Current Issues in Economics Labor demand perspectives in the time of robots 1.

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Current Issues in Economics

Labor demand perspectives in the time of robots

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For decades, people have been predicting how the rise of advanced computing and robotic technologies will affect our lives, but expectations differ:– Some look forward to the vast economic opportunities

that robots will present, claiming, for example, that they will improve productivity or take on undesirable jobs.

– Others are warnings that robots will displace humans in the economy, destroying livelihoods, especially for low-skill workers.

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https://www.youtube.com/watch?v=bbdQbyff_Sk

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"We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come – namely, technological unemployment. This means unemployment due to our discovery of means of economizing the use of labor outrunning the pace at which we can find new uses for labor.” Keynes, John Maynard (1930) Economic Possibilities for our Grandchildren

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Is the Luddite fallacy still at work or we are at “the second half of the chessboard?”• Early concern about technological unemployment was

exemplified by the Luddites, textile workers who feared that automated looms would allow more productivity with fewer workers, leading to mass unemployment.

• In a way it happened: highly skilled artisans were replaced by low skills workers

• But while automation did lead to textile workers being laid off, new jobs in other industries developed.

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“The “dark side” of productivity growth because of automation is merely another form of the Luddite fallacy – the idea that new technology destroys jobs. If the Luddite fallacy were true we would all be out of work because productivity has been increasing for two centuries’ “ marginalrevolution.com

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"There are many reasons to think the software revolution will be even more profound than the agricultural revolution. This time around, change will come faster and affect a much larger share of the economy. [...] [T]here are more sectors losing jobs than creating jobs. And the general-purpose aspect of software technology means that even the industries and jobs that it creates are not forever. [...] If current trends continue, it could well be that a generation from now a quarter of middle-aged men will be out of work at any given moment.“ Larry Summers WSJ 2014

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In 2014, Pew Research canvassed 1,896 technology professionals and economists and found a split of opinion: • 48 percent of respondents believed that new

technologies would displace more jobs than they would create by the year 2025,

• 52 percent maintained that they would not.

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Jobless recoveries: what?• The fact that employment is recovering much

slower than GDP is a relatively new phenomenon jobless recoveries have only really occurred after the recessions after 1991

• It is a distinct break from previous postwar episodes of recession when both GDP and employment would vigorously rebound following recessions

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Jobless recoveries: why?• Disappearance of routine occupations. In the mid-1980s,

about one in three Americans was employed in a routine occupation. Currently, that figure stands at one in four.

• Labor market mismatch? Tertiary education means lower unemployment and faster income growth

• Polarization of labor market. All employment growth of the past 30 years has either been in ‘non-routine’ occupations located at the high-end of the wage distribution, such as software engineers and managers, or in low-paying jobs, such as service occupations like restaurant waiters and janitors.

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Robotization 1st step:• Robots and automation have been in many

types of manufacturing for decades. In the US and China fewer people work in manufacturing today than in 1997.

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Robotization 2nd step:• A change with a potentially far larger impact

on employment, is taking place in clerical work and professional services. Countless traditional white-collar jobs, such as many in the post office and in customer service, have disappeared.

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Robotization 3rd step:Technologies like the Web, artificial intelligence, big data, and improved analytics are automating many non-routine tasks.

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Looking into the future:• “It will change every profession in ways we

have barely seen yet,” B. Arthur. Santa Fe Institute

• “Artificial Intelligence could end human race” Stephen Hawking, University of Cambridge

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Giving up to robots (MIT 2014) http://tiny.cc/k4hzgx

• In manufacturing, advanced robotic technology has opened up the possibility of integrating highly autonomous mobile robots into human teams.

• With this capability comes the issue of how to maximize both team efficiency and the desire of human team members to work with robotic counterparts.

• Our results indicate that workers prefer to be part of an efficient team rather than have a role in the scheduling process, if maintaining such a role decreases their efficiency.

• These results provide guidance for the successful introduction of semi-autonomous robots into human teams.

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How and were labor can survive?Six ways that humans have historically created value, through:• our legs and other large muscles move things to where we need

them to be• our fingers, can rearrange them into useful patterns • our mouths, our words, whether spoken or written – enable us to

inform and entertain one another• our brains, regulate routine activities, keeping the leg- and finger-

work on track• our smiles, help us to connect with others• our minds – our curiosity and creativity – identify and resolve

important and interesting challenges.

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• So the question is not whether robots and computers will make human labor in the goods, high-tech services, and information-producing sectors infinitely more productive. They will.

• What really matters is whether the jobs outside of the robot-computer economy – jobs involving people’s mouths, smiles, and minds – remain valuable and in high demand. B. de Long

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Wages in the time of robots: time of incomes increase

• From 1850 to 1970 or so, rapid technological progress first triggered wage increases in line with productivity gains.

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Wages in the time of robots: time of incomes distribution (middle class)• Then came the process of income-distribution

equalization, as machines, installed to substitute for human legs, and fingers created more jobs in machine-minding, which used human brains and mouths, than it destroyed in sectors requiring routine muscle power or dexterity work.

• Rising real incomes increased leisure time, thereby boosting demand for smiles and the products of minds.

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Wages in the time of robots: what next?

• Future employment growth will be concentrated among the jobs that cannot be automated, particularly in services, which have to be delivered physically.

• The US Bureau of Labor Statistics estimates that among the most rapidly growing occupational categories over the next ten years will be “healthcare support occupations” (nursing aides, orderlies, and attendants) and “food preparation and serving workers” – that is, overwhelmingly low-wage jobs.

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Some jobs to be lost : hollowing the center• Back in 2012, Amazon acquired Kiva Systems,

a maker of robots that can be programmed to pick up online orders in a warehouse and shuttle them to their departure points.

• Google autonomous vehicle technology is accelerating, and for now, is focused on passenger vehicles; but the real labor shortage is in long-haul trucking or agriculture

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Inequality in the time of robots• As computer-processing power grows and artificial-intelligence

software advances, machines are increasingly able to perform complex tasks requiring abstract thinking, such as inferring meaning and making judgments, far beyond routine physical and clerical activities.

• As a result, companies are beginning to automate more highly skilled knowledge-based jobs in fields like law and medicine.

• While this process will generate a significant amount of value – more than $5 trillion in 2025, according to MGI estimates – it will not be distributed evenly.

McKinsey Global Institute

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What to do?• Workers must come to terms with the imperative

of life-long learning • Companies must anticipate and adapt to rapid

change.• Governments will need to:– meet new demands for education and training– implement effective mechanisms for regulating, say,

self-driving cars or the use of genomic data to develop personalized drugs

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Growth remedy or growth problem

Job Growth = Output Growth — Productivity Growth

• Technology is destroying jobs faster than economy is creating new ones when output growth is too slow

• Before we can assess the state of technological unemployment, we have to get rid of bad policy-induced unemployment.

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Current Issues in Economics Labor demand perspectives in the time of robots 1.

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