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

Bonsay, Jamielyn; Cruz, Abigail P.; Firozi, Homa C.; Camaro, And Peter Jeff C.

doi:10.32996/jefas.2021.3.2.13

Cited by 6 publications

(3 citation statements)

References 27 publications

(42 reference statements)

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“…Lastly, Geethu J.A. and Sajini B. Nair's study on "ELDERLY DEPENDENCY in INDIA: FINDINGS from CENSUS DATA" examines the challenges posed by an aging population [8]. Through analyzing census data, the study explores the dynamics of elderly dependency, highlighting its consequences for population structure and economic development.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Analysis of Unemployment Rates Between China and India

Peng

2023

AEMPS

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This study examines the unemployment rate in two major developing economies, China and India, to forecast their economic trajectories. Through an autoregressive integrated moving average (ARIMA) model, this study analyzes historical trends and potential future scenarios that can help make informed decisions for sustainable growth. By evaluating the literature on the labor market, informal economy, demographics, and the impact of technology, this study enriches the understanding of these intricate economies. The study concludes that Chinas unemployment rate has remained stable, indicating an equilibrium, while Indias unemployment rate has fluctuated slightly, which may be due to health crises, technological shifts, and global trade dynamics. This study emphasizes the role of domestic policies, demographic and global economic factors in influencing unemployment rates. Overall, this study provides insights into the dynamics of unemployment in China and India, providing a valuable resource for policymakers, researchers, and businesses to understand the complexities of these economies.

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Section: Literature Reviewmentioning

confidence: 99%

Comparative Analysis of Unemployment Rates Between China and India

Peng

2023

AEMPS

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“…Therefore the answer lies in Keynesian economics The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale which was duly pointed out by Bonsay et al. (2021) suggesting that other economies being involved in AI utilization should focus on developing high standards of an educational system that covers a wide range of skills aligned to the new job creation rooted in technology and leverage this transformation to further enhance people's livelihood and income, as the continuous shift toward technological change is inevitable.…”

Section: Findings and Analysis Based Solutionsmentioning

confidence: 99%

“…Full-time job opportunities are decreasing day by day due to part-time and casual work (Chand et al, 2017). Over the years, as technology took part in driving India's economy, there is also job-deficient growth, rising farm distress and youths concerned for job reservations in the public sector, hence overall employment insignificance might be caused by AI displacing human labor in the services sector, making labor demand for predictable jobs shrink (Bonsay et al, 2021).…”

Section: Application Of Artificial Intelligencementioning

confidence: 99%

Application of artificial intelligence: benefits and limitations for human potential and labor-intensive economy – an empirical investigation into pandemic ridden Indian industry

Mukherjee

2022

MANM

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PurposeThis paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor.Design/methodology/approachThe research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally.FindingsA country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ”Research limitations/implicationsPrior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it.Practical implicationsThe AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government.Social implicationsThe answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale.Originality/valueA study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.

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