The Robot Economy and Its Impact on Employment and National Productivity

An economy where robots gain more employment that human labour is known as “robot economy”. The robot economy is being seen as the second wave of automation. The “robot economy” is expected to take over the world and it is suggested that there will be consequences in the form of technological innovation – a term coined to describe the possible trend of unemployment due to replacement of human labour in workplaces by automation. On the other hand, it is also expected that automation will help improve productivity, especially in the services sector since routine tasks in the workplace can be automated, leaving the workforce to dedicate more time to focus on the abstract, cognitive parts of the work. This is known as the Robot Economy Paradox.

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Contents
Introduction.................................................................................................................................................4
The Robot Economy....................................................................................................................................5
Understanding automation and Robot Economy....................................................................................5
The Impact of the New, Technology based economy on employment and national productivity...........7
Conclusion.................................................................................................................................................10
Australian Economy and the Technological Paradox.............................................................................10
Recommendations.................................................................................................................................12
References.................................................................................................................................................12

Executive Summary
An economy where robots gain more employment that human labour is known as “robot economy”.
The robot economy is being seen as the second wave of automation. The “robot economy” is expected
to take over the world and it is suggested that there will be consequences in the form of technological
innovation – a term coined to describe the possible trend of unemployment due to replacement of
human labour in workplaces by automation. On the other hand, it is also expected that automation will
help improve productivity, especially in the services sector since routine tasks in the workplace can be
automated, leaving the workforce to dedicate more time to focus on the abstract, cognitive parts of the
work. This is known as the Robot Economy Paradox.
The impact of the robot economy is uncertain. It is possible that it may cause more unemployment. It is
also, possible that a robot economy will enhance the knowledge economy, by improving the
productivity of the tertiary sector. This may spur a new wave of innovation and creativity leading to a
creative economy. Research so far suggests that Australia is relatively insulated to the negative effects
of the robot economy. The report provides an explanation of the linkages between a robot economy,
employment and creative economy. The study also provides some recommendations on how to cope up
with the robot economy.

Introduction
Automation has created a virtual, autonomous economy, this giving a automation anxiety to
everyone in the world (Arthur, 2011). There is plenty of uncertainty regarding the direction of
the world, given the rapid increase in automation in various economic spheres. These automation
changes relate to primary and basic tasks and processes such as serving water in a restaurant to
highly skilled ones such as performing highly complicated surgeries. The uncertainty relates to
various aspects of the economy but is more pronounced with regards to unemployment. It is
expected that automation and the robot economy with structurally change economics as we know
it. However, the nature of these structural changes is where a large part of the uncertainty exists.
(Bakhshi, Downing, Osborne, & Schneider, 2017)Various reports (elaborated in this report
further) and data analyses suggest that there will be a loss of employment opportunities in the
future while some analyses suggest that there automation and robotics may add to the
productivity of human labour, especially in the services sector. The nature of impact that the
robot economy would have on an economy depend on the nature of the economy of the country
itself. (Bakhshi, Downing, Osborne, & Schneider, 2017). The new economy thus, would need a
variety of new policy interventions.
This report provides a background to the beginnings of robot economy and the idea of
technology unemployment provided by Keynes in 1930. Further, a two way classification of
tasks and processes in the workforce is explained to explain which area of employment
opportunities are going to shrink in the future. The robot economy is not just expected to reduce
employment opportunities but also, create them. This report also briefly discusses the new
employment economy opportunities that may arise in the new. The report contains a descriptive
explanation of robot economy and technological unemployment. Furthermore, some basic
recommendations are provided to ensure to ensure that Australia is able to resolve the paradox
and exploits all the opportunities that the new economy makes available.

The Robot Economy
Understanding automation and Robot Economy
In 1930, Keynes warned the world of a future where technology will become important as
economies tries to optimize their costs. In the process, jobs that were traditionally done by
labourers would be performed by technology since technology is more efficient. Keynes warned
that the world was following the general trend of finding more ways to replace labour with
machines, instead of finding ways to use labour and called the term “ technological
unemployment”. According to Keynes, the efficiency of technology would increase production
and the problem of production would be resolves. In the modern context, machines can be
replaced by robots, which are more sophisticated robots. The automation of production processes
is happening at such a fast pace, that the world id now said be suffering from. (Keynes, 1963)
Automation is also highly likely to increase inequality and this presents a need for governments
to intervene with policy. Keynes predicted that the average work week would shorten, life
expectancy would increase and the economy would move towards a much larger. Keynes, also,
predicted that inequality would increase since workers would no longer be indispensible. For
example, since workers’ bargaining power has decreased, it would present a disincentive to raise
minimum wage. (Keynes, 1963)
Figure 1 Robot Economy and Singularity Jobs
Source: (Pol & O’Brien, 2018)

