**4. The automation risk in Europe, the United States, and Asia**

The estimated proportion of existing jobs at high risk of automation varies significantly by country.7 Factors such as differences in labor market structure, education and skill levels, governmental policies on Industry 4.0, and differences in working way differentiate automation rates across countries. On the other hand, countries with similar economic structure and similar characteristics present similar potential rates of job automation (see [4, 7] among others). Four country groups that could be set under examination concerning their risk of automation are:


Eastern European countries such as Slovakia (44%) and Slovenia (42%) face relatively high potential automation rates, while Nordic countries such as Finland (22%) and Asian countries such as South Korea (22%) have relatively lower shares of existing jobs that are potentially automatable. It is important here to underline that existing jobs in some countries with low automation rates, such as *Japan and South Korea*, may face higher automation rates in the short term, given that

**13**

**Figure 6.**

**Figure 7.**

*Fourth Industrial Revolution: Opportunities, Challenges, and Proposed Policies*

algorithmic technologies are already widely used there, but in the long term (when the automation will displace manual jobs) will have lower automation rates than countries with lower average workers' skill levels and large manufacturing bases. On the other hand, countries such as Turkey may face a lower exposure in the short term but higher exposure to the later automation waves that will displace manual

*Potential impact across countries by employment shares and automatability of jobs.*

Another interesting point in comparative analysis among these country groups (with an emphasis to the relation between **European and Asian countries**) is that European countries present strong negative correlations between the potential share of existing jobs at high risk of automation and the country education metrics such as government expenditure on education (as a % of GDP). This relationship is not so strong for Asian countries that present lower education spend. On the other hand, Asian countries achieve higher educational outcomes, especially in STEM subjects. Thus, the negative relationship between high education and low automatability holds for these countries as well, even with lower education spend. Furthermore, workforces in the more technologically advanced Asian countries such as Japan, South Korea, and Singapore have already adjusted to automation by *increasingly working with robots*, reducing in this way their future risk exposure

workers such drivers and construction workers.

*DOI: http://dx.doi.org/10.5772/intechopen.90412*

*Potential impact of job automation across the four country groups.*

<sup>7</sup> See [4, 7].

<sup>8</sup> See [7].

### **Figure 6.**

*Industrial Robotics - New Paradigms*

significantly by country.7

renewable sources of energy (wind, wave, solar) that may help countries to ensure their energy autonomy, (iv) sustainable industrialization and sustainable production infrastructure, (v) programs to promote the careful and sustainable use of terrestrial and marine ecosystems, (vi) the protection and sustainable use of forests, (vii) the protection and sustainable use of oceans and other water resources, (viii) the fight against desertification, and (ix) the protection of biodiversity.

**4. The automation risk in Europe, the United States, and Asia**

The estimated proportion of existing jobs at high risk of automation varies

education and skill levels, governmental policies on Industry 4.0, and differences in working way differentiate automation rates across countries. On the other hand, countries with similar economic structure and similar characteristics present similar potential rates of job automation (see [4, 7] among others). Four country groups

a.The **industrial economies**, that is, the economies where industrial production (that is easier to be automated), is still the dominant in total employment. Such economies are the **Eastern European economies** (Germany, Italy, etc.) that tend to have high shares of employment in industry sectors such as manufac-

that could be set under examination concerning their risk of automation are:

turing and transport that will be easily automated until 2030s.

relatively less automatable jobs and high-skill workers.

sectors) and low-skilled workers.

tion. **Figures 6–8**<sup>8</sup>

b.The **services-dominated economies** such as the **United States**, **United Kingdom**, and Netherlands, with relatively automatable jobs more concentrated in service sectors (that tend to be less automatable than industrial

c.The **Nordic countries** such as Finland, Sweden, and Norway (in addition to New Zealand and Greece outside this region) with high employment rates,

d.The **Asian nations** (Japan, South Korea, Singapore, Russia, etc.) with high levels of technological advancement and education and relatively less automatable jobs but also with relatively high concentrations of employment in industrial sectors. *East Asian and Nordic economies* seem to be *less affected* by the automation (with an estimated range 20–25%), and *Eastern European economies* are *more affected* with higher potential automation rate range around to 40%, while *service-dominated countries such as the UK and US* present *intermediate levels* of potential automa-

(individually) and across the four country groups and a range of estimates about

the share of existing jobs that are at high risk of automation by the 2030s.

Eastern European countries such as Slovakia (44%) and Slovenia (42%) face relatively high potential automation rates, while Nordic countries such as Finland (22%) and Asian countries such as South Korea (22%) have relatively lower shares of existing jobs that are potentially automatable. It is important here to underline that existing jobs in some countries with low automation rates, such as *Japan and South Korea*, may face higher automation rates in the short term, given that

depict this potential impact of automatability across countries

Factors such as differences in labor market structure,

**12**

<sup>7</sup> See [4, 7]. <sup>8</sup> See [7].

*Potential impact of job automation across the four country groups.*

**Figure 7.**

*Potential impact across countries by employment shares and automatability of jobs.*

algorithmic technologies are already widely used there, but in the long term (when the automation will displace manual jobs) will have lower automation rates than countries with lower average workers' skill levels and large manufacturing bases. On the other hand, countries such as Turkey may face a lower exposure in the short term but higher exposure to the later automation waves that will displace manual workers such drivers and construction workers.

