Fernand Braudel and those he inspired. I have long recommended Braudel’s three volume history of early capitalism as essential reading for anyone seeking to understand modern global capitalism: Civilization & Capitalism, 15th to 18th Centuries:

The Structures of Everyday Life (Volume 1)

The Wheels of Commerce (Volume 2)

The Perspective of the World (Volume 3)

Of those continuing this “long duration” analysis, I find much of interest in the work of Giovanni Arrighi, The Long Twentieth Century: Money, Power and the Origins of Our Times (2010) and Immanuel Wallerstein, World-Systems Analysis: An Introduction (2004).

This school sets the current iteration of world capitalism as beginning in the 1450s. Everything that characterizes modern global capitalism was already operational by 1500: stock and bond exchanges, hedging with derivatives and insurance, joint stock ventures, highly profitable global trade, commercial credit/paper, central States funding their wars with privately provided credit, et cetera.

In Wallerstein’s analysis, the current form of global capitalism is running out of road. He identifies three long-term forces that are undermining capitalism’s key function, the accumulation of more capital:

1. Urbanization, which has increased the cost of labor.

2. Externalized costs (dumping private waste into the Commons, environmental damage and depletion, et cetera) are finally having to be paid.

3. Rising taxes as the Central State responds to unlimited demands by citizens for more services (education, healthcare, et cetera) and economic security (pensions, welfare).

Wallerstein is one of the few who clearly understands the State’s role as enabler and enforcer of monopolies and cartels. High profit margins are most easily maintained by persuading politicians to create and then regulate quasi-monopolies and cartels.

The State has two core mandates: enable and enforce quasi-monopolies and cartels for private capital, and satisfy enough of the citizenry’s unlimited demands for more services and economic security to provide political stability and thus maintain State/cadre/Aristocratic power.

If the State fails to maintain monopolistic cartels, profit margins plummet and capital is unable to maintain its spending on investment and labor. Simply put, the economy tanks as profits, investment and growth all stagnate.

If the State fails to satisfy enough of the citizenry’s unlimited demands for more of everything, it risks social instability.

That is the nation-state’s quandary everywhere. With growth slowing and parasitic monopolies increasingly difficult to maintain and justify, the State has less tax income to fund its ever-expanding social spending.

In response, the State raises taxes and borrows the difference between its spending and its revenues. This further squeezes spending as the cost of servicing debt rises along with the debt.

In the conventional view, global capital lowers its costs and therefore increases its profits by shifting production to locales with lower labor costs, few environmental restrictions and low taxes (or an affordable bribe structure).

Thus the opening of China was simply the latest opportunity for global capital to shift production to lower-cost areas. Restless capital is now leaving China as its population has moved en masse to urban zones and the cost of labor has risen, and those in the traditional camp are forecasting global capital will decamp to Africa and the remaining low-labor-cost nations in Asia such as Myanmar and Cambodia.

When global capital runs out of low-cost labor opportunities, profit margins decline and the jig is up.

The rapid progress of robotics and automated, networked software is upending this conventional view of capital running into a brick wall as labor costs rise globally. It is increasingly cheaper and less risky to replace human labor with machine and computational capital, for a reason that Wallerstein does not mention: labor does not just demand more services and benefits from the State, it also demands more benefits from employers.

Global capital is thus finding its input costs rising on virtually every front: energy and resources cost more, externalized costs are coming home to roost, urbanized labor demands higher wages and benefits, and the State is raising taxes to fulfill its ever-expanding promises of more services and security.

Investing in robotics and software offers temporary respite by cutting labor costs, but as everything that can be produced by machines or software becomes abundant, margins vanish.

Reducing labor’s share of production costs (and of value created) also has the consequence of reducing the total sum of wages available for consumption and taxes. This feeds the stagnation of the consumer-based economy and severely restricts the State’s ability to raise wage-based and consumption-based taxes.

