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Two of the current leading researchers in labor economics studying the impact of machines and automation on jobs have released a new National Bureau of Economic Research (NBER) working paper, The Race Between Machine and Man: Implications of Technology for Growth, Factor Shares and Employment.
The authors, Daron Acemoglu and Pascual Restrepo are far from the robot-supporting equivalent of Statler and Waldorf, the Muppets who heckle from the balcony, unless you consider their heckling is about how so many have overstated the argument of robots taking all the jobs without factual support:
Similar claims have been made, but have not always come true, about previous waves of new technologies… Contrary to the increasingly widespread concerns, our model raises the possibility that rapid automation need not signal the demise of labor, but might simply be a prelude to a phase of new technologies favoring labor.
In The Race Between Machine and Man, the researchers set out to build a conceptual framework, which shows which tasks previously performed, by labor are automated, while at the same time more ‘complex versions of existing tasks’ and new jobs or positions in which labor has a comparative advantage are created.
The authors make several key observations that show as ‘low skilled workers’ are automated out of jobs, the creation of new complex tasks always increases wages, employment and the overall share of labor increases. As jobs are eroded, new jobs, or positions are created which require higher skills in the short term:
Whilst “automation always reduces the share of labor in national income and employment, and may even reduce wages. Conversely, the creation of new complex tasks always increases wages, employment and the share of labor.”
They show, through their analysis, that for each decade since 1980, employment growth has been faster in occupations with greater skill requirements
During the last 30 years, new tasks and new job titles account for a large fraction of U.S. employment growth.
In 2000, about 70% of the workers employed as computer software developers (an occupation employing one million people in the US at the time) held new job titles. Similarly, in 1990 a radiology technician and in 1980 a management analyst were new job titles.
Looking at the potential mismatch between new technologies and the skills needed the authors crucially show that these new highly skilled jobs reflect a significant number of the total employment growth over the period measured as shown in Figure 1:
From 1980 to 2007, total employment in the U.S. grew by 17.5%. About half (8.84%) of this growth is explained by the additional employment growth in occupations with new job titles.
Unfortunately we have known for some time that labor markets are “Pareto efficient; ” that is, no one could be made better off without making anyone worse off. Thus Acemoglu and Restrepo point to research that shows when wages are high for low-skill workers this encourage automation. This automation then leads to promotion or new jobs and higher wages for those with ‘high skills.’
Because new tasks are more complex, the creation may favor high-skill workers. The natural assumption that high-skill workers have a comparative advantage in new complex tasks receives support from the data.
The data shows that those classified as high skilled tend to have more years of schooling.
For instance, the left panel of Figure 7 shows that in each decade since 1980, occupations with more new job titles had higher skill requirements in terms of the average years of schooling among employees at the start of each decade (relative to the rest of the economy).
However it is not all bad news for low skilled workers the right panel of the same figure also shows a pattern of “mean reversion” whereby average years of schooling in these occupations decline in each subsequent decade, most likely, reflecting the fact that new job titles became more open to lower-skilled workers over time.
Our estimates indicate that, although occupations with more new job titles tend to hire more skilled workers initially, this pattern slowly reverts over time. Figure 7 shows that, at the time of their introduction, occupations with 10 percentage points more new job titles hire workers with 0.35 more years of schooling). But our estimates in Column 6 of Table B2 show that this initial difference in the skill requirements of workers slowly vanishes over time. 30 years after their introduction, occupations with 10 percentage points more new job titles hire workers with 0.0411 fewer years of education than the workers hired initially.
Essentially low-skill workers gain relative to capital in the medium run from the creation of new tasks.
Overall the study shows what many have said before, there is a skills gap when new technologies are introduced and those with the wherewithal to invest in learning new skills, either through extra education, on the job training, or self-learning are the ones who will be in high demand as new technologies are implemented.
In 1812 the British government created an Act of Parliament which made the destruction of mechanized looms – or knitting machines – a capital felony and hence a crime punishable by death. The Act was implemented as a result of so called Luddite attacks on machines.
It should be noted that in many cases the so called Luddites were not raging against the machines taking jobs, but against the employers who failed to provide them with a ‘living wage.’
