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Employment and Social Developments in Europe 2014
and learning resources that are available of which are performed by unskilled and level of professional competence, usu-
globally and often at a fraction of the semiskilled industrial and clerical service ally combined with a long and versatile
cost. Digital applications have shown the workers who typically occupy the middle formal education (e.g. computer pro-
ability to compete with and potentially layers of employment. Some studies strike grammers, creative industries, engi-
undermine various traditional service pro - an alarmist tone and argue that the pro- neers, managers, investment bankers,
viders such as taxis or hotels (e.g. ride- cess has only just begun. Frey and Osborne lawyers, doctors, teachers and scien-
sharing app ‘Uber’ or ‘AirBnb’ flat rental (2013) predict that 47 % of current jobs in tists). Europe has great stakes in devel-
and sharing). Computerisation, typically advanced economies like the United States oping the knowledge-based economy,
confined to manual and cognitive routine are at risk of being automated over the investing in high-end skills and assuring
tasks, is now spreading to activities that next 20 years. optimum job conditions for knowledge
were commonly defined as non-routine workers. Compared with low-skilled
(e.g. Autor and Dorn, 2013; Goos et al., Further technological change is therefore workers, knowledge workers already
2009). Tasks regarded as non-routine only expected to have a strong and polarising enjoy a more privileged position on
a decade ago have since been computer- effect, affecting jobs and skill levels in the labour market, with more favour-
ised at a rapid pace (Autor, et al., 2003; a different manner (see below). In this able working conditions and a higher
Markoff, 2011; Frey and Osbourne, 2013). context, managing the transition into pay. Yet, the knowledge sector is where
Recent examples of how the boundary a new labour market where many jobs the highest potential for productivity
between routine and non-routine tasks succumb to automation must become growth is likely to lie. Hence, a focus on
and between automatable and non- a key priority for policymakers. more efficient working arrangements
automatable routines will be pushed fur- will be key to securing Europe’s position
ther by technology include handwriting 4.1.2. Occupations resilient as a hotspot of high productivity.
recognition, machine translation and the to automation: the importance
use of language analysis to identify gen- of knowledge and creativity 4.1.3. Technology change can
56
eral concepts in documents ( ). (human capital) in view of lead to a possible industrial
technology change renaissance in the EU
Authors speculate about the scale of
the challenge ahead if new technologies The non-routine jobs that are likely to In the recent past, increasing job losses
mature and spread beyond prototypical resist automation in the foreseeable and the rise in job uncertainty have
and experimental applications: self- future are located at either the lower or affected job quality, particularly in
driving vehicles, health diagnostics, auto- higher end of the wage and skill spec- industry. For example, the employment
mated call centres and robot-assisted trum. At the lower end, there are ser- share of the industry sector in the EU as
remote surgery are some examples. The vices such as hospitality, care, beauty, a whole dropped from 22.1 % in 2000 to
impact may spread to related sectors. cleaning, customer service, construction, 17.7 % in 2013. At the same time, jobs in
For example, self-driving vehicles can decorating and installation. These may industry typically offer a high wage level
reduce drivers’ jobs and, if safer, reduce be subjected to some vocational training (compared with the national average
business opportunities in the insur- and licensing in particular legal settings wage): average gross wages in industry
ance sector. but require soft skills such as empathy, were 10.6 % above the national average
improvisation and complex decision mak - gross wage in the EU. The drop in industry
In some sectors, there are already pal- ing. Further, they feature complex man- shares and high wages are a combined
pable signs of rising automation in work ual tasks which in turn rely on specific effect of: a) strong productivity growth in
spaces such as container ports, logistics skills and experience. These jobs are not industry; b) the opening of world markets
warehouses or even hospitals (e.g. robots suited to outsourcing since they have to and changing business models, whereby
pulling trolleys with meals, medicines and be performed on-site. manufacturers outsource certain tasks
blood samples in hospitals (Bloss, 2011) (such as logistics, marketing or legal
or climbing wind turbines much faster Despite their undisputed social utility, advice); and c) a shortage of skilled
than a human and inspecting the blades such non-routine, manual, low- to
human capital in engineering and sci-
100 metres above ground (Robotics-VO, medium-skilled jobs often offer mod - ence which may have been aggravated
2013)). est remuneration with precarious job by the recent crisis that stifled access
arrangements and physically demand- to funds for innovation (e.g. European
While intellectual and knowledge work ing working conditions. Likely reasons for Commission, 2013).
(e.g. computer programming) is flourishing this are the abundant labour supply, the
and craftsmanship-based manual trades possibility of using underpaid migrant A variety of policy measures have been
remain in high demand, many middle-class workers and, in some cases, the threat to implemented to temper the adverse
occupations, typical of the industrialised relocate some part of these tasks to low- socioeconomic impact of delocalisation
th
57
societies of the latter half of the 20 wage countries (Standing, 2011). In this and offshoring (e.g. Eurofound s.a.)( ).
century, are being eroded. Programma - context, there is clearly a need to step up These initiatives have primarily been
ble machines are expected to take over efforts to improve the working conditions used to accommodate the ongoing job
many routine and less routine tasks, many in these jobs and to ensure the applica- shift from industrial activities to other
tion of existing worker protection laws.
