Robotization and Welfare Trends in Future

*Belma Kencebay*

## **Abstract**

There are concerns over the present and possible future impact of new advancements like robots and artificial intelligence on welfare. Experts from different fields including science and business have been concentrating on how new developments may affect the job market, and more broadly how new advancements will influence the society. It would be easy to get support for the use of robots for the tasks which are too difficult or too dangerous for humans. What is the capital owners' focus at that point? What are the economic and social consequences of robotization? In this chapter, literature review including the recent thoughts on how developments in robotics may cause major changes in welfare distribution and revolutionary economic changes is presented.

**Keywords:** robots, personal economy, robotics, economic effect of robotics, welfare trends, unconditional basic income (UBI) , guaranteed minimum income (GMI), industry 4.0, skill premia, skill-biased technical change (SBTC), polarization

## **1. Introduction**

The new World Robotics report indicates that more than 2.4 million robots are working in manufacturing lines. The robot sales amount is around 16.5 billion USD. As indicated by The International Federation of Robotics (IFR) public statement on Feb 19, 2020 from 2020 to 2022 right around 2 million new units of robots are relied upon to be introduced in industrial facilities around the globe [1].

Robotics technology developed majorly from 1990 to 2000s, especially with an increase in the number of industrial robots in the United States and Western Europe from 1993 to 2007. In the United States, the rise numbered to one new robot per 1000 workers, and in Western Europe to 1.6 new robots per 1000 workers. The automotive industry utilizes the major part of it by 38% of existing robots, then the electronics industry follows it by 15% and the plastics and chemicals industry follows it by 10% and lastly metal products industry by 7%. Acemoglu theoretically found that robots can decrease employment and wages and that their local effects can be evaluated utilizing variety in exposure to robots—defined from industrylevel advances in robotics and local industry employment. It is assessed that the relevant field most threatened by robots after 1990 does not exhibit any differential trends before then, and robots' effect is separated from other capital and technologies. One more robot per 1000 workers decreases the employment-to-population ratio by 0.2% and wages by 0.42% [2].

The 47% of laborers in USA will be exposed to risk of losing their employment as indicated by Frey and Osborne [3] study including characterization of

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*Service Robotics*

**References**

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[1] Song J, Zhang T, Xu L, et al. Research actuality and prospect of picking robot for fruits and vegetables. Transactions of the Chinese Society for Agricultural

[10] Wang X. Study on information acquisition and path planning of greenhouse tomato harvesting robot for selective harvesting operations [thesis]. Zhenjiang: Jiangsu University; 2012

[11] Ling X, Zhao Y, Gong L, Liu C, Wang T. Dual-arm cooperation and implementing for robotic harvesting tomato using binocular vision. Robotics and Autonomous Systems.

[12] Foote T. tf: The transform library. In: IEEE Conference on Technologies for Practical Robot Applications (TePRA); 22-23 April 2013. Woburn. New York:

[13] Bohren J, Cousins S. The SMACH high-level executive [ROS news]. IEEE Robotics and Automation Magazine. 2010;**17**(4):18-20. DOI: 10.1109/

[14] Mcgann C et al. Model-Based, Hierarchical Control of a Mobile Manipulation Platform. Thessaloniki, Greece: ICAPS Workshop Planning and Plan Execution for Real-World Systems;

[15] Meeussen W et al. Autonomous door opening and plugging in with a personal robot. In: IEEE International

Automation; 3-7 May 2010. Anchorage. New York: IEEE; 2010. pp. 729-736

[16] Joseph H. Getting Started with Smach [Internet]. 2018. Available from: https://wiki.ros.org/smach/Tutorials/ Getting%20Started [Accessed: 21 March

[17] Marchand E et al. ViSP for visual servoing: A generic software platform with a wide class of robot control skills. IEEE Robotics and Automation Magazine. 2005;**12**(4):40-52. DOI: 10.1109/MRA.2005.1577023

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[2] Kondo N et al. Fruit harvesting robots in Japan. Advances in Space Research. 1996;**18**:181-184. DOI: 10.1016/0273-1177(95)00806-P

[3] Zhao Y, Wu C, Hu X, et al. Research progress and problems of agricultural robot. Transactions of the Chinese Society of Agricultural Engineering.

[4] Tanigaki K et al. Cherry-harvesting robot. Computers and Electronics in Agriculture. 2008;**63**:65-72. DOI: 10.1016/j.compag.2008.01.018

harvesting sweet-pepper in greenhouses. In: Proceedings International Conference of Agricultural Engineering. Zurich;

[7] Nagata M et al. Studies on automatic sorting system for strawberry (part 3) development of sorting system using image processing. Journal of the Japanese Society of Agricultural Machinery.

