Artificial Intelligence and Labor Productivity Paradox: The Economic Impact of AI in China, India, Japan, and Singapore

2021 ◽  
Vol 3 (2) ◽  
pp. 120-139
Author(s):  
Abigail P. Cruz ◽  
Homa C. Firozi ◽  
Jamielyn Bonsay ◽  
And Peter Jeff C. Camaro
Keyword(s):  
Artificial Intelligence ◽  
Labor Productivity ◽  
Unemployment Rate ◽  
High Tech ◽  
Foreign Direct Investments ◽  
Technological Unemployment ◽  
Jobless Growth ◽  
Increase Productivity ◽  
The Relationship ◽  
New Jobs

Artificial intelligence is designed to generate technologies that potentially increase productivity and economic welfare. This study analyzes the relationship between GDP and high-technology exports, GDP per person employed, and unemployment rate in China, India, Japan, and Singapore. Recent concerns on technological unemployment claim that artificial intelligence disrupts the labor market which decreases employment over time. Using the multiple regression analysis, this study proved that Japan comparatively has better utilization of AI and labor productivity as all independent variables show significance to the GDP. Labor productivity in all countries is positively related to GDP. However, China and India showed signs of improper AI utilization as technological unemployment occurred. The unemployment rate in China is insignificant to its GDP, while India's unemployment rate is positively related to GDP, hence the jobless growth. In Singapore, the insignificance of high-tech exports to GDP is due to its lack of R&D investments these recent years. The results suggest that AI escalates growth through proper utilization trade liberalization, as exercised by Japan, as it helps the economy to be open and flexible to various free trade agreements which facilitates technological progress and enables the opening of new markets for growth and expansion, especially of artificial intelligence, which attracts and encourage foreign direct investments that will cater technology transfer, creation of new jobs, and economic growth.

INTERCONNECTION BETWEEN GLOBAL SUPPLY CHAINS AND INDUSTRY

2021 ◽  
pp. 6-11
Author(s):  
Alexander N. Bryntsev ◽  
◽  
M.A. Bykova ◽  
Keyword(s):  
Artificial Intelligence ◽  
Supply Chains ◽  
Automotive Industry ◽  
Industrial Production ◽  
High Tech ◽  
Global Supply Chains ◽  
Global Competition ◽  
Macroeconomic Analysis ◽  
The Relationship

In the article, the authors consider the issues of the relationship between global supply chains and industrial production of semiconductors in modern conditions. Particular attention is paid to the applied value of the application of artificial intelligence technologies in industry in the light of the growth of global competition. Their specific features, strengths and weaknesses are shown. A brief macroeconomic analysis of the development of markets for robotics, the automotive industry, high-tech products, as well as modern regulations on the eve of a new technological order is given.

scholarly journals Analysis of the Impact Fiscal Fundamentals on Unemployment in Nigeria. Imperatives for Covid 19, Era

2021 ◽  
Vol 04 (05) ◽  
Author(s):  
Patrick Ologbenla ◽  
Keyword(s):  
Unemployment Rate ◽  
Government Expenditure ◽  
Research Work ◽  
Youth Unemployment ◽  
Government Revenue ◽  
Increase Productivity ◽  
Employment Generation ◽  
The Impact ◽  
The Relationship

The study examined the impact of fiscal fundamental on unemployment rate in Nigeria from 1980 to 2020 focusing on COVID-19 imperatives. The research work embraces OLS estimating techniques to estimate the relationship between the variables. The result of the analysis revealed that government expenditure had positive and significant effect on the rate of unemployment. Also government revenue had a positive but insignificant impact on unemployment during. The implication of these findings for COVID-19 is that the narrative which is obtained from the analysis needs to be changed. Government revenue should be made to have significant impact on unemployment. The pandemic has led to a lot of job lost and the unemployment rate in Nigeria has risen by about 55% peaking at 36% youth unemployment rate as at last quarter of 2020. The study therefore, recommends that government should refocus expenditure and revenue in the country in such a way it will target development of infrastructural facilities so as to increase productivity and in turn facilitate employment generation.

