Technological unemployment

Technological unemployment is the loss of jobs caused by technological change. Such change typically includes the introduction of labour-saving “mechanical-muscle” machines or more efficient “mechanical-mind” processes (automation). Just as horses employed as prime movers were gradually made obsolete by the automobile, humans’ jobs have also been affected throughout modern history. Historical examples include artisan weavers reduced to poverty after the introduction of mechanized looms. During World War II, Alan Turing’s Bombe machine compressed and decoded thousands of man-years worth of encrypted data in a matter of hours. A contemporary example of technological unemployment is the displacement of retail cashiers by self-service tills.

That technological change can cause short-term job losses is widely accepted. The view that it can lead to lasting increases in unemployment has long been controversial. Participants in the technological unemployment debates can be broadly divided into optimists and pessimists. Optimists agree that innovation may be disruptive to jobs in the short term, yet hold that various compensation effects ensure there is never a long-term negative impact on jobs, whereas pessimists contend that at least in some circumstances, new technologies can lead to a lasting decline in the total number of workers in employment. The phrase “technological unemployment” was popularised by John Maynard Keynes in the 1930s, who said it was a “only a temporary phase of maladjustment”. Yet the issue of machines displacing human labour has been discussed since at least Aristotle’s time.

Prior to the 18th century both the elite and common people would generally take the pessimistic view on technological unemployment, at least in cases where the issue arose. Due to generally low unemployment in much of pre-modern history, the topic was rarely a prominent concern. In the 18th century fears over the impact of machinery on jobs intensified with the growth of mass unemployment, especially in Great Britain which was then at the forefront of the Industrial Revolution. Yet some economic thinkers began to argue against these fears, claiming that overall innovation would not have negative effects on jobs. These arguments were formalised in the early 19th century by the classical economists. During the second half of the 19th century, it became increasingly apparent that technological progress was benefiting all sections of society, including the working class. Concerns over the negative impact of innovation diminished. The term “Luddite fallacy” was coined to describe the thinking that innovation would have lasting harmful effects on employment.

The view that technology is unlikely to lead to long term unemployment has been repeatedly challenged by a minority of economists. In the early 1800s these included Ricardo himself. There were dozens of economists warning about technological unemployment during brief intensifications of the debate that spiked in the 1930s and 1960s. Especially in Europe, there were further warnings in the closing two decades of the twentieth century, as commentators noted an enduring rise in unemployment suffered by many industrialised nations since the 1970s. Yet a clear majority of both professional economists and the interested general public held the optimistic view through most of the 20th century.

In the second decade of the 21st century, a number of studies have been released suggesting that technological unemployment may be increasing worldwide. Oxford Professors Carl Benedikt Frey and Michael Osborne, for example, have estimated that 47 percent of U.S. jobs are at risk of automation. However, their findings have frequently been misinterpreted, and on the PBS NewsHours they again made clear that their findings do not necessarily imply future technological unemployment. While many economists and commentators still argue such fears are unfounded, as was widely accepted for most of the previous two centuries, concern over technological unemployment is growing once again.

The World Bank’s World Development Report 2019 argues that while automation displaces workers, technological innovation creates more new industries and jobs on balance.

Issues within the debates

Long term effects on employment
All participants in the technological employment debates agree that temporary job losses can result from technological innovation. Similarly, there is no dispute that innovation sometimes has positive effects on workers. Disagreement focuses on whether it is possible for innovation to have a lasting negative impact on overall employment. Levels of persistent unemployment can be quantified empirically, but the causes are subject to debate. Optimists accept short term unemployment may be caused by innovation, yet claim that after a while, compensation effects will always create at least as many jobs as were originally destroyed. While this optimistic view has been continually challenged, it was dominant among mainstream economists for most of the 19th and 20th centuries.