Ford (2014) has predicted that the importance of robots will rise in the economy and will peak when
super-intelligence is achieved: a class of robots that can create robots based on the knowlegde received.
Thus, there will be economic singularity which will result in robots taking over the jobs of humans. Based
on this Pol & O’Brien, (2018) have given athe above representation. According to the The authors have
explain how humans are economically superfluous with limits to their ability to produce and consume
goods. The blue curve at rate h(t) is the curve that plots technological innovation and the red curve plots
the robot economy. The authors believe that the two will converge ultimately at the point of economic
singularity. Pol & O’Brien, (2018) defined a robot economy as “to an economy in which technological
unemployment is increasing and the number of jobs taken by robots is greater than the number of jobs
taken by humans as a robot economy.” Earlier, Reveley & Pol, (2017) had highlighted the need for coping
mechanisms that would help stop this convergence. If attempts are made to augment labour by
inproving their skills and knowledge , then the point of convergence may not be realized and the
technological employment may disappear.
A robot economy will typically have the following components:
Figure 2 Components of a Robot Economy
Robot
Economy
Automation
Artificial
Intelligence
Robotics

Source: Prepared by Author
Automation refers to the replacement of routine, low skilled jobs by more efficient machines.
Automation in the current environment is past the primitive stages where machines replaced
simple human tasks such as those of a teller. Automation, today has morphed into a much more
complex system. With the help of 3-D printing, it would be possible to manufacture high quality
goods, much faster. The flexibility of 3-D printing allows for manufacturing of whole range of
products at any geographical location. (Frey & Osborne, 2013). Additionally, the current phase
of automation also, involves the automation of several cognitive processes and tasks.
(Brynjolfsson & McAfee, 2014)
Robotics are. especially useful in critical processes where human error can have large collateral.
Robotics can, effectively reduce the need for medical assistants. Air Traffic control is another
area of employment where robots are preferable to human watchmen. (Arthur, 2011)
Artificial Intelligence, is being increasingly used to obtain deep knowledge. Artificial
intelligence can use data and virtual neural networks which contributed\s to knowledge building
and efficiency of every industry. For example, Artificial Intelligence can be used to predict the
high risk patients on various parameters and thus, help in increasing the efficiency of treatment
by a doctor. (Pearl, 2018).
The Impact of the New, Technology based economy on employment and
national productivity
Automation and robotics can have different impacts on different sectors of the job. On one hand,
robotics and automation can help conduct the routine, mundane jobs with higher precision and
reduce human error. On the other hand, robotics and automation can have adverse effects on the
economy and may lead to unemployment. In any commercial establishment, jobs can be
categorized a routine, unskilled jobs and the abstract creative jobs. The routine mundane tasks
are susceptible to human error and generally, offer lower wages. For example, a factory worker
involved in packaging of products has a low skilled routine job. An example of a automation
taking over such jobs is the Automatic Teller Machine or the ATM. (The Economist Intelligence
Unit, 2018) ATMs have not only replaced humans but have changed the way cash from banks

are deposited. ATMs have made it possible for customers of any bank to withdraw from their
deposits any anytime they wish. Additionally, it is possible for customers to withdraw their cash
from their preferred locations instead of going to the bank. Skilled and creative jobs require
plenty of cognitive skills such as interpretation and analysis. These jobs, typically pay higher
wages since they rely on knowledge. (Frey & Osborne, 2013) These jobs create, what is called a
knowledge economy. (Samuelson & Nordhaus, 2006) According to a study by Frey & Osborne,
(2013), 47% of the low skilled jobs in USA are susceptible to the negative effects of the
onslaught of the robot economy while the typically, highly skilled jobs that require tertiary
education will be able to cope up with the changes in the economy.
According to Borland & Coelli, (2017) the Australian economy has been reasonably insulated
from the effects of the downturn of such jobs. The “total amount of work” has not seen a
decrease in Australia due to the introduction of automative technology. Additionally, the authors
have have observed no structural changes to the economy due to a rise in computer applications
based work. It is noteworth that Australian economy is not an economy that is very highly
dependent on manufacturing jobs such as automobile manufacturing.
According to (Bakhshi, Downing, Osborne, & Schneider, 2017), roughly 10 percent of the work
force is engaged in areas of work that are likely to experience growth in the future, while
approximately 20% of the workforce is engaged in job positions of which the demand is likely to
shrink in the future. The remaining 70 % of the work force is engaged in work areas that face
dynamic uncertainty. There is little clarity regarding the effects of a changing economy on these
jobs. There is a lot of uncertainty regarding the nature of the change that automation, robotics
and artificial intelligence will bring in work. (Serebrenny, Shereuzhev, & Metasov, 2018)
In general, some of the sector s that are expected to grow in developed countries are education,
healthcare and public sector occupation. With some exceptions in the public sector, these
occupations are labour and knowledge intensive requiring tertiary education. (Bakhshi,
Downing, Osborne, & Schneider, 2017) It is expected that manufacturing and mid-level jobs will
be lower in the future. (Bakhshi, Downing, Osborne, & Schneider, 2017)
By and large, it has been observed that the jobs that are at the verge of displacement due to
automation are jobs that do not require high cognitive skills or education. These are highly