According to the esteemed historian Eric Hobsbawm, the Luddites had: “no special hostility to machines as such,” their actions were in fact, “a normal means of putting pressure on employers.” Hobsbawm wrote: “Such misconceptions are, I think, due to the persistence of views about the introduction of machinery elaborated in the early nineteenth century.” Adding:
This sort of wrecking was a traditional and established part of industrial conflict in the period of the domestic and manufacturing system, and the early stages of factory and mine. It was directed not only against machines, but also against raw material, finished goods and even the private property of employers, depending on what sort of damage these were most sensitive to. Thus in three months of agitation in 1802 the Wiltshire shearmen burned hay-ricks, barns and kennels of unpopular clothiers, cut down their trees and destroyed loads of cloth, as well as attacking and destroying their mills.
Essentially Luddites were the early trade unions and not raging specifically against the machines but seeking a ‘fair wage’ for the employees by rioting and causing damage to business owners’ property by any means to press their case.
The misconceptions of the actions of the Luddites led to poor legislation and policy in the United Kingdom.
Job security requires skills only Merlin possesses
In 2013, researchers Carl Frey and Michael Osborne of the Oxford Martin School announced that 47 percent of U S jobs were at risk of computerization:
According to our estimates around 47 percent of total US employment is in the high risk category. We refer to these as jobs at risk – i.e. jobs we expect could be automated relatively soon, perhaps over the next decade or two.
In 2014 Deloitte asked them to carry out similar research in the UK, where it was stated Frey and Osborne: “estimate that on average, 35 per cent of current jobs in the UK are at high risk over the next ten to twenty years.”
Frey and Osborne’s papers have led to a deluge of bleak headlines, such as Death of the Accountant and Auditor; Advances in artificial intelligence could lead to mass unemployment, warn experts; and whilst we are on this theme maybe the most embellished article and headline of all: Technology f*cked us all: The anxiety driving Donald Trump and Bernie Sanders is really about machines taking our jobs. The pessimistic view associated with Frey and Osborne’s paper has even led to claims that we may be headed for another Engels’ Pause: a period of stagnant living standards and higher unemployment in the face of rapid technological change.
I am worried by the seemingly incurable pessimism caused by these headlines, which are also instigating governments to champion or consider policies that may not be in the long term best interests of the population they serve.
The headlines scream that if you want to make your job ‘non-susceptible’ to automation then you should make sure it has the type of skills that only Merlin possesses
It is important to realize that the methodology in the Frey and Osborne papers have never been validated with any actual evidence. Anyone with five minutes to spare, a Maths GCSE, and a modicum of common sense could pick flaws in the selection of types of jobs shown to be at high risk of being taken over by a computer algorithm.
Nevertheless, people, including policy makers, suspend their critical judgment and believe the headlines that robots are set to become a Hobbesian nightmare of breathtaking scope.
But if we look beyond the headlines and read the Frey and Osborne paper we find the authors are not stating ‘robots’ WILL take half of all jobs but computerization ‘could’ displace people from the types of jobs they have highlighted. In fact one of the authors, Carl Benedikt Frey, recently wrote in March 2016:
Although we cannot exclude the possibility that technology may reduce the overall demand for jobs in the future, this is seemingly not an immediate concern.
Meanwhile his co-author Michael Osborne has gone as far as saying:
I think a lot of the risk to professions has been overhyped.
Frey and Osborne do a good job surveying a certain type of literature on the suggested improvements being made within robotic, machine learning, artificial intelligence, etc. Although this research tends to rely too much on sources such as the International Federation of Robotics, an industry association with, in my opinion little impartiality and other publicity afforded to various robots and A.I. providers. They provide very little actual citation of work happening within the labs of developers, nor do they analyze the capabilities of current robots in any great degree through discussions with users of these robots, rather referring to the reported capabilities (or expected capabilities) of Baxter the co-bot by Rethink Robotics with a nominal number in service. They also use research that estimates that “the market for personal and household service robots is already growing by about 20 percent annually.” Which is more or less Roomba the automated vacuum cleaner, that to the best of my knowledge has not displaced any Ukrainian housecleaners in Poland!
Evidence of any actual job displacement by the current types of robotics and computerization illustrated by the authors is not shown. What the authors are doing is predicting a demise of jobs based on their research of the available literature! In fact the authors state in the paper:
We speculate about technology that is in only the early stages of development.
Nevertheless, despite the ‘speculation,’ they do make the bold claim:
In the first wave, we find that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are likely to be substituted by computer automation.