[8] Zhaoxiang L, GANG L. Apple

maturity discrimination and positioning system in an apple harvesting robot. New Zealand Journal of Agricultural Research. 2007;**50**:1103-1113. DOI: 10.1080/00288230709510392

[9] Guo F et al. Fruit detachment and classification method for strawberry harvesting robot. International Journal of Advanced Robotic Systems. 2008;**5**(1):41-48. DOI: 10.5772/5662

[5] Hemming J et al. A robot for

[6] Taqi F et al. A cherry-tomato harvesting robot. In: 18th International Conference on Advanced Robotics (ICAR); 10-12 July 2017. Hong Kong. New York: IEEE; 2017. pp. 463-468

702 occupations dependent on its degree of lack of protection against automation. Other supporting report has been published by the World Bank assesses that 57% of professions in the OECD could be robotized all through the upcoming two decades [4, 5].

Frey and Osborne [3] foresees a shortening of the current trend toward labor market polarization; computerization is mainly related to low skills and low paid professions. Their findings imply that, as technology advances, low experienced labors will redistribute assignments that are not delicate to computerization. Frey and Osborne [3] divide between high, medium, and low risk professions based on the possibility of computerization. According to the study, about 47% of total US employment is in the high risk category [6].

Expanding on the evaluation performed by Frey et al., other investigation assesses the effect of robotization for the OECD including 32 nations that have partaken in the survey of adult skills. It infers that 14% of occupations in OECD would be profoundly controlled by automation (i.e., likelihood of computerization of over 70%). More than 66 million employees from 32 different countries included in Frey's study. According to the study, another 32% of occupations have a danger of somewhere in the range of 50–70% highlighting the chance of huge change in the manner these jobs are fulfilled due to robotization. For example, a critical portion of errands, yet not all, could be robotized, changing the expertise prerequisites for the employments [7–9].

We may see the development of new instruction programs, especially an expansion in computer generated reality gaming-based training and particularly in coding. Be that as it may, this will be tempered by the rise of AI/apply autonomy moving into the information segment, which can possibly prompt the disappearing of expert class, non-administrative desk occupations. Simultaneously, mechanical autonomy will move forcefully into sensor-based, world-route occupations like transportation. We may require a crucial reshaping of our economy and may not give educating/training individuals for occupations that are just not going to be there. And also recent studies found that high levels of anxiety about robotization and automation indicate the broad concerns about their outcomes [7].

It turns out a considerable amount of vulnerability and contention remains. In this chapter, the recent thoughts on how AI and robotics may cause major changes in welfare distribution and revolutionary employment changes will be summarized by a literature review.

## **2. Literature review**

In the study, we will look at two main topics, the first is literature about robotization and its effect on employment and the second is possible future welfare distribution models.

#### **2.1 Robotization and unemployment**

In this area, the academics are divided into two poles, one pole assumes that the firm-level adoption of robots causes a decrease in labor shares, rises in added value and productivity, and reduces the share of production workers. Especially in industrial sectors which are specialized in routine activities are more likely to face substantial decreases in the labor share. Some of the studies theorize that new changes in automation, robotics, and artificial intelligence (AI) might pave the way for broad unemployment. All types of occupations from lawyers to truck drivers will be permanently tumbled. Companies will be forced to change or expire. The

**135**

*Robotization and Welfare Trends in Future DOI: http://dx.doi.org/10.5772/intechopen.93346*

**Robotization effects on employment**

**Studies Dimensions/ideas**

Autor [15] Polarization

Acemoglu and Restrepo [2] SBTC/polarization/ICT Acemoglu and Restrepo [11] The displacement effect Acemoglu and Restrepo [2] Robotization/unemployment Acemoglu et al. [12] Robotization/unemployment Autor and Dorn [13] SBTC/polarization/ICT Autor et al. [14] SBTC/polarization/ICT

Autor et al. [16] SBTC/polarization/ICT Autor et al. [14] SBTC/polarization/ICT Berman et al. [17] SBTC/polarization/ICT

in unemployment.

latest economic signals also reflect this trend; less people are employed, and wages are declining even as productiveness and earnings rise. The list below includes the academicians whose articles associated the robotization and automation to increase

Acemoglu [10] Skill premia/skill-biased technical change (SBTC)

Brynjolfsson and McAfee [18] Robotization/unemployment/structural changes

Brynjolfsson et al. [10] The "capital deeping" with robotization Dao et al. [19] SBTC/routinized job industry based Frey and Osborne [3] Robotization/unemployment Goos and Manning [20] SBTC/polarization/ICT Goos et al. [21] SBTC/polarization/ICT Graetz and Michaels [22] SBTC/polarization/ICT Gregg and Manning [23] Wage inequality/SBTC

