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Journal articles on the topic 'Technological unemployment'

Author: Grafiati

Published: 4 June 2021

Last updated: 30 July 2024

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1

Fiorelli, Federico. "Technological unemployment as frictional unemployment." Kybernetes 47, no. 2 (February 5, 2018): 333–42. http://dx.doi.org/10.1108/k-03-2017-0089.

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Purpose The purpose of this paper is to present some scenarios about a possible future evolution of the labour market in the knowledge economy. Design/methodology/approach The author used the literature to describe the historical evolution of the technology unemployment. Findings Digital technology does not directly generate unemployment, as the balance between jobs destroyed and created has historically always been positive. Indeed, technological unemployment in such a context can manifest itself in the form of frictional unemployment. Originality/value The study enriches the literature on the relationship between digital technologies and unemployment rate.

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2

Samuels, W. J. "The Technological Unemployment and Structural Unemployment Debates." History of Political Economy 31, no. 1 (March 1, 1999): 209–10. http://dx.doi.org/10.1215/00182702-31-1-209.

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3

Campa, Riccardo. "Technological Growth and Unemployment." Journal of Ethics and Emerging Technologies 24, no. 1 (February 1, 2014): 86–103. http://dx.doi.org/10.55613/jeet.v24i1.15.

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The aim of this article is to explore the possible futures generated by the development of artificial intelligence. Our focus will be on the social consequences of automation and robotisation, with special attention being paid to the problem of unemployment. In spite of the fact that this investigation is mainly speculative in character, we will try to develop our analysis in a methodologically sound way. To start, we will make clear that the relation between technology and structural unemployment is still controversial. Therefore, the hypothetical character of this relation must be fully recognized. Secondly, as proper scenario analysis requires, we will not limit ourselves to predict a unique future, but we will extrapolate from present data at least four different possible developments: 1) unplanned end of work scenario; 2) planned end of robots scenario; 3) unplanned end of robots scenario, and 4) planned end of work scenario. Finally, we will relate the possible developments not just to observed trends but also to social and industrial policies presently at work in our society which may change the course of these trends.

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4

Walker, Mark. "BIG and Technological Unemployment." Journal of Ethics and Emerging Technologies 24, no. 1 (February 1, 2014): 5–25. http://dx.doi.org/10.55613/jeet.v24i1.10.

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The paper rehearses arguments for and against the prediction of massive technological unemployment. The main argument in favor is that robots are entering a large number of industries, making more expensive human labor redundant. The main argument against the prediction is that for two hundred years we have seen a massive increase in productivity with no long term structural unemployment caused by automation. The paper attempts to move past this argumentative impasse by asking what humans contribute to the supply side of the economy. Historically, humans have contributed muscle and brains to production but we are now being outcompeted by machinery, in both areas, in many jobs. It is argued that this supports the conjecture that massive unemployment is a likely result. It is also argued that a basic income guarantee is a minimal remedial measure to mitigate the worst effects of technological unemployment.

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5

Fernández-de-Córdoba, Gonzalo, and Emma Moreno-García. "Union games: technological unemployment." Economic Theory 27, no. 2 (February 2006): 359–73. http://dx.doi.org/10.1007/s00199-004-0595-0.

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6

Boone, Jan. "Technological Progress, Downsizing and Unemployment." Economic Journal 110, no. 465 (July 1, 2000): 581–600. http://dx.doi.org/10.1111/1468-0297.00555.

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7

Kapeliushnikov, Rostislav. "The phantom of technological unemployment." Russian Journal of Economics 5, no. 1 (April 17, 2019): 88–116. http://dx.doi.org/10.32609/j.ruje.5.35507.

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Nowadays there are many gloomy prophecies provided by both technologists and economists about the detrimental effects of the so-called Fourth Industrial Revolution on aggregate employment and its composition. These prophecies imply that in the near future we will face Robocalypse — a massive replacement of people by machines alongside an explosion in joblessness. This paper provides theoretical, empirical and historical evidence that the phenomenon of technological unemployment is a phantom. The most general results can be summarized as follows: in the long run, reduction in labor demand under the impact of new technologies is merely a theoretical possibility that has never before been realized in practice; at the level of individual firms, there is a strong positive relationship between innovations and employment growth; at the sectoral level, technological changes cause a multidirectional employment response, since different industries are at different stages of the life cycle; at the macro level, technological progress acts as a positive or neutral, but not a negative factor; a surge in technological unemployment, even in the short-term, seems a remote prospect since in coming decades the pace of technological change is unlikely to be fast enough by historical standards; the impact of new technologies on labor supply may be a more serious problem than their impact on labor demand; technological changes seem to have a much greater effect on the composition of employment than on its level.

