**6. Case study: Greece**

An interesting case study is that of Greece. It is about a country that does not belong to heavy industrial economies, such that of Germany, Slovakia, and Italy which have relatively inelastic labor markets and large tertiary service sectors that may be strongly affected by the Fourth Industrial Revolution. Jobs in Greece are more related to tasks that require the involvement of human factor such as teaching and elderly care and less to routine tasks.

In general, the automation process involves three overlapping waves: (i) an *Algorithm wave* that mainly focuses on automating simple computational tasks such as structured data analysis and mathematical calculations, and it is expected to reach its full maturity by 2020, (ii) an *Augmentation wave* that focuses on the

*Industrial Robotics - New Paradigms*

and machines present in their lives.

entrepreneurship, focusing on the following:

peacefully and effectively across the time will not be set in danger by the AI robots

Besides the problems that may arise or get bigger during the Fourth Industrial Revolution, there are also significant economic and social opportunities that may contribute to a sustainable socioeconomic growth (see [32, 33] among others). Concerning entrepreneurship, new technologies must not be treated as a threat for human work but as a valuable tool/assistant for employees to increase their productivity and facilitate their decision-making and for entrepreneurs to boost their business competitiveness and productivity. Governments could also support

i.Providing know-hows to start-ups and small- and medium-sized enterprises (SMEs) about next-generation technologies and digitalization in order to

ii.Supporting co-operations among enterprises, businesses and research institutes, enterprises and people who have great market experience as business

iii.Promoting funding measures for start-ups and small- and medium-sized enterprises (SMEs) in order to help them participating in technological development processes, for example, facilitation of their access to public funding and guarantees (and to private borrowing), support of co-financing by industry and market players, and use of innovative and close-to-market

iv.Facilitating the access to multilevel platforms that offer digital transformation programs for businesses in order to reduce information asymmetry and

v.Reducing bureaucracy and barriers for business to be expanded in new

The new IT systems may also give to entrepreneurs the chance to participate in new supply chains for small- and medium-sized enterprises and have access to new product and service markets that under other conditions would be difficult and costly. The development of new markets with greater quantity and variety of products and services, and eventual lower prices, in combination with the improvement of the existing jobs' efficiency and the improvement of customer service, will benefit consumers driving to a demand increase and consequently to a labor demand increase. New technologies may further increase the labor demand by creating new, stable, and well-paid jobs in innovative technological sectors that will

These policies may benefit both businesses and governments; entrepreneurs will be smoothly adapted to the new technological conditions and the digitalization having the appropriate support, and governments will increase their tax revenue due to the higher labor income and the increased business gains (due to the use of new technologies that improves businesses' effectiveness). This additional tax revenue may finance higher public spending on health and education and support additional

financing instruments such as business loans and tax incentives.

**5. Opportunities related to the Fourth Industrial Revolution**

increase their revenue and reduce their production costs.

angels, businesses, and public and regional authorities.

help businesses to remain updated and sustainable.

markets and diversify their activities.

**20**

jobs in these areas.

automation of repeating tasks such as communication and information exchange and statistical analysis of unstructured data that is in progress, and (iii) an *Autonomy wave* that focuses on the physical and manual work automation, such as manufacturing and transporting, that is likely to reach its full maturity by 2030.

Based on international studies' results (see [5–7], among others), less than 5% of the jobs in Greece is exposed to the automation risk due to the Algorithm wave, 10% is exposed due to the Augmentation wave and 10% of the jobs is exposed due to of the Autonomy wave, completing a percentage of about 25% of jobs in Greece that is exposed to the automation risk. This is the fourth lowest percentage of exposure to the automation risk among other OECD economies, along with some technologically advanced countries in East Asia and Scandinavia (20–25%).

Moving to an in-depth analysis of the data about the long-term impact of automation in Greece and making a separation by gender, age, educational level, and industry, one may firstly observe that the proportion of men exposed to the risk of automation (27%) is higher than that of women (18%). This is basically related to the nature of the tasks that men undertake, for example, manual work and tasks that require muscle strength and can be easily automated. Additionally, PISA scores show that women in Europe achieve better educational results than men, which may further explain the lower rate of exposure to automation risk for women. It is noteworthy that the percentage of women exposed to the risk of automation in Greece is among the lowest in Europe.

Focusing on the age groups, the highest rate of exposure (25%) is observed for the *middle-aged group (40–50 years)* and the lowest (19%) for the age group of young people with elderly people to follow with 20%. In the most European countries, the highest rate of exposure is observed for the age group of elderly people. This is mainly explained by the difficulty of elder people to be adapted to the new conditions and by the low participation rates of elderly people in labor market and in re-training programs that could help them to be adapted to the new reality. The high rates of "Not in Education, Employment, or Training" middle-aged people in Greece and their very low participation in re-skilling and up-skilling programs in order to get familiar with new technologies and become more competitive in labor market may offer an explanation for the high rate of exposure to the risk of automation for the middle-aged group in Greece.