Huang and Rust [24] Artificial intelligence (AI)/unemployment

Krusell et al. [25] SBTC/polarization/ICT

Michaels et al. [26] SBTC/polarization/ICT Nedelkoska and Quintini [9] Robotization/unemployment Sachs and Kotlikoff [27]; Benzel et al. [28] SBTC/polarization/ICT

Sachs et al. [9] Robotization/unemployment Susskind and Susskind [29] Robotization/unemployment Van Reenen [30] Wage inequality/SBTC/polarization

Goos et al. [21] Polarization

As can be seen above, the dimensions that are studied related with robotization and employment, is listed as skill-biased technical change, polarization, wage inequality, and skill premia. Skill premia can be described as the relative wage of high-skilled workers to low-skilled workers and according to Brynjolfsson and McAfee [18, 32], it has risen over most of the second half of the last century, despite large increases in the supply of high-skilled workers. Acemoglu [10] developed a

Sachs and Kotlikoff [27]; Benzell et al. [28] Robotization/unemployment/structural changes

Wolter et al. [31] 5-step scenario transformation to Industry 4.0

## *Robotization and Welfare Trends in Future DOI: http://dx.doi.org/10.5772/intechopen.93346*

*Service Robotics*

decades [4, 5].

the employments [7–9].

by a literature review.

**2. Literature review**

welfare distribution models.

**2.1 Robotization and unemployment**

employment is in the high risk category [6].

702 occupations dependent on its degree of lack of protection against automation. Other supporting report has been published by the World Bank assesses that 57% of professions in the OECD could be robotized all through the upcoming two

Frey and Osborne [3] foresees a shortening of the current trend toward labor market polarization; computerization is mainly related to low skills and low paid professions. Their findings imply that, as technology advances, low experienced labors will redistribute assignments that are not delicate to computerization. Frey and Osborne [3] divide between high, medium, and low risk professions based on the possibility of computerization. According to the study, about 47% of total US

Expanding on the evaluation performed by Frey et al., other investigation assesses the effect of robotization for the OECD including 32 nations that have partaken in the survey of adult skills. It infers that 14% of occupations in OECD would be profoundly controlled by automation (i.e., likelihood of computerization of over 70%). More than 66 million employees from 32 different countries included in Frey's study. According to the study, another 32% of occupations have a danger of somewhere in the range of 50–70% highlighting the chance of huge change in the manner these jobs are fulfilled due to robotization. For example, a critical portion of errands, yet not all, could be robotized, changing the expertise prerequisites for

We may see the development of new instruction programs, especially an expansion in computer generated reality gaming-based training and particularly in coding. Be that as it may, this will be tempered by the rise of AI/apply autonomy moving into the information segment, which can possibly prompt the disappearing of expert class, non-administrative desk occupations. Simultaneously, mechanical autonomy will move forcefully into sensor-based, world-route occupations like transportation. We may require a crucial reshaping of our economy and may not give educating/training individuals for occupations that are just not going to be there. And also recent studies found that high levels of anxiety about robotization

and automation indicate the broad concerns about their outcomes [7].

It turns out a considerable amount of vulnerability and contention remains. In this chapter, the recent thoughts on how AI and robotics may cause major changes in welfare distribution and revolutionary employment changes will be summarized

In the study, we will look at two main topics, the first is literature about robotization and its effect on employment and the second is possible future

In this area, the academics are divided into two poles, one pole assumes that the firm-level adoption of robots causes a decrease in labor shares, rises in added value and productivity, and reduces the share of production workers. Especially in industrial sectors which are specialized in routine activities are more likely to face substantial decreases in the labor share. Some of the studies theorize that new changes in automation, robotics, and artificial intelligence (AI) might pave the way for broad unemployment. All types of occupations from lawyers to truck drivers will be permanently tumbled. Companies will be forced to change or expire. The

**134**

latest economic signals also reflect this trend; less people are employed, and wages are declining even as productiveness and earnings rise. The list below includes the academicians whose articles associated the robotization and automation to increase in unemployment.