The concept of structural unemployment, a lasting level of joblessness that does not disappear even at the high point of the business cycle, became popular in the 1960s. For pessimists, technological unemployment is one of the factors driving the wider phenomena of structural unemployment. Since the 1980s, even optimistic economists have increasingly accepted that structural unemployment has indeed risen in advanced economies, but they have tended to blame this on globalisation and offshoring rather than technological change. Others claim a chief cause of the lasting increase in unemployment has been the reluctance of governments to pursue expansionary policies since the displacement of Keynesianism that occurred in the 1970s and early 80s. In the 21st century, and especially since 2013, pessimists have been arguing with increasing frequency that lasting worldwide technological unemployment is a growing threat.

Compensation effects
Compensation effects are labour-friendly consequences of innovation which “compensate” workers for job losses initially caused by new technology. In the 1820s, several compensation effects were described by Say in response to Ricardo’s statement that long term technological unemployment could occur. Soon after, a whole system of effects was developed by Ramsey McCulloch. The system was labelled “compensation theory” by Marx, who proceeded to attack the ideas, arguing that none of the effects were guaranteed to operate. Disagreement over the effectiveness of compensation effects has remained a central part of academic debates on technological unemployment ever since.

Compensation effects include:

By new machines. (The labour needed to build the new equipment that applied innovation requires.)
By new investments. (Enabled by the cost savings and therefore increased profits from the new technology.)
By changes in wages. (In cases where unemployment does occur, this can cause a lowering of wages, thus allowing more workers to be re-employed at the now lower cost. On the other hand, sometimes workers will enjoy wage increases as their profitability rises. This leads to increased income and therefore increased spending, which in turn encourages job creation.)
By lower prices. (Which then lead to more demand, and therefore more employment.) Lower prices can also help offset wage cuts, as cheaper goods will increase workers’ buying power.
By new products. (Where innovation directly creates new jobs.)

The “by new machines” effect is now rarely discussed by economists; it is often accepted that Marx successfully refuted it. Even pessimists often concede that product innovation associated with the “by new products” effect can sometimes have a positive effect on employment. An important distinction can be drawn between ‘process’ and ‘product’ innovations. Evidence from Latin America seems to suggest that product innovation significantly contributes to the employment growth at the firm level, more so than process innovation. The extent to which the other effects are successful in compensating the workforce for job losses has been extensively debated throughout the history of modern economics; the issue is still not resolved. One such effect that potentially complements the compensation effect is job multiplier. According to research developed by Enrico Moretti, with each additional skilled job created in high tech industries in a given city, more than two jobs are created in the non-tradable sector. His findings suggest that technological growth and the resulting job-creation in high-tech industries might have a more significant spillover effect than we have anticipated. Evidence from Europe also supports such a job multiplier effect, showing local high-tech jobs could create five additional low-tech jobs.

Many economists now pessimistic about technological unemployment accept that compensation effects did largely operate as the optimists claimed through most of the 19th and 20th century. Yet they hold that the advent of computerisation means that compensation effects are now less effective. An early example of this argument was made by Wassily Leontief in 1983. He conceded that after some disruption, the advance of mechanization during the Industrial Revolution actually increased the demand for labour as well as increasing pay due to effects that flow from increased productivity. While early machines lowered the demand for muscle power, they were unintelligent and needed large armies of human operators to remain productive. Yet since the introduction of computers into the workplace, there is now less need not just for muscle power but also for human brain power. Hence even as productivity continues to rise, the lower demand for human labour may mean less pay and employment. However, this argument is not fully supported by more recent empirical studies. One research done by Erik Brynjolfsson and Lorin M. Hitt in 2003 presents direct evidence that suggests a positive short-term effect of computerization on firm-level measured productivity and output growth. In addition, they find the long-term productivity contribution of computerization and technological changes might even be greater.

