Imacs 2016 imecs 2016 Proceedings (Preliminary version) of the 4
SOCIO-ECONOMIC ASPECTS OF INDUSTRY 4.0
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- 385.Introduction
- 386.1 Will there be any jobs left If so, which ones
- 1.1 Cost disease of personal services, Baumol´s disease
- 1.2 What jobs are most susceptible to automation
- 387.2 Management in the age of Industry 4.0
- 388.5 Conclusions
- 389.Acknowledgements
SOCIO-ECONOMIC ASPECTS OF INDUSTRY 4.0384.Jiří VacekAbstract Recently, the number of publications about Industry 4.0 has been steeply increasing. However, the concept of “Industry 4.0” is primarily being explored from a technical point of view – robotics, Internet of things, big data, smart objects, smart factories. There has been very little inquiry into the question of what it means for people and the society as a whole. Increasing digitisation will not only have an enormous impact on machines, factories and sectors, but on societies, economics and management as well. That is why we must look more closely at these aspects. Where are the risks – but also where are the opportunities for social innovation and progress? Industry 4.0 still has not entered the mainstream academic research, it is much more frequently treated in reports of leading consultancies as McKinsey, Deloitte, Accenture, BCG, World Bank and recently it became one of the main topics of discussion at the WEF 2016. However, as it can profoundly affect the future of jobs, management, education, and social systems, academic research in related disciplines should not stay aside and supplement the activities of technically oriented colleagues
Recently, the number of publications about Industry 4.0 has been steeply increasing. Figure 1 illustrates the rapidly increasing number of searches for “Industry 4.0” on Google. Current total number of related documents is higher than 200 mil. However, the concept of “Industry 4.0” is primarily being explored from a technical point of view – robotics, Internet of things, big data, smart objects, and smart factories. There has been relatively little inquiry into the question of what it means for people and our society on the whole.
The Czech Republic share of manufacture on the GDP is the highest in the EU (26%, while the EU average is 24%), therefore it is highly important to catch the train in time. However, it deserves attention that there still remains 76% of the GDP created in other sectors and proper attention should be paid also to them. Increasing digitisation will not only have an enormous impact on machines, factories and sectors, but on societies, economics and management as well. That is why we should look more closely at these aspects. Where are the risks – but also where are the opportunities for social innovation and progress? Industry 4.0 still has not entered the mainstream academic research – at the date of this paper writing, there were 41 references to Industry 4.0 (title) in the Web of Science and 135 references in Scopus. The topic is much more frequently treated in reports of leading consultancies as McKinsey, Deloitte, Accenture, BCG, World Bank and recently it became one of the main topics of discussion at the WEF 2016 (Foreign Affairs, 2016). However, as it can profoundly affect the future of jobs, education, and social systems, academic institutions should not stay aside. The contribution is based on the systematic literature review of resources described above and its goal is to contribute to the broader discussion of related issues. Naturally, only a small part of available information may be reproduced in a limited space. In some aspects are expressed personal views of the author not always representing the prevailing thinking.
With the diffusion of intelligent digital processes, four new work practices will become much more prevalent in leading organizations: edge-centric decision-making, real-time adaptation, human and digital recombination and experiment-driven design. „Three foregoing industrial revolutions were caused by the boom of mechanic manufacturing machines driven by steam, introduction of mass production with the use of electricity and by incorporating electronic systems and computing technology into manufacturing processes. The current phenomenon is the linking of internet of things, services and people and related immense volume of data generated by communication machine-to-machine, man-to-machine and man-to-man … The Industry 4.0 initiative is not only digitization of manufacture, it is a complex system of changes in many human activities not only in industrial production.” (Mařík 2015) We need to answer the following questions:
As MIT’s Eric Brynjolfsson and Andrew McAfee outline in their recent best seller The Second Machine Age (Brynjolfsson, McAfee, 2014), along with the benefits technological progress will leave many without work as routine tasks, including cognitive ones, are increasingly automated. 