As can be seen above, the dimensions that are studied related with robotization and employment, is listed as skill-biased technical change, polarization, wage inequality, and skill premia. Skill premia can be described as the relative wage of high-skilled workers to low-skilled workers and according to Brynjolfsson and McAfee [18, 32], it has risen over most of the second half of the last century, despite large increases in the supply of high-skilled workers. Acemoglu [10] developed a

model to explore how skill premia changes by time and between countries and how it work on this framework to see the effect of foreign commerce on wage inequality. Skill premia is regulated by technology and the supply of skills. Skill-biased technical change (SBTC) can be described as a transfer in the manufacturing technology that prefer competent over incompetent employees by increasing its relative productivity and, therefore, its relative demand. In the literature, SBTC has been studied for several years in that the productivity of more competent workers has risen more faster than that of incompetent workers. This SBTC has been getting quite high recognition due to its relation with increasing wage inequality. Gregg and Manning [23] concluded that when workers are paid according to their productiveness, alteration in productivity reflects revision in wages, and the labor market position of the incompetent workers will continue to fall apart and disappear. Goos et al. [21] studied the job polarization (JP) within-industry and between-industry components empirically and concluded that the employment design in Western Europe has been polarizing with increasing employment proportions for well-paid occupations and supervisors and also flat-salaried service employees and increasing unemployment shares of manufacturing and routine office employees. The JP is a kind of technological change, favoring toward exchanging employees who are doing routine tasks and then the tasks are offshored and both polarization and offshoring create a decline in the demand for average-skilled workers relative to competent workers and incompetent occupations.

Acemoglu [2] contemplated a few sources including a survey by the Ministry of Industry, information provided by French robot suppliers in addition to list of clients, customs data on imports of industrial robots by firm, and the French fiscal files and developed theoretical expectations about adoption of robots for French assembling companies and examine the level ramifications of robot usage. Out of 55,390 firms in their study, 598 have received robots somewhere in the range of 2010 and 2015. Their study indicated that how companies alter their manufacturing system, recruitment, work force portions, and productiveness as they embrace automation technologies that can help us to better understand the wide-ranging effects of automation. Nevertheless, company-level effects do not correspond to the overall impact of automation because firms that adopt such technologies decline the costs and broaden at the expense of competitors. Acemoglu [2] predicts that French manufacturing firms that embrace robots not only decrease their work force portion and percentage of manufacturing laborer and rise their productivity but also expand their operations and employment. Yet, this is more than offset by significant declines in their competitors' employment. Generally speaking, despite the fact that organizations receiving robots extend their work, the market-level ramifications of robot appropriation are not positive. They also declare that robot acceptance commits to the decrease in the production work force portion by decreasing the covariance between firm-level value added and labor share, and this is because adopters are large and enlarge further as they observe sizable relative decreases in their work force portions. The 20% rise in robot adopting is resulted with a 3.2% increase in industry unemployment [12].

Acemoglu and Restrepo started a framework published in 2019, according to the heart of their framework is the fundamental thought that computerization and along these lines AI and mechanical technology supplant laborers in undertakings that they recently performed, and by means of this channel, make an incredible "The displacement effect." As opposed to assumptions in a lot of macroeconomics and financial matters, which keep up that profitability upgrading innovations consistently increment in general work request, the relocation impact can diminish the interest for work, wages, and business. In addition, the "displacement effect" infers that increments in yield per specialist emerging from robotization will not bring

**137**

*Robotization and Welfare Trends in Future DOI: http://dx.doi.org/10.5772/intechopen.93346*

in the interest for work in nonautomating divisions.

national salary.

effect [12].

of laborers [27, 28, 34].

mechanical pioneers and loafers in each area [35].

about a relative development of the interest for work. The removal effect causes a decoupling of wages and yield per laborer and a decrease in the portion of work in

Acemoglu et al. [12] at that point feature a few countervailing powers that push against the uprooting impact and may infer that computerization, AI, and apply autonomy could build labor demand. First, the replacement of modest machines for human work makes an "efficiency impact": as the expense of delivering mechanized assignments decays, the economy will grow and expand the interest for work in nonautomated errands. The efficiency effect could show itself as an expansion in the interest for work in similar areas experiencing robotization or as an expansion

Second, according to Acemoglu et al. [12], "capital aggregation" activated by expanded mechanization (which raises the interest for capital) will likewise raise the interest for work. Third, mechanization does not simply work at the broad edge—supplanting undertakings recently performed by work—yet at the escalated edge also, expanding the efficiency of machines in assignments that were recently robotized. This marvel, which we allude to as "deepening of automation," makes an efficiency effect however no uprooting, and along these lines builds work request. Despite the fact that these countervailing impacts are significant, they are for the most part deficient to incite a "balanced growth path," implying that regardless of whether these effects were incredible, continuous computerization would at present lessen the offer of work in national income (and potentially employment). Acemoglu et al. [12] contend that there is an all the more remarkable countervailing power that expands the interest for work just as the portion of work in national income: the formation of new undertakings, capacities, and exercises in which work has a near preferred position relative to machines. The production of new errands creates a restoration effect straightforwardly counterbalancing the displacement