So unlikely, so unimaginable
Which jobs are not at risk of automation according to Frey & Osborne?
Occupations that involve complex perception and manipulation tasks, creative intelligence tasks, and social intelligence tasks are unlikely to be substituted by computer capital over the next decade or two.
These are what the authors terms non-susceptible task characteristics.
A sub element of manipulation is manual dexterity. An indication of the level of “Manual Dexterity” computer-controlled equipment would require to perform a specific occupation. Low (level) manual dexterity corresponds to “Screw a light bulb into a light socket”; medium (level) is exemplified by “Pack oranges in crates as quickly as possible”; high (level) is described as “Perform open-heart surgery with surgical instruments”.
It is thus obvious in Frey and Osborne’s thesis that jobs at risk of automation can be summed up as follows:
The probability of an occupation being automated can thus be described as a function of these task characteristics. As suggested by Figure I, the low degree of social intelligence required by a dishwasher makes this occupation more susceptible to computerisation than a public relation specialist, for example. We proceed to examining the susceptibility of jobs to computerisation as a function of the above described non-susceptible task characteristics.
Arriving at 47% of jobs being highly susceptible to automation
The authors relied on O∗NET, an online service developed for the US Department of Labor. O∗NET defines the key features of an occupation as a standardised and measurable set of variables. It also provides open-ended descriptions of specific tasks to each occupation.
They then asked a specific question:
Can the tasks of this job be sufficiently specified, conditional on the availability of big data, to be performed by state of the art computer-controlled equipment?
The authors further identified nine variables that describe the attributes of perception and manipulation, creativity, and social intelligence and which are required to perform the attributes. These are shown in Table 1 from the authors’ paper. They then focused on O∗NET’s description of Tasks.
It should be Work Activity and Skills not Tasks
Time and time again as I look at the types of jobs Frey and Osborne say are at high and medium risk of being done by automation I can’t help but question – is it because they specifically looked at O∗NET data with respect to Tasks and not the essential element that portrays Work Activity and Skills?
Table 1 from Frey and Osborne.
Frey and Osborne indicate that their algorithm predicts that most workers in transportation and logistics occupations, together with the bulk of office and administrative support workers, and labour in production occupations, are at risk of automation within ten to twenty years,
Much of their argument about transportation employees circulates around the advent of driverless cars. We are much closer to an understanding of when driverless cars will be available to the ‘general public’ and it certainly seems that they will not be the main mode of transport in the next 3 decades if current developments and legislation is anything to go by. I do believe that we will see more semi-autonomous trucks on the roads in the coming decade, but I do not see that they will be without a human in the cab for sometime in the future. There are just too many infrastructure problems to overcome, let alone the technical obstacles.
Sports referees, Watch Repairers, Models and Manicurists jobs to be automated
Drill into the report and look at the types of jobs that they say have the highest probability of being replaced by automation and we find all sorts of jobs even the most pessimistic luddite will find hard to accept.
One job at the highest risk of automation, using Frey and Osborne’s methodology is that of Watch Repairer. According to O∗NET statistics there are 3,000 watch repairers in the United States. Now I may accept jobs of watch repairers will dwindle as sales of watches falls due to the fact nearly everybody looks at their smart phone for the time, but not that watches will be repaired by robots! If sales of watches are dwindling why invest the time and money building a robot to repair watches? In fact I suspect that Watch Repairers will become even more of a specialized job as sales of watches focus on the high value watch. I do not expect Watch Repairers will be replaced because an automated machine can repair the watch.
Another job that the authors state is at high risk of automation is Manicurists and Pedicurists – surely that requires a high level of dexterity, precision and social skill?
They also predict the days of Animal Breeders are over (is that because we will all have pet robots?), Gaming Dealers – not social at all!, Real Estate Brokers – presumably robots will arrange to show us around prospective houses. Maybe many people’s favorite choice but not likely any time soon – Umpires, Referees, and Other Sports Officials – will be automated.
Perhaps the one I most flinch at which Frey and Osborne’s algorithm predicts is at high risk of automation is Models.
Look at the tasks O∗NET provides as key for Models.
- Pose for artists and photographers.
- Gather information from agents concerning the pay, dates, times, provisions, and lengths of jobs.
- Follow strict routines of diet, sleep, and exercise to maintain appearance.
- Record rates of pay and durations of jobs on vouchers.