Another interesting point in comparative analysis among these country groups (with an emphasis to the relation between **European and Asian countries**) is that European countries present strong negative correlations between the potential share of existing jobs at high risk of automation and the country education metrics such as government expenditure on education (as a % of GDP). This relationship is not so strong for Asian countries that present lower education spend. On the other hand, Asian countries achieve higher educational outcomes, especially in STEM subjects. Thus, the negative relationship between high education and low automatability holds for these countries as well, even with lower education spend. Furthermore, workforces in the more technologically advanced Asian countries such as Japan, South Korea, and Singapore have already adjusted to automation by *increasingly working with robots*, reducing in this way their future risk exposure

### *Industrial Robotics - New Paradigms*

### **Figure 8.** *Potential rates of job automation by country.*

### **Figure 9.**

*Relationship between density of industrial robots and industry-adjusted job automation rates.*

(they may also be benefited by automation in terms of higher productivity and real wages). **Figure 9**<sup>9</sup> shows this negative correlation between the potential jobs at high risk of automation and the density of industrial robots per country.

Concerning the United States, a great effort has been put to integrate into the manufacturing industry the latest developments in IT, Internet, and mechanical engineering so as to reduce the risk exposure of employees to automation and get benefit by the technological achievements of the Industry 4.0. However, as Brookings Institution [27] in its report underlines the Industry 4.0, and the wider notion of advanced industries has much in common with the advanced manufacturing sector in Europe, although it includes services (e.g., software) and energy as well that led the US economy (especially services); the United States is losing ground to other countries in advanced industry competitiveness since the

**15**

*robots market*.

innovations.

*Fourth Industrial Revolution: Opportunities, Challenges, and Proposed Policies*

comparison with other developed countries remain poor.

labor supply, the STEM occupations, the availability of skills, and the standards in

The leader among the Asian countries remains **China**. China's main ambition is to become a "strong" manufacturing nation within a decade, giving priority on *digitalization, modernization, and companies' maturity in Industry 4.0 terms*, including creativity, quality benefit, and integration of industrialization, information, and green development. Two main initiatives to achieve these goals are the *Internet Plus (IP)* and the *"Made in China"* (see [4] among others). *IP* is a plan aimed at upgrading traditional industries, searching for new technologies and spreading Internet applications into the public sector, increasing both quality and effectiveness of economic and social development. *Made in China 2025 plan* is strictly focused on five major projects among which new innovation centers, green and smart manufacturing, self-sufficiency in infrastructure, and indigenous R&D projects for high-value equipment, moving industrial companies up to the value chain. The main target of the *Made in China 2025 roadmap* is to develop a domestic innovation capacity that may be been seen as *China's equivalent to Industry 4.0*: "an effort to create a manufacturing revolution underpinned by smart technologies." Moreover, a study by Fraunhofer IAO10 about *patents registered in China* in relation to the *Industry 4.0 technologies* shows that Chinese researchers have patented important inventions in the fields of wireless sensor networks, low-cost robots, and big data, concluding that *China will be leading the pack when it comes to production data in the future*. In terms of the number of patents filed for Industry 4.0 technologies, *China has far outperformed the United States and Germany* (which is considered as a pioneer among European countries). The energy-efficient technologies intended for reliable industrial networks to robotics are basic areas in which Chinese have registered key

But the most important field of innovation in which China is considered as a pioneer among Asian countries (and worldwide) is the field of **robotics**. The number of industrial robots, using by businesses to boost their productivity, increases rapidly. According to the International Federation of Robotics or IFR (2015), the worldwide stock of robots reached in 2014 (5 years ago!) at 1.5 million units. This pace of "robotization" grows very rapidly, while the cost of new robots continues to fall and their capabilities to go up. Moreover, with the robot density in most industries to be low, the IFR anticipates that the pace of yearly robot installations will continue to grow even faster in the following years. By 2018, global sales of industrial robots were growing on average by 15% per year, and the number of units sold was around 400,000 units (see **Figures 10** and **11**) [28]. "The automation witnessed by the automotive sector and the electrical/electronics industry comes out top here with a market share of 64 percent," said IFR President Arturo Baroncelli. "A new generation of robots is a strong echo of various demands — the 'Made in China 2025' plan, US re-industrialization, Japan's rejuvenation strategy and the EU's Industrial 4.0 all symbolize the new age of equipment's transformation and a changing production mode," said Dr. Daokui Qu, CEO of SIASUN Robot & Automation. The regional breakdown reveals that 70% of the global robot sales are going to five countries: China, Japan, the United States, South Korea, and Germany. *China remains the main driver of the growth overtime and the world's biggest industrial* 

<sup>10</sup> https://www.fraunhofer.de/en/press/research-news/2014/march/security-tools.html.

*DOI: http://dx.doi.org/10.5772/intechopen.90412*

**4.1 The Asian giant China**

<sup>9</sup> See [7].

labor supply, the STEM occupations, the availability of skills, and the standards in comparison with other developed countries remain poor.