Stepping back to move forward: Centering capital in discussions of technology and the future of work

2020 ◽  
Vol 5 (3-4) ◽  
pp. 129-133
Author(s):  
Benjamin Shestakofsky
Keyword(s):  
Artificial Intelligence ◽  
New Technologies ◽  
Technological Development ◽  
Structural Features ◽  
Robotic Systems ◽  
Future Of Work ◽  
Technological Unemployment ◽  
The Future ◽  
Constructivist Approaches ◽  
The Relationship

Some researchers have warned that advances in artificial intelligence will increasingly allow employers to substitute human workers with software and robotic systems, heralding an impending wave of technological unemployment. By attending to the particular contexts in which new technologies are developed and implemented, others have revealed that there is nothing inevitable about the future of work, and that there is instead the potential for a diversity of models for organizing the relationship between work and artificial intelligence. Although these social constructivist approaches allow researchers to identify sources of contingency in technological outcomes, they are less useful in explaining how aims and outcomes can converge across diverse settings. In this essay, I make the case that researchers of work and technology should endeavor to link the outcomes of artificial intelligence systems not only to their immediate environments but also to less visible—but nevertheless deeply influential—structural features of societies. I demonstrate the utility of this approach by elaborating on how finance capital structures technology choices in the workplace. I argue that investigating how the structure of ownership influences a firm’s technology choices can open our eyes to alternative models and politics of technological development, improving our understanding of how to make innovation work for everyone instead of allowing the benefits generated by technological change to be hoarded by a select few.

scholarly journals The ideology of information and computer technology as a vector of development of intellectual resources in a digital society

2019 ◽  
Vol 31 (1) ◽  
pp. 84-88
Author(s):  
N. Kirichenko
Keyword(s):  
Artificial Intelligence ◽  
Human Resources ◽  
Computer Technology ◽  
High Tech ◽  
The Internet ◽  
Digital Society ◽  
Technological Unemployment ◽  
Computer Technologies ◽  
Information And Computer Technology ◽  
The World

The relevance of the study of this problem is that information and computer technologies contribute to the development of digital society, based on the development of human resources that are intellectual capital.  Information and computer technology affect the development of machines that replaced people and gave rise to "technological unemployment."  The purpose of the study is to show how the information revolution of the twenty-first century contributes to the reduction of labor as a result of progressive robotization.  The technologies that are used today to replace people are different; the need for human resources is reduced thanks to robots, computers and other high-tech gadgets.  Methods of theoretical analysis - deduction and induction, historical and logical, comparative and structural-genetic analysis, information method, which contribute to the insight into the essence of the phenomenon under study as a complex phenomenon and dynamic process.  Results: It has been proven that, thanks to various well-known developments in information-computer technologies and robotics, many experts believe that society is at an early stage of the new industrial (post-industrial) revolution, which in the future can change the way people live and work just like  200 years ago made a steam engine.  Technological unemployment is one of the main reasons for the increase in the overall unemployment rate in Western countries over the past 30 years.  Although to some extent this is due to the demographic revolution and the changing structure of the economy in many countries, the development of information and computer technologies, as well as other types of automation and the Internet have played a significant role, especially since 2000.  Findings.  We have shown that many jobs with cheap labor can disappear, because the digital society focuses on the development of human (intellectual) resources.  The world is turning into a digital society and the world is ruled by a figure based on intelligence, intelligence, algorithms, digitalization.  The digital society consists of a set of algorithms that are controlled by information and computer technologies that penetrate digital management, which is based on intellectual-rational force represented by human resources.  It is human resources that develop robotics, artificial intelligence, computerization, mechanization, robotization, which are based on robotics, artificial intelligence.  These varieties of digital society will accelerate the potential for long-term productivity gains through intellectualization.  Practical recommendations - to develop a small business that rests on the network of intelligent platforms, in connection with which to create jobs on the Internet and create new types of employment.

