TECHNOLOGICAL CHANGE AND THE LABOR MARKET

The usefulness of the article: The rise of new technologies which began in the 1980s, with the rapid diffusion of robotics and IT, has profoundly changed the production methods of companies. This article summarizes how these long-term trends have transformed the labor market in Western countries and reflects on the prospects for innovation linked to artificial intelligence.

Summary  :

• Starting in the 1980s, the wave of innovation linked to robotics and computing sharply increased the remuneration of skilled workers and led to the decline of jobs that were in the middle of the wage distribution.

• This trend has contributed to widening salary gaps between graduates and non-graduates but has had an ambiguous effect on career trajectories. The latter depends on the intrinsic abilities of each individual to retrain, but also on the role played by companies in continuing training.

• Artificial intelligence could partly reverse the trend by further replacing skilled trades, but it will probably not affect the profits of the richest 1% of workers.

• The COVID-19 crisis could bring new impetus to the automation of certain jobs at high risk of viral contamination, by further affecting low-skilled professions and in particular those carried out mainly by women.

Since the Industrial Revolution, production methods have never stopped evolving and transforming over time. However, what characterizes the period between the early 1980s and today is a significant acceleration in the pace of technological change, making adaptation increasingly difficult (Brynjolfsson & McAfee, 2012). This note summarizes how the changes in modes of production that have emerged over the last four decades have affected the labor markets of Western countries, and concludes with a reflection on what we can expect from the next wave of innovation linked to artificial intelligence. The effects of technological change are shown using the example of the United States.

Robotics and computing constitute two of the major innovations of the end of the 20th century (Figure 1). The blue curve shows that in the early 1980s, industrial robots were almost non-existent. The period from 1980 to 2000 saw the first boom in robotics, which was mainly adopted in the automotive industry. From the beginning of the 2000s, these technologies spread more widely in the manufacturing sector until reaching a density of 15 robots per 1000 inhabitants in 2015. The development of IT reached its peak between the 1980s and the 1980s. 2000, where investment in this technology increased from 1.6% to more than 4% of GDP in the United States. This movement came to a sudden halt when the internet bubble burst in 2000 and then stabilized.

The diffusion of these two technologies took place around the same time in other Western countries. This has generated a profound transformation in the way businesses operate, which in turn has led to major changes in the job market.

1. Increased demand for skilled workers

The most striking effect of the rise of new technologies is a considerable increase in the need for qualified labor. Katz & Murphy (1992) and Goldin & Katz (1996) were among the first to describe the phenomenon of “skill-biased technological change” and to depict its consequences for labor market inequalities. Their analysis is based on the observation that the period from the 1980s to the 2000s was characterized both by strong growth in the number of graduates arriving on the job market and by the widening of the salary gaps between graduates and non-graduates ( Figure 2A). On the one hand, the level of education has increased: only 20% of workers had a post-baccalaureate diploma in 1970, while in 2012 they were around 50%. On the other hand, the pay gap according to qualification has widened: a non-qualified worker earned aroundtwo-thirdss of the salary of a qualified worker in 1970, while in 2012 he earned only half. These trends imply that during this period the need for skilled workers in the economy must have increased significantly. Indeed - as shown in Figure 2B - the increase in the education level of the population (shift in labor supply) would have predicted a decline in wage gaps in the absence of an even greater increase in the required work.

The massive adoption of robots and IT tools during this period is often considered the main factor behind the increase in salary inequality between graduates and non-graduates. However, Autor (2014) notes that, with the acceleration in the number of university enrollments in the early 2000s, wage gaps are beginning to stabilize in the United States. He therefore concludes that the increase in wage inequality is not inexorable and that policies encouraging higher education can reverse the trend, by operating on the lever of labor supply.

2. The decline of jobs in intermediate professions

In addition to favoring qualified workers, new production technologies have a second effect: the polarization of the labor market. Autor, Levy, & Murnane (2003) show that the main effect of robotics and computing has been to replace routine tasks previously performed by employees in intermediate occupations. Table 1 summarizes their classification of technological impact according to the type of tasks contained in each profession. They confirm that qualified professionals with an analytical nature such as engineers, doctors, lawyers, and managers are favored by these innovations because they are complementary to them. However, they also show that the workers most negatively affected are not those with the lowest level of education but rather those in intermediate jobs. Among the service employees, there are accountants, secretaries, and customer service managers - mainly replaced by IT -, and among the manufacturing sector workers, there are machine operators and assembly line workers - mainly replaced by robotics. Low-skilled, manual professions, such as delivery drivers, caregivers, and cleaners, are almost not impacted by this phenomenon, because they involve tasks that are difficult to replace by machines.

The fact that new technologies mainly replace professions in the middle of the wage distribution has resulted in the polarization of the labor market. Autor et al. (2006) show that between 1990 and 2000 employment in intermediate professions declined, while employment at both poles of distribution grew (Figure 3). The latter was more significant in skilled professions due to their complementarity with machines but also affected the least well-paid professions. This phenomenon is not specific to the American context but is observed across all industrialized countries. Goos, Manning, & Salomons (2014) show that the same trends are visible in 16 Western European countries, and Harrigan, Reshef, & Toubal (2016) document it for France. However, this phenomenon seems to have faded from the 2000s, probably due to a slowdown in skills needs, while the supply of qualified workers continues to increase (Beaudry, Green, & Sand, 2016).