As this low-growth, lower-profit margin cycle tightens, there is less capital available to invest in future production, and the “highest return investment” is increasingly political lobbying/bribery to enhance or solidify profits gained from quasi-monopolies and cartels.

But the State is also running out of air: parasitic cartels skim huge sums from the economy, diverting it to the very class (the financial Aristocracy, the Party leadership, et cetera) to whom the State is beholden. Since it cannot cut social spending without risking insurrection, the State is forced to borrow increasingly monumental sums to fund its dual mandate.

States that print their own currency are looking longingly at the printing press, tempted to fill the widening gap between their promised social spending and their tax revenues with phantom money. But like funding consumption with debt, this too is an end-game that leads to the same result: the destruction of the State and both its enforcement of profitable cartels and its vast social spending.

The road for both global capital and the State is narrowing to a rocky trail that leads to a cliff. Two sides of the same expansionist coin, neither can continue to expand in a world of diminishing return, shrinking margins, surplus labor, declining wages and tax base, higher input costs and a restive, entitled/high-expectations, urbanized and under-employed workforce.

The standard business cycle has no answer to these structural quandries, and even the credit expansion/renunciation Kondratieff cycle does not provide a model for the next global system, or perhaps non-system. Technology cannot provide the “solution” because technology replaces labor-intensive business models with new low-labor models of production and service.

There will be no labor-intensive technological revolutions, there will only be technological revolutions that radically reduce the need for human labor. Just as profit margins approach zero in a world of over-capacity and over-supply, so too does the the value of most labor decline.

These are not issues that are unique to capitalism; the same dynamics are pressing socialist states that own key industries and control the markets in their nations. The old ideological models of the 19th and 20th centuries are increasingly disconnected from the new realities of capital, State and labor.

We need a new model, and a re-hash of the old broken models will no longer do.

Note: Regarding yesterday’s math faux pas in which the percentages presented added up to 110%. Yikes! I took these directly from the article America’s misguided approach to social welfare (Foreign Affairs, January/February 2013, page 157). (It’s behind The Council on Foreign Relations paywall, so you’ll have to find a print copy.) This shows that you cannot blindly take numbers from mainstream media sources without doing a bit of addition. My apologies for the error.

http://www.oftwominds.com/blogfeb13/terminal-capitalism2-13.html

Categories: Uncategorized

The Greatest Threat to Humanity

by Jake Anderson

Anti Media (October 13 2015)

Stephen Hawking has been outspoken in recent years about the catastrophic dangers humanity faces in the 21st century. He said we should be cautious in attempting to contact aliens, warning that advanced extraterrestrial life may not be friendly toward us and could destroy the human race. He also stated we should be cautious in creating strong artificial intelligence. The renowned physicist joined Tesla’s Elon Musk, Apple co-founder Steve Wozniak, and Google executive Demis Hassabis in signing a letter that warned against a military artificial intelligence arms race.

Hawking even issued a warning to the scientists at the European Center for Nuclear Research (CERN) about the dangers of the Higgs Boson “God Particle”, claiming it could initiate “catastrophic vacuum decay” – a quantum bubble that expands at the speed of light and wipes out the universe.

Recently, Hawking addressed the threat he says may be more far more dangerous to the future of human civilization than robots, aliens, or quantum particles: capitalist greed. During a Reddit AMA, he argued that the future is wrought with the peril of rampant inequality expedited by an automated machine-based global economic system.

“If machines produce everything we need, the outcome will depend on how things are distributed”. Hawking continued,

 

Everyone can enjoy a life of luxurious leisure if the machine-produced 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.

 

Predictably, a dramatic response thread followed. Many commenters agreed with Hawking and denounced the globalist oligarchy that is currently consolidating wealth at an unprecedented rate. Responses ranged from calls for a “bloody revolution” to references to the recent films Elysium, Wall-E, and Zeitgeist 2: Addendum. One commenter invoked the anarcho-syndicalist political views of linguist Noam Chomsky.