Sachs et al. [33] expect in their study that robots are not to help people in the study, however to supplant them totally. They concluded that the presentation of robots will help profitability in the short term, yet decline wages and utilization over the long haul. Sachs and Kotlikoff [27], expecting that "brilliant machines" supplant youthful and untalented yet favor old and talented work, locate that lone a generational arrangement can make the presentation of robots a gainful situation for the two ages. So also, Sachs et al. [33] contend for government redistribution in this situation to counter the "immiserization" of people in the future. Autor [34] reacts to these alerts by expressing that in these models "the key danger isn't innovation essentially yet misgovernance": it is not an issue of shortage of employments, but instead a distributional issue that robots undoubtedly make human work pointless. He contends that a fitting capital duty can assist with gaining innovative ground a government assistance improving procedure for all gatherings

Robotization and advanced innovations all the more for the most part will empower little players, including people and little organizations, to attempt venture work that is currently before were done inside greater firms. The development of little and extremely enormous organizations could make a barbell-shaped economy, in which middle-sized organizations could miss out. It is not yet clear whether computerization could elevate rivalry, empowering firms to enter new zones

outside their past center organizations and making a developing separation between

The skill premia (the general pay of high-talented specialists to low-gifted laborers) rise up the majority of the second 50% of the only remaining century, regardless of huge increments in the gracefully of high-gifted laborers. The end

*Service Robotics*

and incompetent occupations.

industry unemployment [12].

model to explore how skill premia changes by time and between countries and how it work on this framework to see the effect of foreign commerce on wage inequality. Skill premia is regulated by technology and the supply of skills. Skill-biased technical change (SBTC) can be described as a transfer in the manufacturing technology that prefer competent over incompetent employees by increasing its relative productivity and, therefore, its relative demand. In the literature, SBTC has been studied for several years in that the productivity of more competent workers has risen more faster than that of incompetent workers. This SBTC has been getting quite high recognition due to its relation with increasing wage inequality. Gregg and Manning [23] concluded that when workers are paid according to their productiveness, alteration in productivity reflects revision in wages, and the labor market position of the incompetent workers will continue to fall apart and disappear. Goos et al. [21] studied the job polarization (JP) within-industry and between-industry components empirically and concluded that the employment design in Western Europe has been polarizing with increasing employment proportions for well-paid occupations and supervisors and also flat-salaried service employees and increasing unemployment shares of manufacturing and routine office employees. The JP is a kind of technological change, favoring toward exchanging employees who are doing routine tasks and then the tasks are offshored and both polarization and offshoring create a decline in the demand for average-skilled workers relative to competent workers

Acemoglu [2] contemplated a few sources including a survey by the Ministry of Industry, information provided by French robot suppliers in addition to list of clients, customs data on imports of industrial robots by firm, and the French fiscal files and developed theoretical expectations about adoption of robots for French assembling companies and examine the level ramifications of robot usage. Out of 55,390 firms in their study, 598 have received robots somewhere in the range of 2010 and 2015. Their study indicated that how companies alter their manufacturing system, recruitment, work force portions, and productiveness as they embrace automation technologies that can help us to better understand the wide-ranging effects of automation. Nevertheless, company-level effects do not correspond to the overall impact of automation because firms that adopt such technologies decline the costs and broaden at the expense of competitors. Acemoglu [2] predicts that French manufacturing firms that embrace robots not only decrease their work force portion and percentage of manufacturing laborer and rise their productivity but also expand their operations and employment. Yet, this is more than offset by significant declines in their competitors' employment. Generally speaking, despite the fact that organizations receiving robots extend their work, the market-level ramifications of robot appropriation are not positive. They also declare that robot acceptance commits to the decrease in the production work force portion by decreasing the covariance between firm-level value added and labor share, and this is because adopters are large and enlarge further as they observe sizable relative decreases in their work force portions. The 20% rise in robot adopting is resulted with a 3.2% increase in

Acemoglu and Restrepo started a framework published in 2019, according to the heart of their framework is the fundamental thought that computerization and along these lines AI and mechanical technology supplant laborers in undertakings that they recently performed, and by means of this channel, make an incredible "The displacement effect." As opposed to assumptions in a lot of macroeconomics and financial matters, which keep up that profitability upgrading innovations consistently increment in general work request, the relocation impact can diminish the interest for work, wages, and business. In addition, the "displacement effect" infers that increments in yield per specialist emerging from robotization will not bring

**136**

about a relative development of the interest for work. The removal effect causes a decoupling of wages and yield per laborer and a decrease in the portion of work in national salary.