- Report job completions to agencies and obtain information about future appointments.
Now look at the Work Activity O∗NET provides.
- Establishing and Maintaining Interpersonal Relationships — Developing constructive and cooperative working relationships with others, and maintaining them over time.
- Performing General Physical Activities — Performing physical activities that require considerable use of your arms and legs and moving your whole body, such as climbing, lifting, balancing, walking, stooping, and handling of materials.
- Thinking Creatively — Developing, designing, or creating new applications, ideas, relationships, systems, or products, including artistic contributions.
Social Perceptiveness — Being aware of others’ reactions and understanding why they react as they do.
Surely these Work Activities and Skills are elements that fit into Frey and Osborne’s criteria for jobs that will not be automated. I have repeated detailed analysis of over 90 of the occupations that Frey and Osborne indicate are at high and medium risk of automation and each time I question the judgment of the authors.
Policy makers are well advised to do their own analysis before using the Frey and Osborne paper to pursue policies that may not be in the best interest of their constituents.
One final word from the Frey and Osborne which is often overlooked in the hype associated with the paper:
We acknowledge that it is by no means certain that a job is computerisable given our labelling.
 The Destruction of Stocking Frames, etc. Act 1812 (https://en.wikipedia.org/wiki/Destruction_of_Stocking_Frames,_etc._Act_1812)
 Eric Hobsbawm, Machine Breakers (http://libcom.org/history/machine-breakers-eric-hobsbawm)
 Deloitte London Futures: Agiletown: the relentless march of technology and London’s response (http://www2.deloitte.com/uk/en/pages/growth/articles/agiletown-the-relentless-march-of-technology-and-londons-response.html Last accessed 11th April 2016)
 Engel`s Pause: A Pessimist`s Guide to the British Industrial Revolution. Robert C. Allen, April 2007 (http://www.economics.ox.ac.uk/materials/working_papers/paper315.pdf Last accessed 18th April 2016)
 Technology at work: How the digital revolution is reshaping the global workforce. Carl Benedikt Frey, Ebrahim Rahbari 25 March 2016 (http://www.voxeu.org/article/how-digital-revolution-reshaping-global-workforce Last accessed 11th April 2016)
 Robots are leaving the factory floor and heading for your desk – and your job, The Guardian Zoe Corbyn 9th February 2015 (https://www.theguardian.com/technology/2015/feb/09/robots-manual-jobs-now-people-skills-take-over-your-job Last accessed 11th April 2016)
Main paper cited – The Future of Employment: How susceptible are jobs to computerisation? Carl Benedikt Frey and Michael A. Osborne. September 17, 2013 (http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf)
Bank of England’s Andy Haldane warns Smart machines could take 15 million UK jobs and 80 million in the US
In an important new paper based on a speech at the trade union congress in London, Andy Haldane Chief Economist at the Bank of England and Executive Director of Monetary Analysis and Statistics has examined the history of technological unemployment in which he gave a thorough review of the literature and implications for public policy. The media will likely focus on the number of jobs that can be displaced (as I did in the title) and not necessarily Haldane’s points on new jobs being created – both of which are highly important as is ‘skilling-up’.
Andy notes that arguments about “technological unemployment” – the idea that technological advance puts people out of work and bears down on wages – have been raging for centuries. According to Andy, most evidence shows that over the broad sweep of history technological progress has not damaged jobs but rather boosted wages: “Technology has enriched labour, not immiserated it.”
However, he also notes that this broad pattern obscures the fact that there has an increasing skills premium has emerged with each passing wave of technological progress. This was especially the case in the late 20th century, as new machines such as computers began replacing not only physical but cognitive labour. He finds that each phase has eventually resulted in a “growing tree of rising skills, wages and productivity”. But they have also been associated with a “hollowing out of this tree”. Indeed, this hollowing-out of jobs has “widened and deepened with each new technological wave”. This has resulted in a widening income gap between high- and low- skilled workers.
Andy states: “By itself, a widening distribution of incomes need not imply any change in labour’s share of national income: in the past, technology’s impact on the labour share appears to have been broadly neutral. But this time could be different.”