The main theme of the discussion centered around the automation of labor and how that would affect the human workforce and the global economy. Hawking seems to believe that our current trajectory will make such automation a death knell for the working classes, with the bourgeoisie machine owners exerting total economic control over human civilization.

One commenter strongly disagreed with Hawking, referencing recent Journal of Economic Perspective articles and claiming “technology has never, will never, and simply cannot result in structural unemployment”.

The comment thread is a treasure trove of wide-ranging ideas that include:

* The efficacy, or lack thereof, of voting

* A “universal basic income”

* Microeconomics

* Techno-socialism, with “an open source decentralized consensus algorithm for the masses”

* A post-scarcity society run by strong artificial intelligence

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This article (Stephen Hawking Warns About The Greatest Threat to Humanity) is free and open source. You have permission to republish this article under a Creative Commons license with attribution to Jake Anderson and the AntiMedia.org. If you spot a typo, email edits@theantimedia.org.

http://theantimedia.org/stephen-hawking-warns-about-the-greatest-threat-to-humanity/

Categories: Uncategorized

Robots May Shatter …

… the Global Economic Order within a Decade

“The pace of disruptive technological innovation has gone from linear to parabolic”, says Bank of America
            
by Ambrose Evans-Pritchard

The Telegraph (November 05 2015)

Robots will take over 45 percent of all jobs in manufacturing and shave $9 trillion off labour costs within a decade, leaving great swathes of the global society on the historical scrap heap.

In a sweeping 300-page report, Bank of America {1} predicts that robots and other forms of artificial intelligence will transform the world beyond recognition as soon as 2025, shattering old business models in a whirlwind of “creative disruption”, with transformation effects ultimately amounting to $30 trillion or more each year.

“The pace of disruptive technological innovation has gone from linear to parabolic”, it said. Any country that fails to embrace the robot revolution will slip rapidly down the rankings of competiveness, and will be left behind.

South Korea is currently in the lead with 440 industrial robots per 10,000 employees in the manufacturing industry, followed by Japan and Germany. Britain is languishing far behind at 75, one of lowest levels in the developed world, the dark side of the UK’s low-productivity labour policies.

The report said the demand for automation is “skyrocketing” as the world’s population ages – with the number of people over sixty expected to rise from 841 million to more than two billion by the middle of the century – and as the once limitless supply of cheap labour dries up in Asia.

 

The price of an advance robotic welder fell from $182,000 in 2005 to $133,000 last year

 

Manufacturing wages in China have jumped ninefold since 2000, and the country’s workforce is shrinking {2}. China is already the world’s biggest buyer of robots, making up a quarter of the global market.

The costs of robots, “care-bots” for the elderly, “agribots” to plants seeds or pick fruit, commercial drones and artificial intelligence have, on average, dropped by 27 percent over the past ten years, and are expected to fall a further 22 percent by 2005.

The price of an advance robotic welder fell from $182,000 in 2005 to $133,000 last year, and its sophistication is increasing all the time. The standard Baxter collaborative “cobot” that works side by side with people on the factory floor – fixing bolts on a conveyor belt, for example – costs just $22,000.

We are coming close to the crucial “inflexion point” when it is fifteen percent cheaper to use a robot than to employ a human worker.

This threshold has already been crossed in the American, European and Japanese car industries, where it costs $8 an hour to employ a robot for spot welding, compared to $25 for a worker. Hence the eerie post-human feel of the most up-to-date car plants. “We are facing a paradigm shift, which will change the way we live and work”, said the report’s author, Beijia Ma.

The social effect is to squeeze out those at the bottom of the employment ladder, rendering them almost unemployable without re-education. Bank of America describes this as the “displacement of human labour”, estimating that almost half of US jobs could be at risk.

Productivity will soar but wages will not rise at the same pace, if at all. The owners of capital will take an even bigger slice of global income, pushing inequality to yet greater extremes. Labour’s share of the pie peaked at 65 percent in 1975 in the rich countries and has already dropped to 58 percent.