The Luddite fallacy
The term “Luddite fallacy” is sometimes used to express the view that those concerned about long term technological unemployment are committing a fallacy, as they fail to account for compensation effects. People who use the term typically expect that technological progress will have no long term impact on employment levels, and eventually will raise wages for all workers, because progress helps to increase the overall wealth of society. The term is based on the early 19th century example of the Luddites. During the 20th century and the first decade of the 21st century, the dominant view among economists has been that belief in long term technological unemployment was indeed a fallacy. More recently, there has been increased support for the view that the benefits of automation are not equally distributed.

There are two underlying premises for why long-term difficulty could develop. The one that has traditionally been deployed is that ascribed to the Luddites (whether or not it is a truly accurate summary of their thinking), which is that there is a finite amount of work available and if machines do that work, there can be no other work left for humans to do. Economists call this the lump of labour fallacy, arguing that in reality no such limitation exists. However, the other premise is that it is possible for long-term difficulty to arise that has nothing to do with any lump of labour. In this view, the amount of work that can exist is infinite, but (1) machines can do most of the “easy” work, (2) the definition of what is “easy” expands as information technology progresses, and (3) the work that lies beyond “easy” (the work that requires more skill, talent, knowledge, and insightful connections between pieces of knowledge) may require greater cognitive faculties than most humans are able to supply, as point 2 continually advances. This latter view is the one supported by many modern advocates of the possibility of long-term, systemic technological unemployment.

Skill levels and technological unemployment
A common view among those discussing the effect of innovation on the labour market has been that it mainly hurts those with low skills, while often benefiting skilled workers. According to scholars such as Lawrence F. Katz, this may have been true for much of the twentieth century, yet in the 19th century, innovations in the workplace largely displaced costly skilled artisans, and generally benefited the low skilled. While 21st century innovation has been replacing some unskilled work, other low skilled occupations remain resistant to automation, while white collar work requiring intermediate skills is increasingly being performed by autonomous computer programs.

Some recent studies however, such as a 2015 paper by Georg Graetz and Guy Michaels, found that at least in the area they studied – the impact of industrial robots – innovation is boosting pay for highly skilled workers while having a more negative impact on those with low to medium skills. A 2015 report by Carl Benedikt Frey, Michael Osborne and Citi Research, agreed that innovation had been disruptive mostly to middle-skilled jobs, yet predicted that in the next ten years the impact of automation would fall most heavily on those with low skills.

Geoff Colvin at Forbes argued that predictions on the kind of work a computer will never be able to do have proven inaccurate. A better approach to anticipate the skills on which humans will provide value would be to find out activities where we will insist that humans remain accountable for important decisions, such as with judges, CEOs, bus drivers and government leaders, or where human nature can only be satisfied by deep interpersonal connections, even if those tasks could be automated.

In contrast, others see even skilled human laborers being obsolete. Oxford academics Carl Benedikt Frey and Michael A Osborne have predicted computerization could make nearly half of jobs redundant; of the 702 professions assessed, they found a strong correlation between education and income with ability to be automated, with office jobs and service work being some of the more at risk. In 2012 co-founder of Sun Microsystems Vinod Khosla predicted that 80% of medical doctors jobs would be lost in the next two decades to automated machine learning medical diagnostic software.

Empirical findings
There has been a lot of empirical research that attempts to quantify the impact of technological unemployment, mostly done at the microeconomic level. Most existing firm-level research has found a labor-friendly nature of technological innovations. For example, German economists Stefan Lachenmaier and Horst Rottmann find that both product and process innovation have a positive effect on employment. They also find that process innovation has a more significant job creation effect than product innovation. This result is supported by evidence in the United States as well, which shows that manufacturing firm innovations have a positive effect on the total number of jobs, not just limited to firm-specific behavior.

At the industry level, however, researchers have found mixed results with regard to the employment effect of technological changes. A 2017 study on manufacturing and service sectors in 11 European countries suggests that positive employment effects of technological innovations only exist in the medium- and high-tech sectors.There also seems to be a negative correlation between employment and capital formation, which suggests that technological progress could potentially be labor-saving given that process innovation is often incorporated in investment.