Skipping the history parts I’ve highlighted some key points of robot and automation that will displace jobs and I agree with:
Viewed over the sweep of history, then, there is essentially no evidence to suggest technology has damaged jobs and plenty to suggest it has boosted wages. Technology has enriched labour, not immiserated it. Mill was right; Ricardo was wrong. Labour is not dead wood to be carved up between tasks. It is a tree whose trunk and branches have lengthened and thickened with time. The “lump of labour” fallacy is just that.
Or is it?
Looking more closely at past phases of rapid technological change paints a more nuanced picture. Each phase has eventually resulted in a growing tree of rising skills, wages and productivity. But they have also been associated with a “hollowing out” of this tree. Indeed, this hollowing-out has widened and deepened with each new technological wave.
Further going on to indicate:
Based on past patterns, it is argued that information technology may be poised for exponential growth, as its full fruits are harvested. Indeed, we may be on the cusp of a fourth Industrial Revolution or Second Machine Age (Brynjolfsson and McAfee (2014), Ford (2015)).
Its defining feature would be that new-age machines will be thinking as well as doing, sensing as well as sifting, adapting as well as enacting. They will thus span a much wider part of the skill distribution than ever previously. As robots extend their skill-reach, “hollowing-out” may thus be set to become ever-faster, ever-wider and ever-deeper. Or that, at least, is the picture some have painted.
How much wider and deeper? Research by Carl Benedikt Frey and Michael Osborne has tried to quantify this hollowing-out, by assigning probabilities to certain classes of job being automated over the course of the next few decades. Their work was initially done for the US, but has recently been extended to the UK (Frey and Osbourne (2013), Deloitte (2015b)).
Using this methodology, the Bank has recently done its own exercise for the UK and US. Table 3 classifies jobs three ways in the US and UK – high (greater than 66%), medium (33-66%) and low (less than 33%) probability of automation. It also shows the fraction of employment these jobs represent. Chart 27 provides a more granular breakdown of these jobs.
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. Taking the probabilities of automation, and multiplying them by the numbers employed, gives a broad brush estimate of the number of jobs potentially automatable. For the UK, that would suggest up to 15 million jobs could be at risk of automation. In the US, the corresponding figure would be 80 million jobs.
Will we have robot hairdressers and elder care robots?
No-one anytime soon is I think going to choose a robot to cut their hair – I told you the hairdressers were safe. Nor are they likely to choose a robot to look after their young children or elderly parents (tempting as that can sometimes sound). When it comes to forecasting the economy, I can quite believe a thinking machine might over time displace me. But it is less likely an “Andy Robot” will be giving this lecture to the TUC even a decade from now.
However he does clarify his vision:
Even if this diagnosis is right, it nonetheless may suggest a fundamental reorientation in the nature of work could be underway. We may already be seeing early signs of that in the move towards more flexible working, with an increased incidence of part-time working, temporary contracts and, in particular, self-employment. Some have speculated that these seismic shifts could result in the emergence of a “new artisan” class : micro-businesses offering individually-tailored products and services, personalised to the needs of customers, from healthcare and social care, to leisure products and luxuries. This really will be Back to the Future.
Yet the smarter machines become, the greater the likelihood that the space remaining for uniquely-human skills could shrink further. Machines are already undertaking tasks which were unthinkable – if not unimaginable – a decade ago. The driverless car was science fiction no more than a decade ago. Today, it is scientific fact. Algorithms are rapidly learning not just to process and problem-solve, but to perceive and even emote (Pratt (2015)).
As digital replaced analogue, perhaps artificial intelligence will one day surpass the brain’s cognitive capacity, a tipping point referred to as the “singularity” (Stanislaw (1958))). Brad Delong has speculated that, just as “peak horse” was reached in the early part of the 20th century, perhaps “peak human” could be reached during this century (Delong (2014)).
In an experiment, MIT researchers used their AR system to place obstacles — like human pedestrians — in the path of robots, which had to navigate through a virtual city. The robots had to detect the obstacles and then compute the optimal route to avoid running into them. As the robots did that, a projection system displayed their “thoughts” on the ground, so researchers could visualize them in real time.
While we have always heard of a future in which robots would be handling most of the labor, it’s hard to think that most people pictured it in the way that things seem to be heading. Sure, automated work forces will be handling many of the world’s tasks in a relatively short amount of time, ushering in a new era of prosperity and leisure for the masses. The problem is that that prosperity hasn’t been shared, and many of the world’s poor and middle classes will end up scrambling to make ends meet as a result.