The workforce will split yet further into the “haves” at the top of education scale and the “have-nots” with just high school qualifications, not to mention the 800 million illiterates in the world. It is easy to imagine the explosive political consequences if governments fail to take action to mitigate the effects, yet this may be almost impossible in a borderless, globalised world.

Nor are the middle classes invulnerable. Bank of America said “robo-advisors” using algorithm-based systems will “disrupt” 25 million workers in financial and legal services. The Millennial generation – now eighteen to 34 years old – will be the first to switch en masse to these post-human services. This rising cohort already holds $7 trillion of liquid assets and is likely to inherit another $30 to $40 trillion from Baby Boom parents.

Not everybody accepts this overall hypothesis. Professor Charles Goodhart, from the London School of Economics, wrote a paper recently for Morgan Stanley {3} making the opposite argument, contending that the demographic crunch across the Northern hemisphere will overwhelm the effects of technology and lead to an acute labour shortage.

Under his scenario, workers will take their revenge and claw back the lost share of income as wages rise. The return on capital will fall, and the global deflationary supercyle will end in a bloodbath for the bond markets.

There have always been fears of mass destitution with each sudden shift in technology, whether it was the 18th century wool weavers of Yorkshire and the West Country displaced by cotton, or the machine-breaking Luddites in the 19th century threatened by the power loom, or dozens of other such episodes across the world throughout history.

The losers – or their children, at least – are eventually absorbed back into new industries. Human ingenuity has always prevailed. Larry Summers, the former US Treasury Secretary, warns that history is non-linear and it may be different this time.

The proportion of those in the US aged 25 to 54 and not working has tripled since 1965, suggesting that a chronic effect is already taking hold.

They cannot migrate to textile mills and the manufacturing hubs of the cities, as they did in the 18th and 19th centuries to escape the effects of the agricultural revolution.

There is nowhere to go. Labour-saving devices are sweeping everything, everywhere. A single professor can teach a course to 150,000 students through digital technology.

We may achieve the dream of prosperity without toil as robots take over, but find ourselves living in a jobless dystopia.

Links:

{1} https://www.bankofamerica.com/

{2} http://www.telegraph.co.uk/finance/economics/11964280/It-is-already-too-late-to-scrap-Chinas-one-child-policy.html

{3} http://www.morganstanley.com/ideas/demographic-solution-to-inequality/

http://www.telegraph.co.uk/finance/economics/11978542/Robots-may-shatter-the-global-economic-order-within-a-decade.html

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Robots Coming to Steal Half Your Jobs

RT.com (November 13 2015)


(c) Francois Lenoir / Reuters

Roughly half of the workforce in the UK and the US are likely to eventually lose their jobs to robots, as technological automation trends spread across all industries and service sectors, the Bank of England’s chief economist has warned.

Unveiling the Bank’s new statistics {1}, based on the historic trends in the market economy, Andy Haldane warned the Trades Union Congress that half of UK workers might find themselves unemployed in the coming decades.

“Taking the probabilities of automation, and multiplying them by the numbers employed, gives a broad brush estimate of the number of jobs potentially automatable”, Haldane said, stressing that fifteen million people might be affected on the island nation that currently has a workforce of 31.21 million.

The same trend, the chief economist warned will also be witnessed in the US, where the current labor force of roughly 160 million Americans will see half of its jobs go to automation.

“For the UK, that would suggest up to fifteen million jobs could be at risk of automation. In the US, the corresponding figure would be eighty million jobs”, Haldane said.

At the same time, the economist noted that previous predictions concerning the impact of modernization on the workforce had been proven wrong since the beginning of the industrial revolution. However, citing fears over the growth of “artificial intelligence”, Haldane said that if the Bank’s predictions are correct, the labor market patterns of the past three centuries would “shift to warp speed”.

“Machines are already undertaking tasks which were unthinkable – if not unimaginable – a decade ago”, said Haldane. “The driverless car was science fiction no more than a decade ago. Today it is scientific fact.”