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8

Loi, Michele. "Technological unemployment and human disenhancement." Ethics and Information Technology 17, no. 3 (July 28, 2015): 201–10. http://dx.doi.org/10.1007/s10676-015-9375-8.

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9

Postel-Vinay, Fabien. "The Dynamics of Technological Unemployment*." International Economic Review 43, no. 3 (August 2002): 737–60. http://dx.doi.org/10.1111/1468-2354.t01-1-00033.

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10

Feldmann, Horst. "Technological unemployment in industrial countries." Journal of Evolutionary Economics 23, no. 5 (April 17, 2013): 1099–126. http://dx.doi.org/10.1007/s00191-013-0308-6.

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11

Beach, Earl F. "Technological unemployment – A Failure in Theorizing." Commentaires 31, no. 1 (April 12, 2005): 122–32. http://dx.doi.org/10.7202/028687ar.

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The subject of technological unemployment is used to illustrate how accepted theory leads to wrong answers because the technique used is that of partial equilibrium analysis. On this basis one rules out the investment needed to make the change in production method. In a dynamic context, in which such change continues, the employment effects of this investment should be allowed, and they can be seen to be substantial relative to the loss in employment from the installation of the new capital equipment. The result is that technological change conceived in this broad context is expansionary, and the implications for industrial relations and other policies is very important.

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12

Ivanova, Ol'ga. "TECHNOLOGICAL UNEMPLOYMENT: CONSEQUENCES OF DIGITAL TRANSFORMATION." Ergodesign 2022, no. 3 (September 7, 2022): 162–67. http://dx.doi.org/10.30987/2658-4026-2022-3-162-167.

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The study relevance is due to the fact that breakthroughs in IT and the massive spread of the Internet have begun to radically transform markets which were historically associated with offline businesses five to ten years ago. In this study, the author conducts an analysis of modern technologies and their impact on the economy. This allows coming to understanding that the trends associated with changing value chains, created by a person for many centuries is now being greatly modified thanks to new industrial technologies. The most noticeable macroeconomic consequences of the digital transformation as well as its impact on the labour market and unemployment are determined.

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13

VOLKOV, A. M., and R. M. SEYTKALIEV. "Technological unemployment and universal basic income." RUSSIA AND THE CONTEMPORARY WORLD, no. 4 (2021): 101–20. http://dx.doi.org/10.31249/rsm/2021.04.05.

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14

Aizenman, Joshua, and Pierre-Richard Agénor. "Technological Change, Relative Wages, and Unemployment." IMF Working Papers 94, no. 111 (1994): 1. http://dx.doi.org/10.5089/9781451853407.001.

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15

George, C. F. "Unemployment: technological causes, cures and consequences." IEE Proceedings A Physical Science, Measurement and Instrumentation, Management and Education, Reviews 135, no. 5 (1988): 313. http://dx.doi.org/10.1049/ip-a-1.1988.0051.

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16

Agénor, Pierre-Richard, and Joshua Aizenman. "Technological change, relative wages, and unemployment." European Economic Review 41, no. 2 (February 1997): 187–205. http://dx.doi.org/10.1016/s0014-2921(96)00020-7.

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17

Falkinger, Josef. "Technological Unemployment: A Note on Pasinetti." Journal of Post Keynesian Economics 10, no. 1 (September 1987): 37–43. http://dx.doi.org/10.1080/01603477.1987.11489657.

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18

Dalmazzo, Alberto. "Technological Complexity, Wage Differentials and Unemployment." Scandinavian Journal of Economics 104, no. 4 (December 2002): 515–30. http://dx.doi.org/10.1111/1467-9442.00299.

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19

Laura, Claudia, and Chaem Choi. "Do Technological Developments Increase Unemployment? Investigation Of Technological Developments, Education, Job Participation, And Unemployment In Thailand." Tamansiswa Accounting Journal International 4, no. 1 (January 31, 2022): 1–8. http://dx.doi.org/10.54204/taji/vol412022001.