386.1 Will there be any jobs left? If so, which ones?In the fall of 2013, economist Carl B. Frey and information engineer Michael A. Osborne at the University of Oxford published a blood-curdling paper, “The Future of Employment,” in which they argue that over the next two decades, nearly half of U.S. jobs (47%, to be precise) are at high risk of being automated and 19% are at medium risk. They argue that the “safest jobs”—the ones that are impossible to automate—are associated with high levels of education and high wages. Those jobs require high-level cognitive skills and creative, social and emotional intelligence. (Frey, Osborne M, 2013) Technology has been displacing workers since the Industrial Revolution—the First Machine Age—which began in the late 1700s. The steam engine and its descendants automated routine manual labor. The computer revolution of the 1990s changed that. Suddenly, it wasn’t just muscle work—or “unskilled jobs”—that was being handed over to machines but also routine cognitive tasks performed by knowledge workers. (Mokyr et al., 2015) Today, thanks to the exponential advances in mobile robotics (MR), machine learning (ML) and artificial intelligence (AI), many non-routine cognitive and manual tasks are increasingly susceptible to automation. As emphasized by Eric Brynjolfsson and Andrew McAfee, machines equipped by artificial intelligence will be in many cases able to decide faster and better than people do (e.g. even today the control systems in complex situations as airplanes, nuclear power plants, etc., take over the work of operators; lawyers would be lost in the twists of current legislation without the support of expert systems, intelligent diagnostic systems assist doctors, language technologies are replacing minute keepers and call centers, etc.). People get bored, people get headaches. Computers don't. On the other hand, decrease of production costs and resulting decrease of product prices can lead to higher demand, what will imply more work and therefore create new jobs. Quote attributed to a 1965 NASA report advocating manned space flight: "Man is the lowest-cost, 150-pound, nonlinear, all-purpose computer system which can be mass-produced by unskilled labor." In recent article „Will Humans Go the Way of Horses?” (Foreign Affairs, 2016) Brynjolfsson and McAfee quote Nobel prize winner Wassily Leontief referring to the effect of introduction of the combustion engine: “The role of humans as the most important factor of production is bound to diminish in the same way that the role of horses . . . was first diminished and then eliminated.” Unlike horses, people can protect themselves against getting economically meaningless. They can influence their situation by democratic processes. Electorate decides about minimum wage, legality of shared economics (e.g. Uber and Airbnb) and other socio-economic issues as taxing, pensions, etc. Legislation can restrict some jobs destroying technologies. We can ask, if and what two types of work will be in demand: those that can be performed only by people or those that cannot be performed by machines? If the demand for human work will be decreasing, it will not be possible to maintain the trajectory typical for the industrial age – increasing employment and wages. Even today the work productivity is increasing faster than wages, It is not probable that automation and digitization will replace all jobs, rather it will radically change requirements on skills, talent, and creativity. It will lead to further opening of scissors - greater concentration of wealth and power. Developed economies are bifurcating into a small educated elite and the rest. There will be no comfortable “middle.” The elite—about 10% to 15% of the population—will be those with skills that are highly complementary with computers. The ability to harness the speed and power of machine intelligence will allow the elite to be hyper-productive and super wealthy. Others will endure stagnant or falling wages. The best way how to maintain jobs is to equip people by proper competencies. The governments should foster reforms of education, immigration, support entrepreneurship (it is different from business and in the Czech context often not correctly distinguished), investments into infrastructure and basic research. They could support activities actively supporting human work. Unfortunately, all of that demands strategic thinking going beyond the length of the election period. It´s highest time to start thinking about the society us and our children will live in times with decreasing demand for work:
1.1 Cost disease of personal services, Baumol´s diseaseIn 1993 democratic senator Patrick Moynihan (Moynihan, 1993) draw attention to so called Baumol disease, originally introduced by Baumol in the 1960´s and more extensively treated in (Baumol, 2012) . With increasing share of the service sector on the employment and GDP creation (and also on increasing importance of services in industry) their role in society is increasing. Moreover, many of those services cannot be in foreseeable future replaced by machines. The productivity of personal services does not grow, or grows very slowly compared to the productivity generally in the economy. Moynihan (1993) puts it this way: “In 1793 to "produce" a Mozart quartet required four persons, four stringed instruments, and, say, 35 minutes. To produce a Mozart quartet today requires -- four persons, four stringed instruments, 35 minutes. Productivity -- output per person per hour -- has hardly changed. You can play the "Minute Waltz" in 50 seconds, but it isn't the same.” 1.2 What jobs are most susceptible to automationIn autumn 2013 economist Carl B. Frey and IT engineer Michael A. Osborne concluded that within next 20 years in the USA will be endangered by automation with high probability 47% and with medium probability further 19% of jobs. (Frey, Osborne, 2013) The least endangered are jobs that are impossible or difficult to automate. Such jobs are typically occupied by highly educated people with high salaries. They demand high level of cognitive skills, creativity, social and emotional intelligence. Exponential growth of mobile robotics, machine learning and artificial intelligence threatens non-routine cognitive and manual jobs. Big data algorithms can replace human work in broad spectrum of non-routine cognitive tasks. Advanced robots with many degrees of freedom can perform more manual tasks. Frey and Osborne suggest the methodology for estimation of the probability of jobs susceptible to automation based on the routine task intensity (RTI). Some results are summarized in Fig, 2.