Acemoglu et al. [12] at that point feature a few countervailing powers that push against the uprooting impact and may infer that computerization, AI, and apply autonomy could build labor demand. First, the replacement of modest machines for human work makes an "efficiency impact": as the expense of delivering mechanized assignments decays, the economy will grow and expand the interest for work in nonautomated errands. The efficiency effect could show itself as an expansion in the interest for work in similar areas experiencing robotization or as an expansion in the interest for work in nonautomating divisions.

Second, according to Acemoglu et al. [12], "capital aggregation" activated by expanded mechanization (which raises the interest for capital) will likewise raise the interest for work. Third, mechanization does not simply work at the broad edge—supplanting undertakings recently performed by work—yet at the escalated edge also, expanding the efficiency of machines in assignments that were recently robotized. This marvel, which we allude to as "deepening of automation," makes an efficiency effect however no uprooting, and along these lines builds work request. Despite the fact that these countervailing impacts are significant, they are for the most part deficient to incite a "balanced growth path," implying that regardless of whether these effects were incredible, continuous computerization would at present lessen the offer of work in national income (and potentially employment). Acemoglu et al. [12] contend that there is an all the more remarkable countervailing power that expands the interest for work just as the portion of work in national income: the formation of new undertakings, capacities, and exercises in which work has a near preferred position relative to machines. The production of new errands creates a restoration effect straightforwardly counterbalancing the displacement effect [12].

Sachs et al. [33] expect in their study that robots are not to help people in the study, however to supplant them totally. They concluded that the presentation of robots will help profitability in the short term, yet decline wages and utilization over the long haul. Sachs and Kotlikoff [27], expecting that "brilliant machines" supplant youthful and untalented yet favor old and talented work, locate that lone a generational arrangement can make the presentation of robots a gainful situation for the two ages. So also, Sachs et al. [33] contend for government redistribution in this situation to counter the "immiserization" of people in the future. Autor [34] reacts to these alerts by expressing that in these models "the key danger isn't innovation essentially yet misgovernance": it is not an issue of shortage of employments, but instead a distributional issue that robots undoubtedly make human work pointless. He contends that a fitting capital duty can assist with gaining innovative ground a government assistance improving procedure for all gatherings of laborers [27, 28, 34].

Robotization and advanced innovations all the more for the most part will empower little players, including people and little organizations, to attempt venture work that is currently before were done inside greater firms. The development of little and extremely enormous organizations could make a barbell-shaped economy, in which middle-sized organizations could miss out. It is not yet clear whether computerization could elevate rivalry, empowering firms to enter new zones outside their past center organizations and making a developing separation between mechanical pioneers and loafers in each area [35].

The skill premia (the general pay of high-talented specialists to low-gifted laborers) rise up the majority of the second 50% of the only remaining century, regardless of huge increments in the gracefully of high-gifted laborers. The end

was that there more likely than not been something like an SBTC which expanded the interest for high-talented laborers considerably more. Berman et al. [17] were among the frontier to examine the wellsprings of the consistently expanding skill premia. In a comparative vein, Krusell et al. [25] modeled an economy with an interdependent between a sort of capital and high-talented laborers. The kind of capital they have at the top of the priority list is Information and Communication Technology (ICT) capital. Krusell et al. [25] report that the cost of ICT capital has been falling for quite a long while. In this way, such a capital-ability interdependency, a fall in the cost of ICT capital will prompt an expanded reception in firms and consequently to an expanded interest for high-talented specialists to work these machines. Michaels et al. [26] affirm these discoveries with more up to date information: Sectors with higher development in ICT likewise had higher increments in the interest for high-gifted specialists and diminishes in the interest for center talented laborers. Spitz-Oener [36] secures that position necessities have been expanding in a similar time, for example, the extent of complex undertakings has been expanding. These adjustments in the assignment structure have additionally raised the interest for aptitudes in the labor market [25].

Dao et al. [19] discover that industrial sectors which had some expertise in routine exercises would in general experience bigger abatements in the labor share. Graetz and Michaels [22] use open data on robot use to measure the effects on labor profitability development, absolute factor productivity development, unit costs, and employment. Their disclosures show that robots increment labor efficiency development and all out profitability development however will in general reduce output price. While there is by all accounts no impact of robots use and complete business, they locate a negative effect of robots on the work portion of low-gifted specialists [22, 37].

In another investigation, Acemoglu and Restrepo [11] center around US nearby work markets. They join information from EU KLEMS and robot use to follow the impacts of expanded presentation to robots on neighborhood work markets from 1970 to 2007. As Graetz and Michaels [22], they find that the appropriation of robots prompts enormous and strong decreases in work and wages [38].