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This study investigates technological developments, work participation, education, and unemployment where each variable is investigated carefully, especially the relationship between variables. In order to investigate the causal link between variables, this study employs a time frame of 21 years, from 2000 to 2020, and uses the autoregressive vector quantitative approach. This study uses secondary data from the world bank with the control variables being internet literacy, Economics participation, education, and unemployment in Thailand. We found that technological developments in Thailand do not threaten to increase unemployment. Where with the development of technology new jobs are created and the role of education in human capital investment becomes important in increasing human ability to master technology and use technology optimally so that technological developments also increase economic participation. Economic participation is an indicator of labor participation and employment.

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20

HUSIEV, Artem. "The problem of structural unemployment at the present stage of labour market development in Ukraine." Economics. Finances. Law, no. 4/1 (April 30, 2020): 6–9. http://dx.doi.org/10.37634/efp.2020.4(1).1.

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The article explores the theoretical and methodological basis of the problem of structural unemployment. The economic essence of the phenomenon has been identified, as well as the main reasons for its emergence in the context of globalization. The main types of structural unemployment are given: technological, territorial-industry. The relationship between the digitalization of business processes due to scientific and technological progress and the increase in the level of structural unemployment in the country has been revealed. The problem of structural unemployment in Ukraine at the present stage has been analyzed. The concept of public policy on structural unemployment has been proposed. Structural unemployment is a kind of unemployment, which arises as a result of structural changes in the economy of the country, exists under any economic system, its complete elimination is impossible. Depending on the reason for the emergence of structural unemployment is technological and geographically-sectorial unemployment. Technological unemployment is typical for highly developed countries with a high level of digitalization economy and is a consequence of automation of workplaces. Technological unemployment leads to transformations in the structure of demand for labor: withering some professions and the emergence of others. Such unemployment is a positive thing for the country's economy as a whole, so the main measures are to remove negative consequences of this unemployment for individual workers. In Ukraine, due to the relatively low rate of scientific and technological progress, the problem of technological unemployment, compared to developed countries, is less urgent. Geographically, the branch unemployment is caused by disproportions between supply and demand of manpower in certain areas or regions. In Ukraine and other countries with a transitive economy, this type of structural unemployment is more widespread. Balancing the demand and supply on the labor market at the mesoeconomic level is the main direction of the State policy on reducing the level of territorial and industry unemployment in Ukraine.

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21

Цихоцкий, М. А. "The Development of the Sixth Technological Order as a Factor of Technological Unemployment." Vestnik of Russian New University. Series "Man and society", no. 2 (April 28, 2023): 1–5. http://dx.doi.org/10.18137/rnu.v9276.23.02.p.048.

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Рассматриваются вопросы влияния нового витка технико-экономического развития общества на безработицу. Для этого обозначаются известные в настоящий момент характеристики нового технологического уклада, проводится обзор литературы по проблематике, проводится ретроспективный анализ влияния технико-экономического развития на безработицу. По итогам делается вывод, что в настоящий момент шестой технологический уклад перешел в фазу роста, на этом фоне происходит замещение ручного труда, то есть отмирание ряда профессий, что ставит остро проблему технологической безработицы. Технологическая безработица – не новое для мировой истории явление, исследователи выделяют две ее волны. В то же время для смягчения ее последствий предлагается ряд мер, помимо классических, можно обозначить безусловный базовый доход. This article discusses the impact of a new round of technical and economic development of society on unemployment. For this purpose, the currently known characteristics of the new technological order are indicated, a review of the literature on the problem is conducted, a retrospective analysis of the impact of technical and economic development on unemployment is carried out. According to the results, it is concluded that at the moment the 6th technological order has entered a growth phase, against this background there is a replacement of manual labor, i. e. disappearance of a number of professions, which poses an acute problem of technological unemployment. Technological unemployment is not a new phenomenon in world history, researchers identify at least two waves. At the same time, a number of measures are proposed to mitigate its consequences, in addition to the classical ones, an unconditional basic income can be designated

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22

Agarwalla, Aryaman. "HOW CAN TECHNOLOGICAL ADVANCEMENT LEAD TO UNEMPLOYMENT?" International Journal of Advanced Research 11, no. 09 (September 30, 2023): 1179–83. http://dx.doi.org/10.21474/ijar01/17632.