Technological unemployment as frictional unemployment

Kybernetes ◽  
2018 ◽  
Vol 47 (2) ◽  
pp. 333-342 ◽  
Author(s):  
Federico Fiorelli
Keyword(s):  
Unemployment Rate ◽  
Knowledge Economy ◽  
Digital Technology ◽  
Design Methodology ◽  
Digital Technologies ◽  
Historical Evolution ◽  
Content Type ◽  
Future Evolution ◽  
Technological Unemployment ◽  
The Relationship

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.

scholarly journals Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Heidi Aly
Keyword(s):  
Artificial Intelligence ◽  
Developing Countries ◽  
Economic Development ◽  
Labor Productivity ◽  
Developed Countries ◽  
Digital Transformation ◽  
Future Research ◽  
Content Type ◽  
The Impact ◽  
The Relationship

Purpose The entire world is now witnessing the Fourth Industrial Revolution and Artificial Intelligence (AI) is indeed altering the lives of the many in both developing and developed countries. Massive digital transformations are affecting the economies of those countries and are bringing with them many promised merits, as well as many challenges to face. This paper aims to examine the relationship between digital transformation (as a one facet of the fourth revolution and AI trends) on one side, and economic development, labor productivity and employment on the other side. Design/methodology/approach The paper analyzes different indices of digital transformation, and then uses the Digital Evolution Index (DEI) to study those relationships in a group of developing countries using feasible generalized least squares method (FGLS). Findings The results show a positive relationship between the digital transformation index and economic development, labor productivity and job employment. Females seem to gain more from digital transformation compared to males, as suggested by the positive relation with the first and the insignificant relation with the latter. The relationship with vulnerable employment is not significant; more evidence is still needed to judge whether digital transformation will have an impact upon the vulnerable employees in the economy. Research limitations/implications The paper focused on the impact of digital transformation upon total aggregate employment. Future research is still needed to examine the impact upon the structure of the labor market and the shift of occupations. Originality/value The paper aims to add to in the literature regarding the relationship between digital transformation, economic development, employment and productivity in the developing world. The implications of those relationships are of significant importance to policymakers regarding how much support should be given to encourage the digital transformation. At the same time, it shall also indicate how much social support policies are required – if any – to lessen the negative impact of digital transformation on the vulnerable groups inside the country. Another contribution is using a single composite index for digital transformation that is comparable across the chosen set of developing countries, instead of using single indices each capturing a different dimension of digital transformation.

scholarly journals Do foreign direct investments and bank credits affect employment in Uzbekistan?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alisher Suyunov
Keyword(s):  
Time Series ◽  
Unemployment Rate ◽  
Absorptive Capacity ◽  
Creative Industries ◽  
Empirical Literature ◽  
Foreign Direct Investments ◽  
Economic Time Series ◽  
Economic Sectors ◽  
Content Type ◽  
The Relationship

PurposeThe paper investigates the relationship between credit to the economy, foreign direct investment (FDI) and the unemployment rate in Uzbekistan using macroeconomic time series over 2004–2019.Design/methodology/approachThe study estimates the relationship by applying a vector autoregression model, which is considered a “workhorse” model for policy analysis to capture dynamic relationships in economic time series.FindingsThe results suggest both growth in credit to the economy and FDI Granger cause a change in the unemployment rate. The authors found 1% increase in bank credits to the economy growth decreases the unemployment rate by 0.096 pp. over eight years. On the contrary, 1% positive shock to FDI growth increases the unemployment rate by 0.0036% in the context of Uzbekistan.Practical implicationsUzbekistan should improve FDI absorptive capacity, particularly human capital and financial market development, through growth-enhancing structural reforms in the financial sector to stimulate economic growth and employment. The attracted FDI funds should focus on productive and economic sectors with high labor-absorptive capacity, such as financial and professional services, healthcare and biomedicine, creative industries and media, software sector.Originality/valueThe study contributes to the empirical literature on employment effects of FDIs and credit to the economy of Uzbekistan.

scholarly journals The Future of Work in a Jobless Society: Globalization, Smart Digitalization, and Cognitive Automation

