Industry 4.0

1. A Review of the Impact of the
Fourth Industrial Revolution on
Employment
23 October 2018

2. Background and timeline of industrial
revolution
 Over the years there have been distinct transitional changes that have
caused shifts in the speed, quality and organisation of production,
 Each transition had its unique contribution to the contemporary world we
live in today,
 These transitions were driven by the industrial revolution,
 Industrial revolution implied a growth rate increase in industrial production
(Mathias, 2013:12),
 To date, the world had seen three waves of industrial revolution before the
4th Industrial Revolution:
First Industrial Revolution (1784)
• Late 18th Century and early 19th Century
• Characterized by Industrialisation
• Use of water and steam to mechanise production
• Advancement to the use of steam engine
The first industrial revolution shifted the production from a previously labour
intensive to a more capital intensive.

3. Background and timeline of industrial
revolution
Second Industrial Revolution (1870)
• Use of electricity for mass production
• Electricity, combustion engine, steel, chemical synthesis, large factories,
assembly lines
Generally, the second industrial revolution can be broadly characterised by
expansion of industries and electrically-powered mass production based on the
division of labour.
Third Industrial Revolution (1969)
• ‘Digital revolution’
• Use of electronics and ICT to automate production
• ICT, internet and computers
While the third industrial revolution is an era of rapid technological progress
associated with the development of information technology. It is in this era that
electronics and information technology was used to further advance
automation.

4. Fourth Industrial Revolution- What is it??
Fourth Industrial Revolution (Era of Cyber-Physical Systems)
 The fourth industrial revolution is often referred to as Revolution 4.0),
 The term was apparently first used in 2016 by World Economic Forum
(Klaus Schwab),
 Dramatic change in pace and scope of automation of tasks previously done
by humans,
 Blurring of boundaries between the physical, biological and digital spheres,
 Robotics; Artificial Intelligence (AI); Internet of Things (IoT) and Industrial
Internet of Things (IIoT); cyber-physical systems; augmented reality (AR);
virtual reality (VR); biotechnology; nanotechnology; autonomous vehicles;
cloud computing; 3D printing…
 Its International diffusion is exponentially faster than earlier industrial
revolutions,
 “Estimates of how many jobs are vulnerable to being replaced by machine
vary but it is clear that developing countries are more susceptible to
automation as compared to high-income countries.” (Millington, 2017),

5. How Fourth Industrial Revolution is likely to
Affect Employment
 The effect comes in multiple channels:
– Overall number of jobs
– Composition of employment (by skills level, by occupation, by sector
etc.) with certain types of jobs more vulnerable than others,
– Nature of work, work processes and the workplace
 Impact on total employment
– Mass technological unemployment,
– Job displacement/destruction and job creation (generally for different
people),
 Largenet negative impact for developing economies due to skills
availability
– Effect on incomes and quality of life depends on what happens to
‘surplus’,
– Likely rise of inequality,

6. Which jobs most likely to be affected
 The impact depends on degree of automatability–how routine and
codifiableare tasks,
 Overall, lower-skilled jobs are more vulnerable than high-skilled, but not
straight correlation,
 This is one difference from previous types of automation –some white-collar
jobs now more vulnerable than some blue-collar jobs,
 Less vulnerable jobs are those involving creativity, social interaction, high
levels of dexterity, lot of variation amongst tasks,
 According to the NDP (2030) RSA is creating more jobs in the services
industry such as Private Security and these are at more risk to be replaced
by R4.0,
 R4.0, has the potential to compromise achievements towards Goal 8 of the
Sustainable Development Goals on decent work and economic growth aims
to “promote sustained, inclusive and sustained economic growth, full and
productive employment and decent work for all”.

7. Which jobs most likely to be affected
 Technological innovation has been identified as one of the primary drivers
behind unemployment rates,
 Typists, cashiers and telephone operators are jobs that have already been
partially replaced by technology,
 Pace of technological innovation increasing rapidly, making redundancies
more likely in the future,
 Tasks that were previously thought not to be codifiable (e.g. driving) have
been successfully codified,
 Computers ideally suited to routine, manual tasks and can play an assistive
role for non-routine, cognitive tasks (Autor et al., 2013),
 In the 1960s in the USA, significant shifts in labour demand from routine to
non-routine jobs,
 Frey and Osbourne (2017) argue that the scope of automation has
increased rapidly due developments in machine learning and mobile
robotics,
 They find that 47% of US jobs are at risk of automation.

8. Which jobs most likely to be affected
 Rooney (2017) used the methodology adopted by Frey and Osbourne
(2017) to assess the impact of R4.0 on employment in RSA,
 Frey and Osbourne state that with recent technological innovations, almost
every task is (or will be) codifiable, except for what are termed ‘engineering
bottlenecks’,
 These bottlenecks do not have clearly identifiable rules and therefore it is
difficult to develop a computer algorithm for them,
 Frey and Osbourne computed an automation probability for every
occupation and divide occupations into groups which are at ‘low risk’,
‘medium risk’ and ‘high risk’ of automation based on that occupations
automation probability
–Low Risk: Automation probability of between 0.0 and 0.3
–Medium Risk: Automation probability of between 0.3 and 0.7
–High Risk: An automation probability of greater than 0.7

9. Which jobs most likely to be affected
 Rooney (2017) used the Labour Market Dynamics Study (LMDS) 2015 and
Quarterly Labour Force Survey amongst different data sets to simulate an
analysis of the impact of R4.0 on employment in South Africa.
 Criteria of selecting the sample for their simulation included–
–Employee
–Formal Sector
–Matching occupational code between SASCO and ISCO-08
–Associated probability with an occupation (one exception was for
‘sweeper and manual labourers’ due to the large number of individuals (865
000) in this role.)
–Total sample size was 10.2 million from the LMDS (from an original
sample size of 11.1 million formal sector employees).