routine mundane jobs. For example, self driving cars can replace drivers. (Bakhshi, Downing,
Osborne, & Schneider, 2017) Robotics can be used to carry out mundane agricultural tasks with
higher precision which has the potential reduce the costs of labour associated with agriculture.
(Serebrenny, Shereuzhev, & Metasov, 2018) Several standardized processes in the
manufacturing sector can be performed by robots.
Smart and self learning can not only do perform their tasks but also, build their own knowledge
and become more intuitive. Thus, they will be able to perform some repetitive jobs even in the
skilled industry. (The Economist Intelligence Unit, 2018) For example, computers can be coded
to publish syndicated articles with basic information, thereby replacing journalists.
The average productivity of the services industry, although, could stand to gain from the
automation of jobs. According to EIU, the assistance on artificial intelligence can help boost the
productivity of the medical sector in the UK.
The parts of the labour market most exposed to automation have the characteristic of being
highly routine, such as truck driving in modern society, or a factory worker in the Industrial Age.
1979-01-01
1982-06-01
1985-11-01
1989-04-01
1992-09-01
1996-02-01
1999-07-01
2002-12-01
2006-05-01
2009-10-01
2013-03-01
2016-08-01
280
290
300
310
320
330
340
350
360
Weekly Real Wages in USA since
1979
Weekly Real Eages
Wages (in adjusted US Dollars)
Graph 1 Weekly Real Earnings in USA since 1979
Source (Board of Governors of the Federal Reserve System, 2018)

According to Keynes’s analysis, as mentioned earlier, real wages of the economy may suffer
since a greater share of workplace productivity may come from the technologically. This creates
friction against worker earnings as entrepreneurs are more likely to invest in technological up
gradation than in providing higher wages to workers. The graph above depicts the weekly real
earnings in USA since 1970. real earnings of workers has increased by less than 15% since
1970s. Since 1970s, a vast variety of human processes have been automated. For example,
manufacturing and automobile jobs have experienced a steady decline due to automation.
(Bakhshi, Downing, Osborne, & Schneider, 2017)
Conclusion
Australian Economy and the Technological Paradox
Economies are dynamic and their structures keep changing with time. The industrial revolution reduced
the demand for artisanal goods and created more employment for people as factory workers. This
created a whole new working class. Similarly, the current revolution expected due to the robot economy
will create new jobs and wipe out some old ones. This paradox of a robot economy.
Sep-1986
Jun-1989
Mar-1992
Dec-1994
Sep-1997
Jun-2000
Mar-2003
Dec-2005
Sep-2008
Jun-2011
Mar-2014
Dec-2016
-4.0
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Australia's Per Hour Labour
Productivity (Non Farm) growth since
1986
Australia's Per Hour
Labour Productivity (Non
Farm) growth since 1986
Graph 2 Per Hour Labour Productivity (non Farm) growth of Australia
Source: (Reserve Bank of Australia, 2018)