RoboLaw: Why and how to regulate robotics
Even a robot that can perform complex tasks without human supervision and take decisions towards that end may still not be deemed an agent in a philosophical sense, let alone a legal one. The robot is still an object, a product, a device, not bearing rights but meant to be used. What would justify a shift on a purely ontological basis (thus forcing us to consider the robot as a being provided with rights and duties) is what Gutman, Rathgeber and Syed call ‘strong autonomy’ – namely the ability to decide for one’s self and set one’s own goals. However, at present this belongs to the realm of science fiction, and it can be argued that this is not the direction we desire to take with robots in any case.
Elon Musk wades in — again: Talking at MIT’s Aeronautics and Astronautics Department’s Centennial Symposium last week, Musk said, “With artificial intelligence, we are summoning the demon. You know all those stories where there’s the guy with the pentagram and the holy water and he’s like… yeah, he’s sure he can control the demon—it doesn’t work out.” Mike Loukides counters that:
David Ferrucci and the other IBMers who built Watson understand that Watson’s potential in medical diagnosis isn’t to have the last word, or to replace a human doctor. It’s to be part of the conversation, offering diagnostic possibilities that the doctor hasn’t considered, and the reasons one might accept (or reject) those diagnoses. That’s a healthy and potentially important step forward in medical treatment, but do the doctors using an automated service to help make diagnoses understand that? Does our profit-crazed health system understand that? When will your health insurance policy say “you can only consult a doctor after the AI has failed”? Or “Doctors are a thing of the past, and if the AI is wrong 10% of the time, that’s acceptable; after all, your doctor wasn’t right all the time, anyway”? The problem isn’t the tool; it’s the application of the tool.
The prospect of a jobless economy certainly seems daunting. But if we can successfully manage it and put our machines to work, we could enter into an unprecedented era of material abundance while dramatically extending our leisure time. Rather than be tied to menial and demeaning work, we’d be free to engage in activities that truly interest us.
Most people work below their capabilities, leading lives of mediocrity and getting by in an ‘average capacity.’ We make promises and commitments to ourselves and to our employers, investors or partners, which we often fail to deliver.
We think we are escaping the rat-race of office cubicles by setting up our own small family business, but we continue to trudge through our day using a fraction of our talents and capabilities. We get sidetracked reading gossip papers and magazines, sports sites, friends Facebook posts and a myriad of other distracting, attention grabbing time sucks. And yet we still claim we did a hard day’s work! When in fact the days just keep going on and on—like the movie Groundhog Day.
But the problem is, so often only 10% of people are high achievers – nothing, and I mean nothing, is stopping you from being a high achiever, except your own laziness.
This averageness is leaving a trail of misery and debt for our-selves, our loved ones and our children and future generations.
We live in a time, where it seems to me, entitlement prevails. Far too many people believe they are entitled to a high standard of living, they believe they work hard because they show up at the factory, office, institution or small business they own and yet they squander most of the day.
What happened to REAL hard work and ingenuity?
Is it any wonder the newspapers and TV stations, on a daily basis, are announcing that Robots will take your job?
Now of course this does not apply to every profession, I know some high school teachers that work harder than many finance executives and board directors I work with at close quarters. I work with PhD students that work harder than some of the tenured professors and I know many young engineers and behavioral science graduates that are creatively developing Apps and solutions to solve real world problems.
Unless we move from an ‘average,‘ to an ‘augmented’ personal economy, we will suffer and stagnate and lose everything we have worked for including our self-esteem.
Make no mistake about it, robotic and automated technology is changing the way we work, and it WILL displace those that work in an average and mediocre way. No job is safe… there are already robot burger flippers, waitresses are being displaced by automatic ordering services in restaurants, driverless trucks are replacing fork lift drivers, and factory workers, the robot barman is far more efficient and ‘friendlier’ than many bar staff, driverless cars will replace taxi drivers, and even psychiatrists could be displaced, automation has displaced millions of office jobs and will continue to do so. The list is endless and much of it has been happening for years, and suddenly the advances of technology have brought it closer to where it could impact your job no matter what you do.
As head of the AI at Singularity University, Neil Jacobstein, told the BBC. “It isn’t artificial intelligence that keeps me awake at night, it is human stupidity.”