10. Impact of R4.0 By Rooney (2017)

11. Impact of R4.0 By Rooney (2017)
Race
African
M 15.68
H 45.98
L 38.35
Coloured
M 17.19
H 37.85
L 44.95
Indian
M 29.68
H 29.86
L 40.46
White
M 41.77
H 27.39
L 30.83
Gender
Male
M 16.44
H 49.61
L 33.95
Female
M 24.94
H 31.39
L 43.67

12. Impact of R4.0 By Rooney (2017)
Age
15-24 years
M 9.66
H 43.24
L 47.1
25-34 years
M 15.22
H 44.1
L 40.67
35-44 years
M 21.41
H 42.98
L 35.61
45-54 years
M 27.27
H 38.07
L 34.65
55-64 years
M 28.22
H 36.08
L 35.7
65+ years
M 37.72
H 30.03
L 32.24
Province Province
Western Cape North West
M 20.66 M 13.5
H 39.63 H 52.78
L 39.71 L 33.72
Eastern Cape Gauteng
M 22.3 M 21.64
H 35.15 H 40.98
L 42.55 L 37.38
Northern Cape Mpumalanga
M 16.23 M 17.9
H 42.84 H 46.37
L 40.93 L 35.73
Free State Limpopo
M 17.62 M 21.9
H 42.68 H 44.68
L 39.7 L 33.42
KwaZulu-Natal
M 19.04
H 41.31
L 39.65

13. Impact of R4.0 By Rooney (2017)
Industry Industry
Agriculture forestry and fishing Wholesale and retail trade
L 8.47 L 9.69
M 37.38 M 45.29
H 54.15 H 45.02
Mining and quarrying Transport, storage and communication
L 4.73 L 8.29
M 78.72 M 60.17
H 16.55 H 31.53
Manufacturing Financial and business services
L 8.33 L 17.75
M 45.25 M 52.79
H 46.42 H 29.46
Electricity, gas and water Community, social and personal (CSP) services
L 14.51 L 44.84
M 55.2 M 24.8
H 30.29 H 30.36
Construction
L 5.86
M 30.41
H 63.73

14. Impact of R4.0 By Rooney (2017)
The study found Top High Risk Employment located in (in the order of highest
to high:
 Community, social and personal (CSP) services
 Wholesale and retail trade
 Manufacturing
 Construction
 Finance

15. Implication for Workers’ Unionization
The impact of R 4.0. on employment is evident in industries that absorbs most
of the semi-skilled and unskilled workers in South Africa:
 CSP services
Classification Minor Code
Public administration and defence activities 91
Education 92
Health and social work 93
Other community, social and personal service
activities
94
Activities of membership organisations not
elsewhere classified
95
Recreational, cultural and sporting activities 96
Other 99

16. Implication for Workers’ Unionization
The impact of R 4.0. on employment is evident in industries that absorbs most
of the semi-skilled and unskilled workers in South Africa:
 Wholesale and retail trade (unskilled and semi skilled)
 Manufacturing (unskilled and semi skilled)
 Construction (unskilled and semi skilled)
 Finance (more skilled workforce)
These sectors, with the exception of Finance, are mostly dominated by workers
who need voice representation, mostly vulnerable and the impact of R 4.0 is
directly destroying their opportunities for employment.
Furthermore, R 4.0 has potential impact on inequality and unemployment:
“The National Minimum Wage poses the risk of a steep increase in labour
costs. As a result this manufacturer is looking into increasing automation to
increase the efficiency of current production, whilst saving on labour costs. The
intention is to increase the bottom line so that steep increases in wage do not
lead to workers being let go.”
Trade unions therefore find relevance but for a significant low coverage of
workers post the dawn of 4th industrialization.

17. Concluding remarks and recommendations
 80% of jobs are at high or medium risk of being automated,
 Females, coloureds, young people (15 –24) and those with no education
are most at risk of seeing their jobs automated,
 Absolute job losses (total number of job losses) are likely to be highest in
CSP services, wholesale and retail trade and construction,
 Relative job losses (percentage of total employment) are likely to be
highest in construction, agriculture and manufacturing,
 R 4.0 brings with it uncertainty and anxiety in the labour market,
 Previous industrial revolutions saw displacement of labour due to
technological advancement,
 There is a need to incorporate robotics in the work environment, particularly
harmful environment and to improve productivity in order to be prepared to
benefit from R 4.0, the question is “are we ready for the coming production
and service changes?”

18. Concluding remarks and recommendations
 Employment outcomes are not cast in stone –policy can influence the situation
to some extent,
 The less prepared and proactive a country is, the higher job losses likely to be
• Direct due to changing nature of domestic production
• Indirect due to loss of international market shares
 Policy focus should be on
• Minimising job losses, and
• Reskilling workers in vulnerable jobs.

19. Thank You…
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