B. RISKS OF UNEMPLOYMENT AND INCREASING INCOME DIVIDES
2. Job polarization
Job polarization refers to an expansion in high- and low-wage jobs combined with a contraction in middle-wage jobs. This phenomenon is not new; it has been documented in many advanced economies since the 1970s,43 though it is not yet happening to any great extent in developing countries.44 45
More conservative studies, usually from experts in specific technologies,
are cautious of overestimating effects
in the short term and underestimating those
in the long term.
Polarization has intensified in developed countries as skilled cognitive tasks are increasingly supported by computers. Higher-paid occupations tend to benefit more because they use computers more intensively than lower-paid ones.46 These occupations steadily absorb tasks from other professions;
for instance, when a manager starts to book her own travel instead of relying on an assistant.
Computerization reduces the demand for middle-wage jobs, such as those of clerks doing routine tasks.47 Thus far, there has been less impact on the demand for many of the lowest-skilled manual tasks, but that seems set to change with greater use of AI and robots.48 A study based on data on robot adoption within industries in 17 countries found that increased robot use reduced the share of employment of low-skilled workers.49 In addition, ever-more-capable robots and AI software will put further pressure on workers performing routine tasks, both manual and cognitive – from strawberry pickers to radiologists.50
AI can also affect the quality of employment – making it more interesting for high-skilled workers, but more boring for low-skilled workers. AI systems can also make high-skill jobs more problem-solving and demanding. In contrast, low-skilled workers are more likely to be receiving orders or instructions automatically generated by an AI system.51 A recent survey examined differences in the use of AI by workers in Denmark and found that high-skilled workers tended to use information compiled automatically by the AI systems for making decisions or advising clients (Box III 2).
Box III 2
Artificial intelligence, work organization and skills in Denmark
One of the world’s first surveys of employees’ use of AI on job and skills was conducted in 2019 by IKE, Aalborg University Business School, Denmark. This distinguished two uses of AI. The first is where the employee uses information compiled by the AI system to help them make decisions or advise clients. This corresponds to the idea that AI systems may enhance the skills of employees by providing useful inputs for further decision-making. The second is where the employee merely receives orders or instructions generated automatically by the AI system.
The survey found that around one-quarter of all employees used AI in one or other of the two forms at least once a month. However. the high-skilled workers were more likely to use the first form. As indicated in the figure below, while a similar proportion of all three categories of worker used AI to receive orders, a much higher proportion of the middle and high-skilled workers used it to support decision making.
The study also found that using AI for decision making increased the complexity of problem-solving tasks and thus made the work more demanding and interesting, while just receiving AI-generated instructions tends to make work more repetitive. The study shows the importance in both developed and developing countries of reshaping education and training system to best prepare students for working life.
Share of employees using AI by type of use
0 5 10 15 20 25 30
Low Middle High
AI for decisions AI for orders
Source: UNCTAD based on Gjerding AN, Holm JR and Lorenz E and Stamhus, J (2020). Ready, but challenged: Diffusion and use of artificial intelligence and robotics in Danish firms: Findings from the TASK survey. Alborg University Business School working paper series 001-2020.
Not all job polarization can be attributed to technological change. In advanced economies job polarization has been taking place during a period of globalization – and the shift in employment from manufacturing to services (Figure III 4).52 In Sweden, for example, the 1970s and 1980s
were periods of pronounced job polarization, but one study concluded that this was not due to routine-based technological change.53 For the low- and lower-middle-income countries the greatest shift in employment has been from agriculture to services.
Over the same period, there has been a trend towards higher-skill employment (Figure III 5). In upper-middle- and high-income countries, most work is in middle-skill jobs – such as clerical support workers, service and sales workers, craft and related trades workers, plant and machine operators, and assemblers. In the high-income countries there was a significant share of high-skill jobs. All country groupings, however, saw an expansion of high-skill occupations. Only the high-income countries had a reduction for medium-skilled workers.
Figure III 4
Employment by broad economic sector, income grouping (Percentage of total employment)
70.8 60 53.8
20.4 29.2 30.2 40.0 36.3 53.4 67.7 74.7
2000 2020 2000 2020 2000 2020 2000 2020
Low income Lower-middle income Upper-middle income High income Agriculture Manufacturing Industry (minus manufacturing) Services 0
Source: UNCTAD based on data from ILOStat.
Figure III 5
Employment by skill level
(Percentage of total civil employment)
74.4 67.9 59.4
2000 2020 2000 2020 2000 2020 2000 2020
Low income Lower-middle income Upper-middle income High income Low skills and skilled agricultural, forestry and fishery workers Medium skill High skill Source: UNCTAD based on data from ILOStat according to the ISCO-08.
Notes: Following ISCO-08 construction logic, a high skill level refers to major groups 1 to 3, a medium skill level to major groups 4, 5, 7 and 8, and a low skill level to major group 9 (skilled agricultural, forestry and fishery workers correspond to group 6, which is also considered medium skill but is combined with group 9 in the data made available by ILOStat).54
Some of the job polarization over this period will have been caused by automation, but much will also have been the result of trade and international competition. A study of job polarization in Denmark between 1999 and 2009 suggested that the main cause was import competition, through worker-level adjustments – with the highly educated and skilled workers ending up in high-wage jobs whereas less-educated workers ended up in low-wage positions.55 The workers most affected were those doing manual tasks regardless of how routine they were.
Another study, in Germany, found that the decline in manufacturing employment was steeper in import-competing than export-oriented sectors.56 However, the authors found that manufacturing jobs were retained because of rising trade with China and Eastern Europe. Moreover, the increase in services was caused by people entering the labour market, either young people or those returning from non-employment.
Adjustment in local labour markets due to import competition can be slow. A study on the effects of China’s emergence as an industrial powerhouse in local labour markets in the United States found that in the cities more affected, wages and labour-force participation rates sometimes remained low, and unemployment rates remained high, more than a decade after the start of the China trade shock.57 Technological change is thus interlinked with structural changes and international trade. Low and middle-income countries are probably less exposed to potential negative effects of frontier technologies such as AI and robots on job polarization.