Limited macroeconomic analysis has been done to study the relationship between technological shocks and unemployment. The small amount of existing research, however, suggests mixed results. Italian economist Marco Vivarelli finds that the labor-saving effect of process innovation seems to have affected the Italian economy more negatively than the United States. On the other hand, the job creating effect of product innovation could only be observed in the United States, not Italy. Another study in 2013 finds a more transitory, rather than permanent, unemployment effect of technological change.

Measures of technological innovation
There have been four main approaches that attempt to capture and document technological innovation quantitatively. The first one, proposed by Jordi Gali in 1999 and further developed by Neville Francis and Valerie A. Ramey in 2005, is to use long-run restrictions in a Vector Autoregression (VAR) to identify technological shocks, assuming that only technology affects long-run productivity.

The second approach is from Susanto Basu, John Fernald and Miles Kimball. They create a measure of aggregate technology change with augmented Solow residuals, controlling for aggregate, non-technological effects such as non-constant returns and imperfect competition.

The third method, initially developed by John Shea in 1999, takes a more direct approach and employs observable indicators such as Research and Development (R&D) spending, and number of patent applications. This measure of technological innovation is very widely used in empirical research, since it does not rely on the assumption that only technology affects long-run productivity, and fairly accurately captures the output variation based on input variation. However, there are limitations with direct measures such as R&D. For example, since R&D only measures the input in innovation, the output is unlikely to be perfectly correlated with the input. In addition, R&D fails to capture the indeterminate lag between developing a new product or service, and bringing it to market.

The fourth approach, constructed by Michelle Alexopoulos, looks at the number of new titles published in the fields of technology and computer science to reflect technological progress, which turns out to be consistent with R&D expenditure data. Compared with R&D, this indicator captures the lag between changes in technology.


Preventing net job losses

Banning/refusing innovation
Historically, innovations were sometimes banned due to concerns about their impact on employment. Since the development of modern economics, however, this option has generally not even been considered as a solution, at least not for the advanced economies. Even commentators who are pessimistic about long-term technological unemployment invariably consider innovation to be an overall benefit to society, with JS Mill being perhaps the only prominent western political economist to have suggested prohibiting the use of technology as a possible solution to unemployment.

Gandhian economics called for a delay in the uptake of labour saving machines until unemployment was alleviated, however this advice was largely rejected by Nehru who was to become prime minister once India achieved its independence. The policy of slowing the introduction of innovation so as to avoid technological unemployment was however implemented in the 20th century within China under Mao’s administration.

Shorter working hours
In 1870, the average American worker clocked up about 75 hours per week. Just prior to World War II working hours had fallen to about 42 per week, and the fall was similar in other advanced economies. According to Wassily Leontief, this was a voluntary increase in technological unemployment. The reduction in working hours helped share out available work, and was favoured by workers who were happy to reduce hours to gain extra leisure, as innovation was at the time generally helping to increase their rates of pay.

Further reductions in working hours have been proposed as a possible solution to unemployment by economists including John R. Commons, Lord Keynes and Luigi Pasinetti. Yet once working hours have reached about 40 hours per week, workers have been less enthusiastic about further reductions, both to prevent loss of income and as many value engaging in work for its own sake. Generally, 20th-century economists had argued against further reductions as a solution to unemployment, saying it reflects a Lump of labour fallacy. In 2014, Google’s co-founder, Larry Page, suggested a four-day workweek, so as technology continues to displace jobs, more people can find employment.

Public works
Programmes of public works have traditionally been used as way for governments to directly boost employment, though this has often been opposed by some, but not all, conservatives. Jean-Baptiste Say, although generally associated with free market economics, advised that public works could be a solution to technological unemployment. Some commentators, such as professor Mathew Forstater, have advised that public works and guaranteed jobs in the public sector may be the ideal solution to technological unemployment, as unlike welfare or guaranteed income schemes they provide people with the social recognition and meaningful engagement that comes with work.