Sep-1985
Aug-1987
Jul-1989
Jun-1991
May-1993
Apr-1995
Mar-1997
Feb-1999
Jan-2001
Dec-2002
Nov-2004
Oct-2006
Sep-2008
Aug-2010
Jul-2012
Jun-2014
May-2016
Apr-2018
0.0
20.0
40.0
60.0
80.0
100.0
120.0
Australia's Per Hour Labour Productivity (non
Farm)Index since 1985
Australia's Per Hour Labour
Productivity since 1985
Graph 3 Australia's Per Hour Labour Productivity
Source: (Reserve Bank of Australia, 2018)
As seen above, Australia’s labour productivity in the non farm sectors has been increasing since
1980. Since 1980, the index has grown by two thirds but has stagnated in the recent times. In the
graph on Labour productivity growth in non farm sectors per hour, there is a lot of volatility. In
the recent years, it has declined, experiencing negative growth rates from the base. This presents
a case for further investment in the human capital since the two graphs above can help reach the
conclusion that technology may have had a greater share in increasing productivity at work than
improvement in skills and efficiency of human labour. However, according to (Organization for
Economic Co-operation and Development, (2017) Australia’s stagnant progress has a variety of
adverse consequences. Real wages are expected to remain stagnant in Australia, if the
productivity does not improve. Additionally, inequality is on the rise and “inclusiveness is being
eroded”. As mentioned above, the share of technology could have had a greater role in
increasing the overall productivity of labour. Typically, technological advances originate in the
urban areas and are at the forefront of the adoption of technology while rural areas tend to be at
the bottom rung if the adoption of technology. Hence, this may widen the gap between growth in
urban and rural areas(which have a higher density of Australia’s native people).

Recommendations
It is important that the Australian government prioritizes coping mechanisms in a robot economy. (Pol &
O’Brien, 2018)The following are a few recommendations that have also been endorsed by previous
research..
The OECD recommended that Australian government increase investment in building resources
towards more invest in non- Science Technology Engineering and Mathematical subjects.
According to recommendations of neo-classical theory, countries that are in high stages of
development should pursue growth in knowledge and innovation sectors. (Organization for
Economic Co-operation and Development, 2017)
Additionally, the OECD also recommended that the Australian Government takes measures to
increase access to information and communication technology. (Organization for Economic Co-
operation and Development, 2017)
Plenty of technological research and innovation does not have productive effects simply due to
lack of connecting linkages from between research and businesses. In order to maximize the
effect of technological innovations, there is a need to improve the linkages between business and
non-commercial research facilities. (Organization for Economic Co-operation and Development,
2017)
It is important to embrace the new automated robot economy and look at strategies that will
make help the Australian keep up pace with the changing economic environment in the world.
References
Arthur, W. B. (2011, October). Where is technology taking the economy? McKinsey Quarterly.
Bakhshi, H., Downing, J. M., Osborne, M. A., & Schneider, P. (2017). THE FUTURE OF SKILLS:
EMPLOYMENT IN 2030. London: Pearson and Nesta.
Board of Governors of the Federal Reserve System. (2018, April 20). Fred Economic Data. Retrieved from
Federal Reserve Bank of St. Louis: https://fred.stlouisfed.org/series/LES1252881600Q
Borland, J., & Coelli, M. (2017). Are Robots Taking Our Jobs? Australian Economic Review, 377-397.
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time
of Brilliant Technologies .

Ford, M. (2014). Rise of the Robots. New York: Basic books.
Frey, C. B., & Osborne, M. A. (2013). The Future of Employment: How Susceptible are Jobs to
Computerisation. Oxford: Oxford Martin School, University of Oxford.
Keynes, J. M. (1963). Essays in Persuasion pp. 358-373. New York: W. W. Norton & Co.
Organization for Economic Co-operation and Development. (2017). OECD Economic Surveys: Australia.
Paris: Organization for Economic Co-operation and Development.
Pearl, R. (2018, March 13). Artificial Intelligence In Healthcare: Separating Reality From Hype. Retrieved
from Forbes: https://www.forbes.com/sites/robertpearl/2018/03/13/artificial-intelligence-in-
healthcare/#3ca057c41d75
Pol, E., & O’Brien, M. (2018). An Analytical Description of a Robot Economy. Unpublished.
Reserve Bank of Australia. (2018, March 30). Statistical Tables. Retrieved April 13, 2018, from Reserve
Bank of Australia: https://www.rba.gov.au/statistics/tables/
Reveley, J., & Pol, E. (2017). ROBOT INDUCED TECHNOLOGICAL UNEMPLOYMENT: TOWARDS A YOUTH-
FOCUSED COPING STRATEGY. Psychosociological Issues in Human Resource Management
5/2017, 169-186.
Samuelson, P. A., & Nordhaus, W. D. (2006). Economics (18th International Edition). New delhi: Tata
McGraw Hill.
Serebrenny, V., Shereuzhev, M., & Metasov, I. (2018). Approaches to the robotization of agricultural
mobile machines. 13th International Scientific-Technical Conference on Electromechanics and
Robotics “Zavalishin’s Readings" (p. Online Publication). Moscow: EDP Sciences.
The Economist Intelligence Unit. (2018). Robots: Smart, and getting smarter. Retrieved from The
Economist: http://intothefuture.eiu.com/robots-smart-and-getting-smarter/#_ftn1