The movement of AI task substitution from lower to higher intellect (mechanical, scientific, instinctive, and sympathetic) brings about unsurprising movements after some time. As indicated by this view, scientific abilities will turn out to be less significant, as AI assumes control over progressively expository errands, giving the "milder" natural and sympathetic aptitudes considerably more significance for administration representatives. In the end, AI will be equipped for performing even the instinctive and compassionate undertakings, which empowers imaginative methods of humanmachine incorporation for offering support yet in addition brings about a key risk for human employment [24, 39].

Other than work replacement, the innovative change is relied upon to influence the structure of employment much more than the degree of employment, something that would make a more polarized labor market between profoundly qualified and low-gifted occupations. An outcome, there would be progressively huge pay imbalances between the two posts.

A primary challenge for the eventual fate of work is related to adapting to rising disparity, as innovative change will generate the victors and failures and an expansion of the working poor [5, 21]. The some of studies concludes that innovation might be the single biggest supporter of the expansion in disparity of salary. This emerges on the grounds that organizations embrace advances at an alternate pace and have varying degrees of accomplishment with their AI and automated changes. Simultaneously, the robotization of laborers' exercises for capital drives down the work portion of pay [7, 35].

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complementary [43].

*Robotization and Welfare Trends in Future DOI: http://dx.doi.org/10.5772/intechopen.93346*

optimistic studies are listed below:

**Studies Dimensions/ideas**

Negroponte [46] Borderless new era

**Robotization effects on** 

**employment**

Until then some studies from pessimistic view are mentioned, but there are some other studies believe that robotization and employment can be complimentary. The

Arntz et al. [40] Automation is hard to adapt/massive diversity of tasks/adaptability of jobs in the digital transformation Autor and Salomons [41] Own-industry, between-industry, cross-country, and final demand

Bresnahan et al. [42] Skilled labor is complementary with a cluster of three distinct changes

new products and services.

Kurzweil [44] Improvements in technology will yield greater opportunities Mokyr et al. [45] Innovations will result in unimaginable new occupations

Song [47] Technology, will rid markets of inefficiency and propel humanity toward its fullest potential Wolter et al. [31] The Economy 4.0 scenario will create 1.5 million new jobs which will

Zeira [48] Increases capital requirements/highly productive countries will employ robotization

at the firm level: information technology, new work organization, and

Autor [34] The automation and labor are highly complementary

effects

Doms et al. [43] Skilled labor and ICT are complementary

not exist

For example, Autor [34] identify in his study that the automation has not clear out a most of jobs instead, automation will substitute for labor—as it is typically intended to do. But, automation will also complement labor, increases output that create higher demand for labor, and responds to changes in labor supply. He believes that some studies lean to overestimate the context of robot backup for labor and forget the robust complementarities between robotization and labor that rise productivity, increase earnings, and boost demand for labor. Autor [34] also argue in his study that the polarization is doubtful to go very far into the anticipated future. Arntz et al. [40] demonstrates that these pessimistic scenarios are exaggerating the portion of automatable jobs by ignoring the massive diversity of tasks within jobs as well as the versatility of jobs in the digital transformation. In order to support their proposal, they used detailed task data and declared that, when taking into accounting the spectrum of tasks within jobs, the robotization risk of US jobs decrease from 38 to 9%. Earlier studies have produced by Doms et al. concluded that based on the skill-biased nature of ICT that indicate skilled labor and ICT are

Autor and Salomons [41] has also concluded that systematic view of four different channels of how robotization may affect the employee market; ownindustry effects, between-industry, cross-country effects, and final demand effects. They stated that total factor productivity has negative direct effects on employment but positive indirect effects. In summary, the positive effects dominate and the long term outcome of robotization on employment is positive. They studied 24 OECD economies and stated that while displacing employment in the industries where it originates, automation generates indirect employment

*Service Robotics*

specialists [22, 37].

human employment [24, 39].

work portion of pay [7, 35].

imbalances between the two posts.

was that there more likely than not been something like an SBTC which expanded the interest for high-talented laborers considerably more. Berman et al. [17] were among the frontier to examine the wellsprings of the consistently expanding skill premia. In a comparative vein, Krusell et al. [25] modeled an economy with an interdependent between a sort of capital and high-talented laborers. The kind of capital they have at the top of the priority list is Information and Communication Technology (ICT) capital. Krusell et al. [25] report that the cost of ICT capital has been falling for quite a long while. In this way, such a capital-ability interdependency, a fall in the cost of ICT capital will prompt an expanded reception in firms and consequently to an expanded interest for high-talented specialists to work these machines. Michaels et al. [26] affirm these discoveries with more up to date information: Sectors with higher development in ICT likewise had higher increments in the interest for high-gifted specialists and diminishes in the interest for center talented laborers. Spitz-Oener [36] secures that position necessities have been expanding in a similar time, for example, the extent of complex undertakings has been expanding. These adjustments in the assignment structure have addi-

tionally raised the interest for aptitudes in the labor market [25].