The future accountants face a “vocational extinction” of 95 percent, while hairdressers’ positions will be cut by a third. Economists will lose up to fifteen percent market share to robots. Overall the Bank of England forecasts that around seventy percent of jobs in sales and customer service jobs will be cut because of robots. Skilled trades people are also at risk.

“For the UK, roughly a third of jobs by employment fall into each category, with those occupations most at risk including administrative, clerical and production tasks”, Haldane warned.

The effect of robotization will have a “massive” impact on industry and society, the chief economist warned, where people’s social skills will play more of value in the workforce.

“In a world in which machines came to dominate tasks involving core cognitive processing, the importance of, and skill premium attached to, non-cognitive skills is likely to rise. The high skill – high pay jobs of the future may involve skills better measured by EQs than IQs, by jobs creating social as much as financial value”, Haldane concluded.

Link {1}: http://www.ons.gov.uk/ons/rel/lms/labour-market-statistics/november-2015/statistical-bulletin.html

https://www.rt.com/uk/321771-robots-automation-jobs-unemployment/

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Capitalism, Not China …

… Is to Blame for the Current Global Economic Decline

by Richard D Wolff

Truthout | Op-Ed (December 22 2015)

Capitalism, like a speeding train, barreled into a stone wall in 2008. Shocked and dazed, its leaders have been trying to “recover”. By that, they mean to fix the mangled tracks, reposition the locomotive and cars on those tracks and resume forward motion. No basic economic change, in their view, is needed or even considered. They see no absurdity in such a “recovery plan” – just as they saw no approaching catastrophe in the years leading up to 2008.

It was Marx who clearly explained in Capital (1867) the contradiction capitalism’s leaders rarely grasp. Showing how capitalists compete (and survive in competition) by maximizing profits, he focused his readers on capitalists’ strategies of “economizing” on the number of workers they hire (often by substituting machines) and/or replacing more costly workers with cheaper employees. The contradiction emerges when their economizing undermines the market for what capitalists must sell to survive. Boosting their profits by saving on labor often reduces laborers’ total purchasing power, what they can afford to buy from capitalists. That hurts capitalists’ sales and profits. Likewise, when workers’ wages and salaries rise, the resulting benefits to capitalists’ sales can be partially or totally reversed as higher wages cut into profits. The history of capitalism often wobbles between the poles of this contradiction.

Starting in the 1970s, capitalism intensified its economizing on labor. This became possible because huge new supplies of labor power entered the orbits of the established old centers of capitalism (Western Europe, North America and Japan). Most of those new, additional workers had previously been excluded from the labor forces available to those old centers. They had been kept away inside capitalism’s formal and informal colonies in Asia, Latin America and Africa or else inside state capitalisms (Soviet Russia, Eastern Europe and China). After the 1970s, such workers were brought into direct capitalist employment either by migrating to Western Europe, North America and Japan or by the movement of capitalist enterprises from old to new centers (China, India, Brazil, et cetera).

Integrating those newly available workers into globalizing capitalism raised the total supply of labor power far above capitalists’ demand for it. That supply-demand imbalance sharply lowered their wage bills and boosted their profits. Capitalists’ lower outlays for workers’ wages might have quickly depressed the purchasing power of the total working class, undermined the market demand for capitalists’ output and thereby depressed profits: another case study of capitalist contradiction. However, the 1970s saw a quite unique development that postponed the depression of working-class demand. A massive expansion of consumer credit (mortgage debt, car loans, credit cards, et cetera) in the old capitalist centers took off. After the 1970s, workers offset stagnant or falling real wages there by borrowing.

Capitalists enjoyed ever higher profits after the 1970s since labor productivity kept rising (what workers provided to employers) while wages (what employers provide to workers) did not. The rising profits deposited into the banks flowed out, in good part, to become rising consumer loans. The consumer credit explosion since the 1970s postponed the classic capitalist contradiction. It propped up consumer demand that might otherwise have tanked when a sharply expanded, globalized labor force enabled capitalists to economize on their wage bill.