There is absolutely no excuse for mediocrity – but if you choose to live in an average way, don’t say I didn’t warn you…
50 years ago, author Isaac Asimov prophesized about the future: “What will the World’s Fair of 2014 be like?” he wrote in the New York Times. “I don’t know, but I can guess.”
His essay forecast everything from self-driving cars:
“Much effort will be put into the designing of vehicles with ‘Robot-brains’”
To Keurig machines:
“Kitchen units will be devised that will prepare ‘automeals,’ heating water and converting it to coffee.”
To photochromic lenses:
“The degree of opacity of the glass may even be made to alter automatically in accordance with the intensity of the light falling upon it.”
But Asimov’s most impressive prophecy had less to do with gadgets than perceiving what that progress would mean for society.
”The world of A.D. 2014 will have few routine jobs that cannot be done better by some machine than by any human being,” he wrote. Later, he added, ”The lucky few who can be involved in creative work of any sort will be the true elite of mankind, for they alone will do more than serve a machine.”
A proliferation of new books, scientific studies, newspaper and journal articles are informing us that it was advances in technology and automation that have contributed to the extended period of unemployment that continues in the Great Recession. They tell us that robots will take our jobs, with headlines such as: “How Technology is Destroying Jobs[i]” “Will Robots Steal Your Job? You’re highly educated. You make a lot of money. You should still be afraid[ii].” We read that: “Factories have replaced millions of workers with machines.[iii]”
Automation and other productivity improvements are expected to have eliminated 2.2 million business-services jobs in the United States and Europe from 2006 to 2016, at a rate of about 200,000 jobs annually, according to the Hackett Group, a Miami-based consultancy.
The Economist magazine calls this the “Third Industrial Revolution[iv].” I call it the Robot Economy, one that millions can and should benefit from and thereby avoid being displaced with what the brilliant Joseph Schumpeter termed ‘the inevitable creative destruction‘ that will lead us out of the great recession.
Over the last 20 years there has been incredible advances in automation. Windows 3.1 was released between 1992 and 1994, the first viable desktop publishing program which catapulted more and more individuals and businesses to begin using computers. In 1993 the Internet was in its infancy, used mainly by some government department and universities – it is only in the last 10 years that internet communication has taken off and streamlined many business processes; just look at banking and airline/travel reservations. It is as recent as 2009 that we began to see the widespread use of smartphones. Manufacturers assembly lines have largely replaced people with machines.
In short technology has advanced at a vast pace and the advantages technology has brought to automating processes and improving daily tasks within homes and businesses has had a significant impact on reshaping the workplace – eliminating many jobs, whilst creating new ones.
It’s not just that the old economy, built on factory work and mid-level office jobs, has stagnated. It’s that the nature of work itself is changing, largely because of the increasing power of intelligent machines and new evolutionary companies, such as Google, Tesla and Amazon and bell-weather IBM with their Watson artificial intelligence platform.
We may all immediately think of machines and automation as common features in factories, but also consider the insurance sector, in the UK alone some 75% of car insurance is now purchased online, just one example of a multi billion dollar industry that has considerably automated its sales reach and in so doing eliminated the job of the door-to-door friendly neighborhood insurance salesman.
Smart software is transforming almost everything about work, and ushering in an era of a new meritocracy. It makes workers redundant, by doing their work for them. It makes work more unforgiving, by tracking our mistakes. And it creates an entirely new class of workers: people who know how to manage and interpret computer systems, and whose work, instead of competing with the software, augments and extends it. Over the next several decades wages for that new class of workers will grow rapidly, while the rest will be left behind.
A recent scientific study indicated that people with ‘numeracy’ skills are likely to fair better in the workplace than those with literacy skills. On average people with 1 basis point more in numeracy skills earn 18% more than those with literacy skills. Clearly numeracy skills are essential for people programming the algorithms that are driving the robot economy through software. I’ll write more about this study in the coming weeks as I am not so convinced and creative types with marketing and psychology skills will be much in demand as Professor Tyler Cowen has written in his book Average is Over.
Finally back to Asimov, who also wrote in his essay Whatever you Wish: “It may be that machines will do the work that makes life possible and that human beings will do all the other things that make life pleasant and worthwhile.”
Will we have and want more leisure time? Having meaningful work that stimulates and challenges the mind is something I certainly I hope to continue to do – isn’t that something most of us want?
Hat Tip to Zachary M. Seward at Quartz for the initial NY Times Asimov article.