Dao et al. [19] discover that industrial sectors which had some expertise in routine exercises would in general experience bigger abatements in the labor share. Graetz and Michaels [22] use open data on robot use to measure the effects on labor profitability development, absolute factor productivity development, unit costs, and employment. Their disclosures show that robots increment labor efficiency development and all out profitability development however will in general reduce output price. While there is by all accounts no impact of robots use and complete business, they locate a negative effect of robots on the work portion of low-gifted

In another investigation, Acemoglu and Restrepo [11] center around US nearby work markets. They join information from EU KLEMS and robot use to follow the impacts of expanded presentation to robots on neighborhood work markets from 1970 to 2007. As Graetz and Michaels [22], they find that the appropriation of robots prompts enormous and strong decreases in work and wages [38].

The movement of AI task substitution from lower to higher intellect (mechanical, scientific, instinctive, and sympathetic) brings about unsurprising movements after some time. As indicated by this view, scientific abilities will turn out to be less significant, as AI assumes control over progressively expository errands, giving the "milder" natural and sympathetic aptitudes considerably more significance for administration representatives. In the end, AI will be equipped for performing even the instinctive and compassionate undertakings, which empowers imaginative methods of humanmachine incorporation for offering support yet in addition brings about a key risk for

Other than work replacement, the innovative change is relied upon to influence the structure of employment much more than the degree of employment, something that would make a more polarized labor market between profoundly qualified and low-gifted occupations. An outcome, there would be progressively huge pay

A primary challenge for the eventual fate of work is related to adapting to rising disparity, as innovative change will generate the victors and failures and an expansion of the working poor [5, 21]. The some of studies concludes that innovation might be the single biggest supporter of the expansion in disparity of salary. This emerges on the grounds that organizations embrace advances at an alternate pace and have varying degrees of accomplishment with their AI and automated changes. Simultaneously, the robotization of laborers' exercises for capital drives down the

**138**

Until then some studies from pessimistic view are mentioned, but there are some other studies believe that robotization and employment can be complimentary. The optimistic studies are listed below:


For example, Autor [34] identify in his study that the automation has not clear out a most of jobs instead, automation will substitute for labor—as it is typically intended to do. But, automation will also complement labor, increases output that create higher demand for labor, and responds to changes in labor supply. He believes that some studies lean to overestimate the context of robot backup for labor and forget the robust complementarities between robotization and labor that rise productivity, increase earnings, and boost demand for labor. Autor [34] also argue in his study that the polarization is doubtful to go very far into the anticipated future. Arntz et al. [40] demonstrates that these pessimistic scenarios are exaggerating the portion of automatable jobs by ignoring the massive diversity of tasks within jobs as well as the versatility of jobs in the digital transformation. In order to support their proposal, they used detailed task data and declared that, when taking into accounting the spectrum of tasks within jobs, the robotization risk of US jobs decrease from 38 to 9%. Earlier studies have produced by Doms et al. concluded that based on the skill-biased nature of ICT that indicate skilled labor and ICT are complementary [43].

Autor and Salomons [41] has also concluded that systematic view of four different channels of how robotization may affect the employee market; ownindustry effects, between-industry, cross-country effects, and final demand effects. They stated that total factor productivity has negative direct effects on employment but positive indirect effects. In summary, the positive effects dominate and the long term outcome of robotization on employment is positive. They studied 24 OECD economies and stated that while displacing employment in the industries where it originates, automation generates indirect employment

growth in customer industries and rise in aggregate demand, finally bringing net employment growth [41].

Another optimistic study is made by Bresnahan et al. [42]; their study concluded that the competent labor is complementary with a group of three separate changes at the company level: information technology, new work organization, and new products and services.

In labor economics field, replacement of human work by AI and robots is fervently talked about. In any case, as indicated by Autor , robotization and mechanical advancement has not prompted the oldness of human work. Indeed, computerization and labor are exceptionally correlative and are partial to representatives that are versatile, ingenious, and arrangements situated [34].

Taking into account the former practices learned since the Industrial Revolution, Mokyr et al. argue that PCs and robots will make anew things and organizations and that these thing progressions will achieve impossible new occupations [45, 49].