Concerning educational level, the lowest rate of exposure to automation is observed for highly educated people (10%), the highest (30%) for people who have medium educational level, while people with low educational level present a rate of exposure of about 24%. It is about an expected result since highly qualified and educated people are at lower automation risk than medium- or low-qualified workers because of the nature of the tasks they undertake that is more complex and demanding and thus more difficult to be automated. The fact that the highest rate of exposure to automation is observed for people with medium educational level is in accordance to the results of several studies, such that of UBS [26], according to which the greatest impact of the Fourth Industrial Revolution will be experienced by the medium-skilled employees in jobs such as the customer service that although require communication skills and personal contact with the clients can be easily replaced by artificial intelligence.

The industry that appears to be most exposed to automation in Greece is the manufacturing sector with 35% rate of exposure (the 4th lowest percentage among other OECD countries). The second most exposed industry is the construction sector with 25% rate of exposure (second lowest), followed by retail trade with 23% (third lowest), social protection and health industry with 20%, and the education sector with the lowest rate of exposure of 3%. Humanitarian activities such as social protection and care services, education, and teaching require high

**23**

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

social and cognitive skills, personal contact, and communication skills and exhibit low exposure rates to automation in comparison with the manufacturing and the construction sectors. This is in accordance to the previous findings for the Fourth Industrial Revolution concerning the sectors that are more exposed to automation. In general, the rates of exposure to automation for all professional sectors in Greece are among the lowest in Europe; especially the risk of automation of the educational sector in Greece is lower than the average of all countries worldwide, emphasizing the anthropocentric nature of the Greek educational system that makes quite difficult the total replacement of human factor by machines and robots in the long run.

Major waves of technological progress such that of Fourth Industrial Revolution

always create concerns about the future of human labor and the possibility of substitution of the human factor by machines and robots. The main findings of this paper show that the Industry 4.0 does not seem to threaten the human labor under the conditions that employees are able to be quickly adapted to the new reality and governments follow the appropriate policies to protect people from the unpredictable and undesirable consequences of technological progress. The jobs that are most exposed to automation are the routine jobs with a high volume of tasks that do not require high communicative and cognitive skills such as office work, constructions and manufacturing, and wholesale and retail trade. On the other hand, jobs such as teaching, nursing, and elderly care that are multitask and require flexibility, true creativity, and social intelligence are difficult to be automated. Therefore, the complete substitution of human workforce by robots in labor market is extremely

Deloitte's report [24] characterizes the Fourth Industrial Revolution as "a mixture of hope and doubt." On the one hand, new technologies create opportunities for sustainable economic growth and reduction of unemployment; create new job positions in innovative sectors; contribute to the strengthening of competitiveness and productivity of workers and businesses, to the increase of labor income and business gains, to the improvement of human life quality, and to the physical and mental health improvement increasing life expectancy; allow for high levels of innovation and knowledge; facilitate the access to quality education for all; and contribute to the early diagnosis of extreme weather events, to the sustainable urbanization, and to the fight against inequalities, poverty, and hunger. On the other hand, the loss of millions jobs due to automation, the invasion of artificial intelligence even in jobs where the human factor is crucial, the potential income and socioeconomic inequality gap widening with the poor and developing economies to be more affected, the gender gap expansion, the increase of poverty and hunger because of the potential job loss, the violation of personal data, the use of new technologies for illegal activities, the national and international security issues such as the threat of a nuclear or a chemical conflict, and the climate change with the increasing extreme weather phenomena are some of the most important challenges

Indicative key policies that governments could follow to deal with these challenges and take advantage from opportunities arising from the Fourth Industrial Revolution are the following: (1) give priority to the *education and* the *training* for people of all ages (with an emphasis to STEM issues) in order to obtain the cognitive and social skills required by the labor market and protect job positions from automation; (2) create *new well-paid jobs*, so as to moderate the potential job loss (due to automation) and deal with income and socioeconomic inequality;

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

**7. Conclusion**

unlikely to happen.

related with the Industry 4.0.

### *Fourth Industrial Revolution: Opportunities, Challenges, and Proposed Policies DOI: http://dx.doi.org/10.5772/intechopen.90412*

social and cognitive skills, personal contact, and communication skills and exhibit low exposure rates to automation in comparison with the manufacturing and the construction sectors. This is in accordance to the previous findings for the Fourth Industrial Revolution concerning the sectors that are more exposed to automation. In general, the rates of exposure to automation for all professional sectors in Greece are among the lowest in Europe; especially the risk of automation of the educational sector in Greece is lower than the average of all countries worldwide, emphasizing the anthropocentric nature of the Greek educational system that makes quite difficult the total replacement of human factor by machines and robots in the long run.