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My paper talks about how technological changes has both directly and indirectly impacted unemployment. I use secondary data and Microsoft Excel regression to form correlations between the two. These correlations help me reach to my conclusion about the effect technological changes has on unemployment in the economy.

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23

Koronowski, Adam. "Technological Progress and Unemployment: Luddism and Beyond." Gospodarka Narodowa 284, no. 4 (August 31, 2016): 5–22. http://dx.doi.org/10.33119/gn/100757.

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24

Peters, Michael A. "Beyond technological unemployment: the future of work." Educational Philosophy and Theory 52, no. 5 (May 7, 2019): 485–91. http://dx.doi.org/10.1080/00131857.2019.1608625.

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25

Vilaça, Murilo, Murilo Karasinski, and Jon Rueda Etxebarria. "Technological progress, unemployment and universal basic income." Enrahonar. An international journal of theoretical and practical reason 72 (March 19, 2024): 139–54. http://dx.doi.org/10.5565/rev/enrahonar.1543.

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As the world of technology increasingly intersects with humanity, one name stands out as a guide in this complex and ever-changing territory: James Hughes. In this interview, we had the opportunity not only to learn more about the author’s thinking and expertise, but also to explore the perspectives he brings on the technological future.

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26

Bennett, Jenny. "Skill-specific unemployment risks: Employment protection and technological progress – A cross-national comparison." Journal of European Social Policy 26, no. 5 (November 21, 2016): 402–16. http://dx.doi.org/10.1177/0958928716664294.

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This article focuses on the relationship between employment protection legislation (EPL) and skill-specific unemployment risks. As a consequence of skill-biased technological progress, low- and high-skilled workers are expected to be affected differently. Moreover, the level of technological progress should moderate the relation between EPL and skill-specific unemployment risks. The analyses are based on data from the Labour Force Survey from the year 2008 and concentrate on the civilian labour force aged between 25 and 49 years in 20 European countries. The results show that stricter EPL strengthens unemployment risks between skill groups only when the level of technological progress is very advanced. In other countries, stricter EPL is related to less inequality in unemployment risks. However, there are two sides to a coin. While stricter EPL is related to lower unemployment risks for the low skilled in most countries, it leads to higher unemployment rates for the highly skilled at the same time.

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27

Dzhunkeev, Urmat. "Modelling the impact of digital technologies on the unemployment rate in Russia." Moscow University Economics Bulletin, no. 6 (December 30, 2021): 186–201. http://dx.doi.org/10.38050/0130010520216.9.

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The paper examines labor market patterns in the light of digital economy development. The aim is to analyze labor market conjuncture in terms of registered unemployment dynamics. The degree of digital economy development is assessed through three indicators: the share of organizations using (1) the Internet, (2) local area networks, (3) number of personal computers per 100 employees. In addition to technological development indicators, the article also makes account of certain demographic factors. Since early 2000s, the degree of Internet penetration in organizations has doubled, while the number of computers increased threefold. The share of elderly population and life expectancy rate have increased by 5 percent and 7 years respectively. Drawing on econometric panel data models regarding federal districts in Russia for 2003–2019, the author provides the following findings. First, the proliferation of technological advances reduces unemployment rate. Second, an increase in the proportion of population above working age and life expectancy entails the reduction in unemployment rate. Third, combined effect of technological and demographic factors increases unemployment rate. The magnitude of the reduction exceeds the degree of increase in the unemployment rate due to technological advances. Thus, technological unemployment is more likely a theoretical possibility. Fourth, the determinants taken into consideration explain from 38 to 43 percent of unemployment rate change. The proposed approach can be applied in designing regulatory policies regarding employment with regard to the implementation of digital technologies in organizations and population aging in Russia’s regions.

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28

Kuzior, Aleksandra. "Technological Unemployment in the Perspective of Industry 4.0." Virtual Economics 5, no. 1 (April 6, 2022): 7–23. http://dx.doi.org/10.34021/ve.2022.05.01(1).