3. An ambiguous effect on career trajectories

Empirical evidence has joined a consensus diagnosis that new production technologies linked to robotics and computing are destroying jobs in the middle of the wage distribution and creating jobs at the top of the distribution, without changing much for professions at the bottom of the distribution. However, the effect on total employment and career trajectories remains ambiguous and seems to depend on the particular context of interest. Bessen (2017) explains how the effect of new technologies on total employment also depends on the impact on demand for the goods produced with these innovations. The latter is set to grow due to falling prices associated with falling production costs (Graetz & Michaels, 2018). Dauth et al. (2019) find that the rise of robotics in Germany destroys jobs in industry but creates as many jobs in services, and shows that employees tend to retrain for better quality jobs by remaining with the same employer.

Similarly, Battisti, Dustmann, & Schönberg (2017) show that German routine workers do not necessarily experience a decline in their wages or an increased probability of unemployment. They recognize that companies play a crucial role in reskilling their employees by training them in analytical tasks that complement technology. Cortes (2016) emphasizes that in the United States, the consequences vary depending on the intrinsic capacities of individuals. The most capable workers succeed in retraining for more qualified analytical professions and see an increase in their salary. Conversely, workers with fewer skills face an increased risk of downgrading. The effect on job loss nevertheless seems quite weak.

In a recent contribution based on Swedish data, Edin et al. (2019) compare career trajectories over 30 years according to the routine nature of the job that individuals held in the mid-1980s – at the very beginning of the technological shock. They found that workers who were in routine jobs experienced a decline in their cumulative earnings of about 2% to 5% over the period from 1986 to 2013. This is explained by a combination of factors including higher wage growth. low in these professions and an increased risk of unemployment and downgrading to lower-paid professions. Furthermore, they agree with Cortes (2016) in showing that individuals who were already less well paid among routine workers are those who suffered the greatest decline in income over the period. In ongoing work, Le Moigne (2021) shows that the disappearance of jobs in the middle of the hierarchy within companies considerably decreases promotion opportunities for workers at the very bottom of the ladder. This suggests that paths to upward mobility could deteriorate following the disappearance of intermediate jobs.

4. Artificial Intelligence: A trend reversal?

In recent years we have witnessed the introduction of the next technological wave linked to artificial intelligence. This recent innovation is driven by the increasingly massive availability of huge databases – Big Data – and by the availability of the computing power necessary to analyze them. Although it is still too early to be able to measure the impact of its development on the labor market, some prospective studies are beginning to emerge and suggest that this technology could, at least in part, reshuffle the cards. Webb (2019) takes the same approach as Autor et al. (2006) by making a classification of tasks likely to be accomplished by artificial intelligence, and by identifying which professions are therefore at risk of being replaced by machines. The result is shown in Figure 4.

Unlike the previous wave of technological change, this one seems to affect the most skilled professions more. The ability of artificial intelligence to quickly analyze large volumes of data to detect trends, infer diagnoses, and make predictions could in the future replace certain tasks done today by doctors, lawyers, laboratory analysts, etc… We could therefore expect a downward leveling in the distribution of wages. However, this would not necessarily imply a reduction in inequalities in our societies. Workers in STEM (Science, Technology, Engineering, and Mathematics) professions will remain very complementary to artificial intelligence, and the owners of capital will emerge even more favored - two groups that already bring together the richest strata today. Webb (2019) estimates that artificial intelligence will reduce wage inequality between the top 10% and the bottom 10%, but will not affect the profits of the top 1%.

A report from France Stratégie on this subject underlines that, as with previous revolutions, the effect on total employment is ambiguous and could even be positive due to the productivity gains enabled by artificial intelligence (Benhamou & Janin, 2018 ). This report maintains that the challenges raised by AI resemble those described for previous innovations: the challenge will be to support professional retraining towards tasks where human contact remains crucial, such as supervision or reception. However, it also underlines an increasingly significant risk of “a loss of autonomy of the employee, subject to increasingly insidious automated control, with the associated psychosocial risks”.

5. Conclusion

The rise of technologies linked to robotization and computerization has contributed to increasing wage inequalities by increasing the need for qualified workers and destroying jobs with an average level of remuneration. These structural changes have sometimes polarized the career trajectories of individuals by inhibiting social mobility, but in other contexts, they have enabled the retraining of workers towards more interesting and better-paid jobs. Continuing training and support during career transitions play a crucial role in promoting the adaptation of workers already present in the market. In addition, access to higher education should be encouraged, by increasing the places available in technical fields, to adapt the skills of new generations to the needs of the future. Artificial intelligence could reduce the salary advantage in certain skilled professions, but we do not expect it to reduce the level of inequalities in our societies by itself. In addition, the health crisis linked to COVID-19 could bring new impetus to the automation of certain jobs at high risk of viral contamination, by further affecting low-skilled professions and in particular those carried out mainly by women (Chernoff & Warman, 2020).