It can be concluded that routine jobs will be the most susceptible to automation, while new jobs demanding knowledge, creativity, innovative and entrepreneurial thinking will flourish. However there exist a serious, not very often mentioned problem: the people whose jobs will disappear will have to undergo substantial requalification and not all of them will have the personal traits and ability to find new jobs of quite different character from their former one. Into being can come a new class of not only unemployed, but even unemployable. Nevertheless it will be important to prevent their social exclusion. Some countries (Switzerland, the Netherlands) started experimenting with basic income available to all people, independent of their employment. However, such a concept implies extreme demands on public budgets. In the Czech Republic, social benefits even today consume 42% of the state budget. (Státní rozpočet v kostce,, 2015) It will be necessary to reconsider the basics of the system of taxes, social and health insurance that in today´s system will not be paid by robots, automatic systems, etc. There remains a question if those losses can be compensated by increased VAT tax and other taxes resulting from increased salaries or progressive tax. Another possible approach is flexicurity, made up of the special mix of labour market flexibility combined with social security. The purpose of flexicurity is to join various kinds of flexibility with different degrees of security. (Flexicurity, 2016) 387.2 Management in the age of Industry 4.0“Managers and machines, unite” - Accenture Intelligent machines support better and faster decision making. They allow to managers to focus more on the specifically “human” activities. They complement knowledge and experience of managers, their ability of experimenting and innovating. Accenture research (Shanks, Sinha&Thomas, 2015) included 37 managers from seven industries and 9 countries. They valued most the decision making support of new technologies. Real potential they see in releasing the organisation creative potential, identification of new opportunities and leading of dynamic workers. 84% of managers suppose the machines will help them to increase effectiveness and efficiency and make the work more interesting; 57% of them replied their current competencies are not satisfactory. However, only about fifth of managers considers interpersonal skills important. It may be a problem, as they will have to inspire and motivate their teams. Only 46% would rely on the advice of intelligent systems in decision making. Without trust it is improbable that the organisation would do more than automating some routine managerial tasks. What could increase their trust? 60%: better understanding of principles of systems working and generating advice 55%: selection of a system with good references 49%: selection of a system explaining logics of its decisions Fig. 3: Expected managers skills importance Interpersonal Skills Source: Adapted from (Accenture, 2015) 388.5 ConclusionsOver the next five years, new digital technologies promise to dramatically change work outcomes and work experiences for employees of all sorts – manual workers, knowledge workers and managers alike – across a wide array of industries. To move from looking digital to being digital, companies must engage in a deep shift in the way they do business. 389.AcknowledgementsThis contribution was prepared with support on the University of Bohemia internal grant SGS-2016-034 – Actual trends in business management and entrepreneurship 390.ReferencesBatten Institute (2015), Innovation in the Age of Smart Machines. Retrieved March 28, 2016, from http://issuu.com/batteninstitute/docs/smartmachines-120414-issuu Baumol, W. J. (2012). The cost disease: Why computers get cheaper and health care doesn't. New Haven, CT: Yale University Press. Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York: W.W. Norton. David H. Autor (2015). The history and future of workplace automation. Journal of Economic Perspectives, 29(3), pp 3–30, http://economics.mit.edu/files/10865, http://pubs.aeaweb.org/doi/pdfplus/10.1257/jep.29.3.3 Enabling the next production revolution (2015), OECD, Retrieved March 28, 2016, from http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=DSTI/IND%282015%292&docLanguage=En Flexicurity (2016). Danish Ministry of Employment, Retrieved March 28, 2016, from http://uk.bm.dk/en/Themes/The%20Danish%20Labour%20Market/Flexicurity.aspx Foreign Affairs (2016). The Fourth Industrial Revolution: A Davos Reader. Retrieved March 28, 2016, from https://www.foreignaffairs.com/anthologies/2016-01-01/fourth-industrial-revolution Frey C.B., Osborne M. (2013). The Future of Employment: How susceptible are jobs to computerisation? Retrieved March 28, 2016, from http://www.oxfordmartin.ox.ac.uk/publications/view/1314 Mařík V. (ed.) (2015). Průmysl 4.0. Retrieved March 28, 2016, from http://www.mpo.cz/dokument162351.html Michael Chui, James Manyika, and Mehdi Miremadi (2015). Four fundamentals of workplace automation. McKinsey Quarterly, Retrieved March 28, 2016, from http://www.mckinsey.com/insights/business_technology/four_fundamentals_of_workplace_automation Mokyr, J., Vickers, C., & Ziebarth, N. L. (2015). The History of Technological Anxiety and the Future of Economic Growth: Is This Time Different? Journal of Economic Perspectives, 29(3), 31-50. Moynihan D.P. (1993). Don't Blame Democracy. Retrieved March 28, 2016, from https://www.washingtonpost.com/archive/opinions/1993/06/06/dont-blame-democracy/4201905c-8d43-4f24-b385-3a62b9cdea85/ Shanks R., Sinha S., Thomas R.J. (2015). Managers and machines, unite! Retrieved March 28, 2016, from http://www.accenture.com/managersandmachines
doc. Ing. Jiří Vacek, Ph.D. University of West Bohemia, Faculty of Economics Husova 11, 306 14 Plzeň vacekj@kpm.zcu.cz
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