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The article concerns the problem of technological unemployment in the perspective of industry 4.0 development. The purpose of the article is to indicate the positive and negative effects of industry 4.0 development and to define the ways of programming education as a way to counteract the negative effects of industry 4.0 development. The author emphasizes the need for an appropriate education curriculum, aimed at acquiring both professional and engineering competences as well as humanistic, ethical and social competences at the same time. Technological unemployment is defined as a temporary, short-term phenomenon, lasting until human capital is shifted to other applications. The lack of adequate education, including lifelong learning, creates a risk of transition from technological unemployment to structural unemployment, which is much more dangerous for economic and social reasons. The article, therefore, contains an analysis of the labor market in terms of the demand for specific competences in the perspective of industry 4.0 development and forecasts of the demand for competences of the future. There is no doubt that the development of industry 4.0 requires specialized competences combining the skills of an IT specialist and an automation / robotics specialist who has skills in the field of cyber-physical systems integration, operation of advanced production management systems and complex production data analysis systems as well as the application of artificial intelligence algorithms in the production space. At the same time, however, specialists with high communication, interpersonal and social competences will be sought, hence there is a need for appropriate education curriculum.

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29

Mukoka, Shame. "On Technological Progress: Analysing Ricardo’s Theory on Unemployment." Journal of Economics, Trade and Marketing Management 4, no. 1 (May 21, 2022): p42. http://dx.doi.org/10.22158/jetmm.v4n1p42.

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30

Gajewska, Katarzyna. "Technological Unemployment but Still a Lot of Work." Journal of Ethics and Emerging Technologies 24, no. 1 (February 1, 2014): 104–12. http://dx.doi.org/10.55613/jeet.v24i1.16.

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This article explores the impact of both technological unemployment and a basic income on the provision of services of general interest. A basic income may promote the restructuring of production into postcapitalist forms and projects involving peer production. This change, as well as technological unemployment, will result in lower state and market capacities to provide services. Instead, people will create various forms of self-organization to meet their needs. The paper presents examples of such models. Some ideas about the new forms of inequalities in this system will be presented to inspire a further study of this scenario.

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31

Engelmann, Sabine. "Trade Liberalisation, Technological Change and Skill-Specific Unemployment." Journal of Global Economy 8, no. 3 (December 1, 2012): 197–224. http://dx.doi.org/10.1956/jge.v8i3.264.

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The aim of this paper is to formalise a two-country model of trade liberalisation and technological change with heterogeneous firms and search-and-matching frictions in the labour market. By considering different sectors and factors of production we allow for comparative advantages and study the trade and technology effects within and between sectors on wages and employment of skilled and low-skilled workers. Technological change together with inter-sectoral trade has distributional consequences across the labour force, favouring the skilled against the low-skilled workers. Intra-sectoral trade counteracts as it increases the demand for low-skilled workers, too. The overall effects on wages and employment of skilled and low-skilled workers depend on the extent of technological change, inter-sectoral trade and intra-sectoral trade.

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32

Fadinger, Harald, and Karin Mayr. "SKILL-BIASED TECHNOLOGICAL CHANGE, UNEMPLOYMENT, AND BRAIN DRAIN." Journal of the European Economic Association 12, no. 2 (January 28, 2014): 397–431. http://dx.doi.org/10.1111/jeea.12049.

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33

Prat, Julien. "The impact of disembodied technological progress on unemployment." Review of Economic Dynamics 10, no. 1 (January 2007): 106–25. http://dx.doi.org/10.1016/j.red.2006.09.003.

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34

MISHAN, E. J. "Technological Unemployment: Why There are Hard Times Ahead." Political Quarterly 67, no. 2 (April 1996): 151–57. http://dx.doi.org/10.1111/j.1467-923x.1996.tb01578.x.

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35

Faria, João Ricardo. "Entrepreneurship and business cycles: technological innovations and unemployment." International Entrepreneurship and Management Journal 11, no. 2 (June 6, 2014): 253–65. http://dx.doi.org/10.1007/s11365-014-0327-2.

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36

Walsh, Toby. "Expert and Non-expert Opinion About Technological Unemployment." International Journal of Automation and Computing 15, no. 5 (June 13, 2018): 637–42. http://dx.doi.org/10.1007/s11633-018-1127-x.

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37

Floridi, Luciano. "Technological Unemployment, Leisure Occupation, and the Human Project." Philosophy & Technology 27, no. 2 (May 6, 2014): 143–50. http://dx.doi.org/10.1007/s13347-014-0166-7.

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38

Peters, Michael A. "Technological unemployment: Educating for the fourth industrial revolution." Educational Philosophy and Theory 49, no. 1 (August 7, 2016): 1–6. http://dx.doi.org/10.1080/00131857.2016.1177412.