But then in 2008, 25 years of rising consumer debt based on stagnant real wages reached its predictable limits. As workers’ incomes proved insufficient to service bloated debt obligations, their defaults – together with those of financial firms that had speculated in consumers’ debts – contributed to the 2008 crash. They also contribute to the subsequent “recovery” that has bypassed most Americans.

Capitalism’s recovery now proceeds like another speeding train headed toward contradiction and catastrophe. Capitalists continue to profit from stagnant wages (enabled by the continued excess supplies of labor power relative to demand) coupled with rising labor productivity. Yet they also confront weak and weakening market demands that cannot absorb what capitalist production capacities require for profitability. Mainstream ideology drives the refusal to see capitalism and its contradictions as central to today’s economic dilemmas. The major “recovery” strategies reproduce the same capitalism with its contradiction.

China too is both victor and victim in capitalism’s contradiction and its temporary postponement from the 1970s to 2008. On the one hand, the stagnation of wages coupled with the expansion of consumer (and government) credit in North America, Western Europe and Japan provided soaring demands there for relatively cheap consumer goods exports from China. Having bet its industrialization strategy on those export markets, China achieved economic superpower status by selling into capitalism’s contradiction and its postponement via credit. Likewise merchants such as Walmart achieved parallel status by being the retail outlets for Chinese products. Financial enterprises in capitalism’s old centers perhaps benefited the most as they developed extremely profitable ways to securitize the consumer debt, sell it and insure it (credit default swaps, et cetera). Financial enterprises benefited doubly as they also managed (via hedge funds, et cetera) the extreme wealth redistributed and concentrated upward by stagnant real wages and the postponement of capitalism’s contradiction via credit.

But now China is becoming a victim of the classic capitalist contradiction. China’s exports flag because consumer demand in capitalism’s old centers is falling. Wage stagnation in those centers can no longer be offset by credit expansion. Nor can it be offset by rising demand among what are still the far lower-waged workers in capitalism’s new centers (China’s included). In simplest terms, capitalism’s post-1970s global development substituted lower- for higher-waged workers while it redistributed almost all the wealth created since the 1970s to a top one to three percent of the world’s wealthy.

The eventual effect of capitalism’s contradiction (notwithstanding its temporary postponement via credit) was predictable. Chinese production would slow down and thus cut its demands for raw materials, energy and many other basic production inputs. Falling sales of those inputs are now decimating the many national and regional economies that became dependent upon selling those inputs to the Chinese and other new capitalist centers. Thus global economic decline persists – notwithstanding the endlessly hyped “recoveries”.

The cause of global economic decline is not China (or any other particular part of a more-globalized-than-ever world economy), but rather the capitalist contradiction that could no longer be postponed by credit extension. That so many contemporary economic pundits and others blame China reflects a combination of very superficial economics and old-fashioned China bashing.

Copyright, Truthout. May not be reprinted without permission.

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Richard D Wolff is Professor of Economics Emeritus, University of Massachusetts, Amherst where he taught economics from 1973 to 2008. He is currently a Visiting Professor in the Graduate Program in International Affairs of the New School University, New York City. He also teaches classes regularly at the Brecht Forum in Manhattan. Earlier he taught economics at Yale University (1967~1969) and at the City College of the City University of New York (1969~1973). In 1994, he was a Visiting Professor of Economics at the University of Paris (France), I (Sorbonne). His work is available at rdwolff.com and at democracyatwork.info.

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http://billmoyers.com/2014/07/15/capitalism%E2%80%99s-deeper-problem/

http://www.truth-out.org/news/item/30678-critics-of-capitalism-must-include-its-definition

http://www.truth-out.org/news/item/31567-socialism-means-abolishing-the-distinction-between-bosses-and-employees

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http://www.truth-out.org/opinion/item/34095-capitalism-not-china-is-to-blame-for-the-current-global-economic-decline

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