2021 ◽  
Vol 92 ◽  
pp. 07016
Author(s):  
Irina Dijmărescu ◽  
Luminița Ionescu
Keyword(s):  
Artificial Intelligence ◽  
Value Added ◽  
Comparison Analysis ◽  
New Era ◽  
Future Of Work ◽  
The Future ◽  
Cognitive Automation ◽  
Increase Productivity ◽  
Near Future ◽  
New Jobs

Research background: The future of work is undoubtedly one of the toughest challenges faced by many researchers and managers all over the word. The new era in digital globalization and smart digitalization, the trends in robotization and artificial intelligence have changed the labour market. Due to accelerated technology, many companies are ready to adopt digital solutions, stationary robots and drones with significant consequences over the declining jobs. The new human-machine frontier will determine a different outlook work in a jobless society, where many roles become automated, while human’s role in these processes is minimized. Purpose of the article: In our opinion, globalization and impact of artificial intelligence on the future of work will be significant. In this paper we try to analyse and clarify the issues in question in terms of smart digitalization, cognitive automation, human-machine frontier and changing employment types. The data used for this research was obtained from previous study conducted by World Bank and OECD. Methods: In order to fulfil our goal, we apply the methods of comparison, analysis, deduction and our estimates for identifying the trends that are shaping the future of jobs and the evolution of jobs caused by technological change. Findings & Value added: In the near future, innovation will continue to accelerate and many artisan jobs are being lost to computerization and office automation. Finally, we formulate our own conclusion and view about digitalization and opportunities to create new jobs, increase productivity, and cost reduction, through innovation and accelerating change.

scholarly journals Hybrid Artificial Intelligence HFS-RF-PSO Model for Construction Labor Productivity Prediction and Optimization

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 214
Author(s):  
Sara Ebrahimi ◽  
Aminah Robinson Fayek ◽  
Vuppuluri Sumati
Keyword(s):  
Artificial Intelligence ◽  
Labor Productivity ◽  
The Other ◽  
Swarm Optimization ◽  
Factors Affecting ◽  
Novel Approach ◽  
Study Results ◽  
Productivity Prediction ◽  
Hybrid Artificial Intelligence ◽  
The Relationship

This paper presents a novel approach, using hybrid feature selection (HFS), machine learning (ML), and particle swarm optimization (PSO) to predict and optimize construction labor productivity (CLP). HFS selects factors that are most predictive of CLP to reduce the complexity of CLP data. Selected factors are used as inputs for four ML models for CLP prediction. The study results showed that random forest (RF) obtains better performance in mapping the relationship between CLP and selected factors affecting CLP, compared with the other three models. Finally, the integration of RF and PSO is developed to identify the maximum CLP value and the optimum value of each selected factor. This paper introduces a new hybrid model named HFS-RF-PSO that addresses the main limitation of existing CLP prediction studies, which is the lack of capacity to optimize CLP and its most predictive factors with respect to a construction company’s preferences, such as a targeted CLP. The major contribution of this paper is the development of the hybrid HFS-RF-PSO model as a novel approach for optimizing factors that influence CLP and identifying the maximum CLP value.

Supporting Employment and Improving the Efficiency of the Labor Market to Ensure Productivity Growth in the Tula Region

2021 ◽  
Vol 9 (2) ◽  
pp. 15-20
Author(s):  
M. Bykova ◽  
Irina Savina ◽  
Andrey Shishkin
Keyword(s):  
Labor Market ◽  
Retrospective Analysis ◽  
Labor Productivity ◽  
Unemployment Rate ◽  
Productivity Growth ◽  
State Policies ◽  
Regional Level ◽  
Factors Affecting ◽  
The Relationship

The paper provides a retrospective analysis of the relevance of the productivity issue. Various approaches to the possibility of increasing this indicator at the regional level based on the identification of various factors are considered. An analysis of projects devoted to increasing labor productivity in the Tula region and contributing to supporting employment was carried out. The need to use employment indicators as factors affecting productivity is justified. An analysis of the relationship between regional and state policies in support of employment in the region and the main indicators of the unemployment rate was carried out. On the example of the Tula region, the need for sectoral analyses in order to identify advanced industries at the regional level is justified. Optimization of programs at both regional and federal levels is proposed, taking into account the needs of advanced industries in the field of training.

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