For less developed economies, public works may be an easier to administrate solution compared to universal welfare programmes. As of 2015, calls for public works in the advanced economies have been less frequent even from progressives, due to concerns about sovereign debt. A partial exception is for spending on infrastructure, which has been recommended as a solution to technological unemployment even by economists previously associated with a neoliberal agenda, such as Larry Summers.

Improved availability to quality education, including skills training for adults and other active labour market policies, is a solution that in principle at least is not opposed by any side of the political spectrum, and welcomed even by those who are optimistic about long-term technological employment. Improved education paid for by government tends to be especially popular with industry.

Proponents of this brand of policy assert higher level, more specialized learning is a way to capitalize from the growing technology industry. Leading technology research university MIT published an open letter to policymakers advocating for the “reinvention of education”, namely a shift “away from rote learning” and towards STEM disciplines. Similar statements released by the U.S President’s Council of Advisors on Science and Technology (PACST) have also been used to support this STEM emphasis on enrollment choice in higher learning. Education reform is also a part of the U.K government’s “Industrial Strategy”, a plan announcing the nation’s intent to invest millions into a “technical education system”. The proposal includes the establishment of a retraining program for workers who wish to adapt their skill-sets. These suggestions combat the concerns over automation through policy choices aiming to meet the emerging needs of society via updated information. Of the professionals within the academic community who applaud such moves, often noted is a gap between economic security and formal education —a disparity exacerbated by the rising demand for specialized skills—and education’s potential to reduce it.

However, several academics have also argued that improved education alone will not be sufficient to solve technological unemployment, pointing to recent declines in the demand for many intermediate skills, and suggesting that not everyone is capable in becoming proficient in the most advanced skills. Kim Taipale has said that “The era of bell curve distributions that supported a bulging social middle class is over… Education per se is not going to make up the difference.” while an op-ed piece from 2011, Paul Krugman, an economics professor and columnist for the New York Times, argued that better education would be an insufficient solution to technological unemployment, as it “actually reduces the demand for highly educated workers”.

Living with technological unemployment

Welfare payments
The use of various forms of subsidies has often been accepted as a solution to technological unemployment even by conservatives and by those who are optimistic about the long term effect on jobs. Welfare programmes have historically tended to be more durable once established, compared with other solutions to unemployment such as directly creating jobs with public works. Despite being the first person to create a formal system describing compensation effects, Ramsey McCulloch and most other classical economists advocated government aid for those suffering from technological unemployment, as they understood that market adjustment to new technology was not instantaneous and that those displaced by labour-saving technology would not always be able to immediately obtain alternative employment through their own efforts.

Basic income
Several commentators have argued that traditional forms of welfare payment may be inadequate as a response to the future challenges posed by technological unemployment, and have suggested a basic income as an alternative. People advocating some form of basic income as a solution to technological unemployment include Martin Ford, Erik Brynjolfsson, Robert Reich and Guy Standing. Reich has gone as far as to say the introduction of a basic income, perhaps implemented as a negative income tax is “almost inevitable”, while Standing has said he considers that a basic income is becoming “politically essential”. Since late 2015, new basic income pilots have been announced in Finland, the Netherlands, and Canada. Further recent advocacy for basic income has arisen from a number of technology entrepreneurs, the most prominent being Sam Altman, president of Y Combinator.

Skepticism about basic income includes both right and left elements, and proposals for different forms of it have come from all segments of the spectrum. For example, while the best-known proposed forms (with taxation and distribution) are usually thought of as left-leaning ideas that right-leaning people try to defend against, other forms have been proposed even by libertarians, such as von Hayek and Friedman. Republican president Nixon’s Family Assistance Plan (FAP) of 1969, which had much in common with basic income, passed in the House but was defeated in the Senate.