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39

Katselidis, Ioannis, Angelos Vouldis, and Panayotis G. Michaelides. "Sumner Slichter and Emil Lederer on technological unemployment." International Journal of Social Economics 38, no. 6 (May 10, 2011): 537–56. http://dx.doi.org/10.1108/03068291111131391.

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40

Stadler, Manfred, and Rüdiger Wapler. "Endogenous Skilled-biased Technological Change and Matching Unemployment." Journal of Economics 81, no. 1 (November 10, 2003): 1–24. http://dx.doi.org/10.1007/s00712-003-0014-1.

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41

Meckl, Jürgen. "Accumulation of technological knowledge, wage differentials, and unemployment." Journal of Macroeconomics 26, no. 1 (March 2004): 65–82. http://dx.doi.org/10.1016/j.jmacro.2002.09.003.

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42

Prokopowicz, Katarzyna. "Technological unemployment – who is afraid of losing their job to a robot?" Journal of Business Management 20 (2022): 118–29. http://dx.doi.org/10.32025/jbm22001.

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Objective: The study aimed to identify, analyse and assess the mood regarding the possibility of employees losing their jobs and being replaced with robots and regarding methods of preventing technological unemployment. Methodology: In March 2021, an online survey of a group of economically active adults in Poland (N=158) was carried out. Using the Internet, the standardised survey was addressed to people selected by the author. Results: The research has shown that employees are not afraid of losing their jobs, yet almost 90% of respondents plan to increase their competencies. People in managerial positions focus on developing cognitive and social competencies, while people in other positions plan to develop technical competencies. Research limitations: The research did not include unemployed and digitally excluded people. The research sample was selected by the author. Therefore, we do not extrapolate the results to the general public. Practical implications: The study shows that employees do not yet fully perceive the problem of technological unemployment. However, when planning their development, they learn independently or choose courses. Low interest in developing competencies in studies may signal that universities should make changes in their pedagogical offering. Novelty: Most research in the field of technological unemployment deals with the description of a business phenomenon or perspective. There is relatively little research on attitudes and reactions of human capital to the phenomenon of technological unemployment. Keywords: technological unemployment, competencies, human capital, Industry 4.0Classification:research paper

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43

Kapeliushnikov, R. "Is technological change a devourer of jobs?" Voprosy Ekonomiki, no. 11 (November 20, 2017): 111–40. http://dx.doi.org/10.32609/0042-8736-2017-11-111-140.

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The paper provides a critical analysis of the idea of technological unemployment. The overview of the existing literature on the employment effects of technological change shows that on the micro-level there exists strong and positive relationship between innovations and employment growth in firms; on the sectoral level this correlation becomes ambiguous; on the macro-level the impact of new technologies seems to be positive or neutral. This implies that fears of explosive growth of technological unemployment in the foreseeable future are exaggerated. Our analysis further suggests that new technologies affect mostly the structure of employment rather than its level. Additionally we argue that automation and digitalisation would change mostly task sets within particular occupations rather than distribution of workers by occupations.

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44

Çil, Melek, and Yildiz Yilmaz Guzey. "Technology and gender: Understanding the changing dynamics of female unemployment in the G7 countries." Journal of New Economy 25, no. 1 (April 5, 2024): 26–49. http://dx.doi.org/10.29141/2658-5081-2024-25-1-2.

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Technology has profound effects on labour market dynamics. Numerous studies have highlighted the unique opportunities and challenges that technological change presents to specific demographic groups. The aim of the study is to examine the long-term impact of technological changes within organisations on female unemployment at a macro level. From the perspective of the contingency approach and economic growth theories, the research conducts a panel cointegration analysis employing CCE-MG and AMG long-term panel cointegration estimators. The data on the female unemployment rate, the percentage of R&D expenditure in GDP and the ICT patents in total patents in the G7 countries for 1985–2020 is sourced from the OECD statistics. The analysis indicates the presence of an effect of technological change on the female unemployment rate as well as the national variations in their relationship. In particular, in three countries out of seven (Germany, the UK, the USA), there is the relationship between technological advancements and female unemployment. For the most part, increases in the percentage of R&D expenditure and ICT patents augment the female unemployment, though in Germany a rise in R&D expenditure leads to a decrease in it. The results will contribute to understanding the impact of technology-driven changes in organisations on gender-based labour inequality. The research highlights the complexity of the impact of technological advancements on the female employment and underscores the need for shaping related government policies by considering each country’s specific conditions.

