**7. Conclusion**

*Industrial Robotics - New Paradigms*

Greece is among the lowest in Europe.

tion for the middle-aged group in Greece.

replaced by artificial intelligence.

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.

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

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 automa-

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

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

cally advanced countries in East Asia and Scandinavia (20–25%).

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 technologi-

**22**

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 unlikely to happen.

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 related with the Industry 4.0.

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;

(3) *strengthen social security networks*, especially for those who have difficulty to be adapted to new technologies; (4) apply *tax transformations* in order to increase tax revenue from workers whose earnings will increase due to the Industry 4.0 and apply a tax relief for workers whose income will be reduced; (5) *support entrepreneurship*, by giving small and start-up businesses the chance to improve their efficiency and increase their revenue using new technologies; (6) promote *women's participation in STEM programs* and activities in order to reduce the gender gap; (7) *support countries' cooperation*, for a better diffusion of knowledge and best practices among national governments; (8) give an emphasis to *transparency* through digital portals and accountability mechanisms; (9) impose strict rule*s* to prevent the use of new technologies for *illegal activities* and protect people from a possible violation of their personal data; (10) institutionalize strict laws and regulations to protect people from a possible nuclear or chemical conflict with unpredictable consequences; (11) promote *smart agricultural production* in order to deal with hunger; and (12) support *sustainable use of resources*, *protection of ecosystems,* and new forms of "clean" energy as renewable sources of energy in order to deal with *climate change* and ensure *energy autonomy*. All the policies must be fully compatible with the *Sustainable Development Goals of the United Nations* in order to effectively deal with the challenges of the Industry 4.0 and ensure a sustainable economic growth.

Finally, the case study of Greece is set under consideration in this paper. Greece does not belong to the heavy industrial economies of Europe, but it has a more people-focused labor market. Greece has the fourth lowest rate of exposure to the automation risk (about 24%) among other economies worldwide, with men being more exposed to the risk of automation than women mainly because of the nature of the tasks they undertake that is easier to be automated, for example, manual works. According to the results, the highest rate of exposure is observed for middle-aged people who have medium educational level. 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 and the fact that the tasks of medium-educated employees can be easily replaced by artificial intelligence offer an explanation for this result. The industry that appears to be most exposed to automation in Greece is the manufacturing sector. Humanitarian activities such as care services, education, and teaching that require high social, cognitive, and communication skills exhibit low rates of exposure to automation; especially the rate of exposure to the automation risk of the educational sector is lower than the average of all countries worldwide, emphasizing the anthropocentric nature of the Greek educational system that makes difficult the total replacement of human factor by machines and robots in the long run.