One objection to basic income is that it could be a disincentive to work, but evidence from older pilots in India, Africa, and Canada indicates that this does not happen and that a basic income encourages low-level entrepreneurship and more productive, collaborative work. Another objection is that funding it sustainably is a huge challenge. While new revenue-raising ideas have been proposed such as Martin Ford’s wage recapture tax, how to fund a generous basic income remains a debated question, and skeptics have dismissed it as utopian. Even from a progressive viewpoint, there are concerns that a basic income set too low may not help the economically vulnerable, especially if financed largely from cuts to other forms of welfare.

To better address both the funding concerns and concerns about government control, one alternative model is that the cost and control would be distributed across the private sector instead of the public sector. Companies across the economy would be required to employ humans, but the job descriptions would be left to private innovation, and individuals would have to compete to be hired and retained. This would be a for-profit sector analog of basic income, that is, a market-based form of basic income. It differs from a job guarantee in that the government is not the employer (rather, companies are) and there is no aspect of having employees who “cannot be fired”, a problem that interferes with economic dynamism. The economic salvation in this model is not that every individual is guaranteed a job, but rather just that enough jobs exist that massive unemployment is avoided and employment is no longer solely the privilege of only the very smartest or highly trained 20% of the population. Another option for a market-based form of basic income has been proposed by the Center for Economic and Social Justice (CESJ) as part of “a Just Third Way” (a Third Way with greater justice) through widely distributed power and liberty. Called the Capital Homestead Act, it is reminiscent of James S. Albus’s Peoples’ Capitalism in that money creation and securities ownership are widely and directly distributed to individuals rather than flowing through, or being concentrated in, centralized or elite mechanisms.

Broadening the ownership of technological assets
Several solutions have been proposed which do not fall easily into the traditional left-right political spectrum. This includes broadening the ownership of robots and other productive capital assets. Enlarging the ownership of technologies has been advocated by people including James S. Albus John Lanchester, Richard B. Freeman, and Noah Smith. Jaron Lanier has proposed a somewhat similar solution: a mechanism where ordinary people receive “nano payments” for the big data they generate by their regular surfing and other aspects of their online presence.

Structural changes towards a post-scarcity economy
The Zeitgeist Movement (TZM), The Venus Project (TVP) as well as various individuals and organizations propose structural changes towards a form of a post-scarcity economy in which people are ‘freed’ from their automatable, monotonous jobs, instead of ‘losing’ their jobs. In the system proposed by TZM all jobs are either automated, abolished for bringing no true value for society (such as ordinary advertising), rationalized by more efficient, sustainable and open processes and collaboration or carried out based on altruism and social relevance, opposed to compulsion or monetary gain. The movement also speculates that the free time made available to people will permit a renaissance of creativity, invention, community and social capital as well as reducing stress.

Other approaches
The threat of technological unemployment has occasionally been used by free market economists as a justification for supply side reforms, to make it easier for employers to hire and fire workers. Conversely, it has also been used as a reason to justify an increase in employee protection.

Economists including Larry Summers have advised a package of measures may be needed. He advised vigorous cooperative efforts to address the “myriad devices” – such as tax havens, bank secrecy, money laundering, and regulatory arbitrage – which enable the holders of great wealth to avoid paying taxes, and to make it more difficult to accumulate great fortunes without requiring “great social contributions” in return. Summers suggested more vigorous enforcement of anti-monopoly laws; reductions in “excessive” protection for intellectual property; greater encouragement of profit-sharing schemes that may benefit workers and give them a stake in wealth accumulation; strengthening of collective bargaining arrangements; improvements in corporate governance; strengthening of financial regulation to eliminate subsidies to financial activity; easing of land-use restrictions that may cause estates to keep rising in value; better training for young people and retraining for displaced workers; and increased public and private investment in infrastructure development, such as energy production and transportation.

Michael Spence has advised that responding to the future impact of technology will require a detailed understanding of the global forces and flows technology has set in motion. Adapting to them “will require shifts in mindsets, policies, investments (especially in human capital), and quite possibly models of employment and distribution”.

Source from Wikipedia