( ) For instance, Symantec’s Clearwell ( ) At http://www.eurofound.europa.eu/areas/
57
56
system proved to be capable of analysing At the high end of non-routine and non- industrialrelations/dictionary/definitions/
(conceptual contents, not just words) and automatable jobs are those consisting restructuring.htm http://www.eurofound.
sorting more than 570 000 documents in europa.eu/areas/industrialrelations/
two days. of complex cognitive tasks and a high dictionary/definitions/restructuring.htm
150
and learning resources that are available of which are performed by unskilled and level of professional competence, usu-
globally and often at a fraction of the semiskilled industrial and clerical service ally combined with a long and versatile
cost. Digital applications have shown the workers who typically occupy the middle formal education (e.g. computer pro-
ability to compete with and potentially layers of employment. Some studies strike grammers, creative industries, engi-
undermine various traditional service pro - an alarmist tone and argue that the pro- neers, managers, investment bankers,
viders such as taxis or hotels (e.g. ride- cess has only just begun. Frey and Osborne lawyers, doctors, teachers and scien-
sharing app ‘Uber’ or ‘AirBnb’ flat rental (2013) predict that 47 % of current jobs in tists). Europe has great stakes in devel-
and sharing). Computerisation, typically advanced economies like the United States oping the knowledge-based economy,
confined to manual and cognitive routine are at risk of being automated over the investing in high-end skills and assuring
tasks, is now spreading to activities that next 20 years. optimum job conditions for knowledge
were commonly defined as non-routine workers. Compared with low-skilled
(e.g. Autor and Dorn, 2013; Goos et al., Further technological change is therefore workers, knowledge workers already
2009). Tasks regarded as non-routine only expected to have a strong and polarising enjoy a more privileged position on
a decade ago have since been computer- effect, affecting jobs and skill levels in the labour market, with more favour-
ised at a rapid pace (Autor, et al., 2003; a different manner (see below). In this able working conditions and a higher
Markoff, 2011; Frey and Osbourne, 2013). context, managing the transition into pay. Yet, the knowledge sector is where
Recent examples of how the boundary a new labour market where many jobs the highest potential for productivity
between routine and non-routine tasks succumb to automation must become growth is likely to lie. Hence, a focus on
and between automatable and non- a key priority for policymakers. more efficient working arrangements
automatable routines will be pushed fur- will be key to securing Europe’s position
ther by technology include handwriting 4.1.2. Occupations resilient as a hotspot of high productivity.
recognition, machine translation and the to automation: the importance
use of language analysis to identify gen- of knowledge and creativity 4.1.3. Technology change can
56
eral concepts in documents ( ). (human capital) in view of lead to a possible industrial
technology change renaissance in the EU
Authors speculate about the scale of
the challenge ahead if new technologies The non-routine jobs that are likely to In the recent past, increasing job losses
mature and spread beyond prototypical resist automation in the foreseeable and the rise in job uncertainty have
and experimental applications: self- future are located at either the lower or affected job quality, particularly in
driving vehicles, health diagnostics, auto- higher end of the wage and skill spec- industry. For example, the employment
mated call centres and robot-assisted trum. At the lower end, there are ser- share of the industry sector in the EU as
remote surgery are some examples. The vices such as hospitality, care, beauty, a whole dropped from 22.1 % in 2000 to
impact may spread to related sectors. cleaning, customer service, construction, 17.7 % in 2013. At the same time, jobs in
For example, self-driving vehicles can decorating and installation. These may industry typically offer a high wage level
reduce drivers’ jobs and, if safer, reduce be subjected to some vocational training (compared with the national average
business opportunities in the insur- and licensing in particular legal settings wage): average gross wages in industry
ance sector. but require soft skills such as empathy, were 10.6 % above the national average
improvisation and complex decision mak - gross wage in the EU. The drop in industry
In some sectors, there are already pal- ing. Further, they feature complex man- shares and high wages are a combined
pable signs of rising automation in work ual tasks which in turn rely on specific effect of: a) strong productivity growth in
spaces such as container ports, logistics skills and experience. These jobs are not industry; b) the opening of world markets
warehouses or even hospitals (e.g. robots suited to outsourcing since they have to and changing business models, whereby
pulling trolleys with meals, medicines and be performed on-site. manufacturers outsource certain tasks
blood samples in hospitals (Bloss, 2011) (such as logistics, marketing or legal
or climbing wind turbines much faster Despite their undisputed social utility, advice); and c) a shortage of skilled
than a human and inspecting the blades such non-routine, manual, low- to
human capital in engineering and sci-
100 metres above ground (Robotics-VO, medium-skilled jobs often offer mod - ence which may have been aggravated
2013)). est remuneration with precarious job by the recent crisis that stifled access
arrangements and physically demand- to funds for innovation (e.g. European
While intellectual and knowledge work ing working conditions. Likely reasons for Commission, 2013).
(e.g. computer programming) is flourishing this are the abundant labour supply, the
and craftsmanship-based manual trades possibility of using underpaid migrant A variety of policy measures have been
remain in high demand, many middle-class workers and, in some cases, the threat to implemented to temper the adverse
occupations, typical of the industrialised relocate some part of these tasks to low- socioeconomic impact of delocalisation
th
57
societies of the latter half of the 20 wage countries (Standing, 2011). In this and offshoring (e.g. Eurofound s.a.)( ).
century, are being eroded. Programma - context, there is clearly a need to step up These initiatives have primarily been
ble machines are expected to take over efforts to improve the working conditions used to accommodate the ongoing job
many routine and less routine tasks, many in these jobs and to ensure the applica- shift from industrial activities to other
tion of existing worker protection laws.
( ) For instance, Symantec’s Clearwell ( ) At http://www.eurofound.europa.eu/areas/
57
56
system proved to be capable of analysing At the high end of non-routine and non- industrialrelations/dictionary/definitions/
(conceptual contents, not just words) and automatable jobs are those consisting restructuring.htm http://www.eurofound.
sorting more than 570 000 documents in europa.eu/areas/industrialrelations/
two days. of complex cognitive tasks and a high dictionary/definitions/restructuring.htm
150
