The Impacts of Automation on Employment in the Service Sector in Germany

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The Impacts of Automation on Employment in the Service Sector in Germany by Mind Map: The Impacts of Automation on Employment in the Service Sector in Germany

1. have its

1.1. Background

1.1.1. based on earlier research from

1.1.1.1. Dauth et al. (2017)

1.1.1.2. Saviotti et al. (2018)

1.1.1.3. World Bank (2019)

1.1.2. in technological advancement in industrial automation, which aims to widen profit margins through

1.1.2.1. Deploying an exponentially growing number of robots

1.1.2.1.1. that guarantees greater precision and sustains quality at possible price premiums

1.1.2.2. Substituting human jobs or activities

1.1.2.2.1. to reduce labor costs

2. center around the current situation that

2.1. + Automation has not led to rising unemployment in Germany

2.1.1. , as the service jobs created by industrial automation offset those in manufacturing

2.2. - Service occupations are also becoming codifiable and, hence, replaceable by more advanced robots

2.2.1. , consequently challenging the workforce to be well-equipped for the quaternary sector and new occupations that work with robots

2.3. + GDP growth rates has increased steadily

2.3.1. through the boosted productivity of industrial robots

2.4. - Earnings are drastically shifting from workers to owners of capital and other resources invested in automation

2.4.1. , leading to a shrinking income share of labor despite the promising growth of national aggregate income

3. should be critically analyzed on the

3.1. National Aggregate Level

3.1.1. which concerns

3.1.1.1. Structural unemployment

3.1.1.1.1. defined as

3.1.1.2. Greater income disparity

3.1.1.2.1. defined as

3.2. Individual Level

3.2.1. which faces

3.2.1.1. Adaptation to the inevitable changing nature of service jobs

3.2.1.1.1. meaning

4. should further suggest countermeasures for

4.1. Government Authorities

4.1.1. such as

4.1.1.1. taxing robots that replace human jobs

4.1.1.1.1. , which could help accumulate funds to provide social welfare for workers vulnerable to industrial automation

4.1.1.2. extending labor law protections beyond standard workers

4.1.1.2.1. , which prevents the government from punishing non-standard workers, e.g. those who work freelance and those who switch or interrupt their careers

4.2. Current Workforce

4.2.1. in adult training for an automated service sector

4.3. Potential Workforce

4.3.1. in investing in education that helps build up appropriate human capital