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Danaher, John. "Sex Work, Technological Unemployment and the Basic Income Guarantee." Journal of Ethics and Emerging Technologies 24, no. 1 (February 1, 2014): 113–30. http://dx.doi.org/10.55613/jeet.v24i1.17.

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Is sex work (specifically, prostitution) vulnerable to technological unemployment? Several authors have argued that it is. They claim that the advent of sophisticated sexual robots will lead to the displacement of human prostitutes, just as, say, the advent of sophisticated manufacturing robots have displaced many traditional forms of factory labour. But are they right? In this article, I critically assess the argument that has been made in favour of this displacement hypothesis. Although I grant the argument a degree of credibility, I argue that the opposing hypothesis -- that prostitution will be resilient to technological unemployment -- is also worth considering. Indeed, I argue that increasing levels of technological unemployment in other fields may well drive more people into the sex work industry. Furthermore, I argue that no matter which hypothesis you prefer -- displacement or resilience -- you can make a good argument for the necessity of a basic income guarantee, either as an obvious way to correct for the precarity of sex work, or as a way to disincentivise those who may be drawn to prostitution.

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Semin, Alexander N., Egor A. Skvortsov, and Ekaterina G. Skvortsova. "Application of artificial intelligence and robot technologies in agriculture and assessment of their impact on rural unemployment." Economy of agricultural and processing enterprises, no. 9 (2022): 40–45. http://dx.doi.org/10.31442/0235-2494-2022-0-9-40-45.

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The growth of technological unemployment in the context of the massive use of robots and artificial intelligence is an urgent practice and scientific problem. The purpose of the study is to assess the impact of the use of artificial intelligence technologies and robotics on unemployment in agriculture. As research methods, screening of scientific literature on this issue and questioning of the expert group are used. The analysis and grouping of various scientific approaches to assessing the impact of artificial intelligence technologies and robotics on technological unemployment has been carried out. According to experts, the use of artificial intelligence and robotics technologies in agriculture will cause a cardinal impact on the industry (56.6% and 58.9%, respectively). At the same time, experts assess the possible increase in unemployment in rural areas as a result of the use of these technologies as insignificant (55.3% and 59.6% of all estimates). Specific recommendations are given to reduce the impact of the use of artificial intelligence technologies and robotics on technological unemployment, which consist in the need to improve the skills of workers, acquire unique skills for them, and create effective trade union organizations.

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Saner, Marc, and Wendell Wallach. "Technological Unemployment, AI, and Workplace Standardization: The Convergence Argument." Journal of Ethics and Emerging Technologies 25, no. 1 (June 1, 2015): 74–80. http://dx.doi.org/10.55613/jeet.v25i1.42.

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The current debate over technological unemployment sacrifices significant analytic value because it is one-sided, limited in scope, and sequential. We show that analyzing technological innovations in parallel with apparently independent socio-economic innovations and trends offers important analytical benefits. Our focus is on socio-economic innovations and trends that standardize education, workplace requirements, and culture. A highly standardized workplace is not only more suitable for international outsourcing; it is also more suitable for machine labor. In this context, we identify five specific research questions that would benefit from parallel analysis and scenarios. We also introduce the concepts “functional equivalency” and “functional singularity” (in juxtaposition to technological singularity) to provide semantic tools that emphasize the importance of an integrated approach, capable of tracking and analyzing two interacting and potentially converging trends.

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Weston, Anthony. "TECHNOLOGICAL UNEMPLOYMENT AND THE LIFESTYLE QUESTION A PRACTICAL PROPOSAL." Journal of Social Philosophy 16, no. 2 (June 1985): 19–30. http://dx.doi.org/10.1111/j.1467-9833.1985.tb00434.x.

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Aguilera, Andrés, and María Gabriela Ramos Barrera. "Technological Unemployment: An approximation to the Latin American Case." AD-minister, no. 29 (2016): 59–78. http://dx.doi.org/10.17230/ad-minister.29.3.

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Sargent, Timothy C. "Structural Unemployment and Technological Change in Canada, 1990-1999." Canadian Public Policy / Analyse de Politiques 26 (July 2000): S109. http://dx.doi.org/10.2307/3552506.

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