Institutional capacity to benefit from and adapt to technological advancements is, with regard to labor market productivity, at least on par with fundamental factors including wage level, education level, legislation, and market regulations. Artificial intelligence (AI) applications, in particular, symbolize the pinnacle of technological progress at present and represent the pinnacle of this process of transformation. Artificial Intelligence, which originated in the 1950s with the development of algorithms designed to simulate human intelligence, will have a significant impact on human existence in the near future, according to Stephen Hawking: "Artificial Intelligence will be the greatest revolution in the history of mankind." Regrettably, unless we discover methods to prevent it, it will also be the last. He aptly summarizes the situation as follows: " Productivity and total output are inversely proportional to the degree of active AI implementation in the labor market, according to a multitude of studies.
Notwithstanding the plethora of instances that positively illuminate the labor market, the agenda is occupied with pessimistic expectations for the near future. The cartoon that appeared on the October 2017 cover of The New Yorker magazine depicts humanoid robots traveling to work and presenting alms to a beggar. This particular cartoon effectively illustrates certain concerns that occupy the human mind regarding this subject. A comprehensive analysis of the relationship between human and machine labor, as well as the manner in which workers engage with sophisticated production machinery, is published in the same issue of the magazine. An analysis is conducted to determine the effects of actively implementing contemporary automation technologies in the manufacturing process. Additionally, the potential ramifications of technological advancements on the labor market are assessed (De Stefano, 2019). These analyses, which were carried out just prior to the advent of AI as a paradigm shift in technology, suggest apprehensions regarding the imminent consequences of technological advancements on the labor market.Labor market concerns regarding the adverse effects of technological advancements are not novel. Keynes (1937), whose seminal work is the formula for escaping the Great Depression, examines comparable issues in his pre-Second World War technological unemployment theory. Job loss is a recognized consequence of technological change in theory. At various phases of the industrial revolution, the relationship between technological advancement and the labor market is evaluated from various perspectives. The phases are categorized in the literature as follows: the First Industrial Revolution, which encompassed mechanical advancements like steam engines and railroads; the Second Industrial Revolution, which introduced economies to the concept of mass production; and the Third Industrial Revolution, which saw the introduction of computer and internet technologies. Subsequent to this, the integration of digital technologies into various facets of society's economic existence—including informatics, cloud infrastructures, big data technologies, wireless networks, the internet of things, AI-powered robots, smart factories, and cyber-physical systems—will occur naturally (Hepaktan & Ŗimşek, 2022; Othman, Bahrin, & Azli, 2016; Thames & Schaefer, 2017). This final stage, which is typically categorized as automation, is regarded as the zenith of AI technology's application in the labor and production markets. Presently, AI applications are regarded as the pinnacle of technological advancement in contemporary economies. Artificial intelligence (AI) encompasses a diverse array of technologies that are specifically engineered to empower machines with the capacity to perceive, interpret, act, and learn, thereby emulating the cognitive abilities of humans. To be more precise, it is a cutting-edge technology comprised of systems, including sophisticated complex language models, that are capable of generating novel content, ranging from text to images, through the process of learning from extensive training data. Certain more specialized AI models include pattern recognition capabilities. The rapid evolution of the expanding potential applications of AI is facilitated by the emergence of GenAI. Numerous researchers posit that this signifies an imminent expansion of the influence of AI, which will involve a reconfiguration of labor and business operations (Cazzaniga et al., 2024). Unavoidably, such assessments engender apprehensions among individuals regarding the trajectory of the labor market. With the implementation of AI, labor requirements are anticipated to be reduced to an absolute minimum, resulting in decreased error margins and production costs; conversely, output quality and efficiency are anticipated to increase. The complete implementation of the Fourth Industrial Revolution is anticipated to initiate a process of restructuring across numerous sectors, including education, communication, industry, and informatics (Akgül & Ayer, 2019).
Presently, economically significant occupations are being executed with superhuman efficiency by AI technologies. Certain occupations are linked to well-compensated professions, such as radiologists, while others are linked to unsalaried occupations, like agricultural laborers. The accelerating development of AI will eliminate the need for a vast array of occupational groups in contemporary economies, where rising inequality is a significant social and political issue. These groups include those engaged in agricultural labor and those in qualified professions such as lawyers and physicians. It is anticipated that this situation will exacerbate economic inequality (Webb, 2019). Technological advancements have an impact on both the wages and character of the labor force. The phenomenon under consideration is the result of skill-biased technical change, which can be described as a modification in manufacturing processes that prioritizes skilled labor over unskilled labor. This preference for skilled labor leads to an increase in quality-based productivity, subsequently generating a corresponding demand for skilled labor in comparison to unskilled labor (Violante, 2016). Whether positive or negative, the influence of AI on wages accelerates the 1980s-era upward trend of wage inequality. While the significance of gender and nationality attributes of the labor force diminishes, particularly in technological societies, wage disparities emerge among employed individuals and the educational attainment of distinct age cohorts assume prominence.Developed economies, characterized by their established service sectors and mature industries, have a greater concentration of employment in industries that primarily demand complex cognitive abilities, as stated in the IMF report. Hence, these economies are more vulnerable to advancements in artificial intelligence (AI) and are more positioned to gain advantages from such developments. Hence, despite the fact that developed nations utilize AI to gain a competitive edge, it is anticipated that it will exacerbate pre-existing economic disparities (Cazzaniga et al., 2024). Skills mismatches may result from the labor market's swift technological evolution propelled by AI. Employment in sectors with a high demand for new skills may be difficult to obtain for workers whose skills become obsolete, resulting in underemployment and social disruption. Labor force reductions caused by AI may exert a negative impact on compensation, particularly for those with limited skills.
References
Akgül, B., & Ayer, Z. (2019). Change in the Staff Structure of Media Institutions in Industry 4.0 Process. Route Educational and Social Science Journal, 6(8), 126-134.
Cazzaniga, M., Jaumotte, F., Li, L., Melina, G., Panton, A. J., Pizzinelli, C., . . . Tavares, M. M. (2024). Gen-AI: Artificial Intelligence and the Future of Work. Staff Discussion Notes, 2024(001).
De Stefano, V. (2019). ‘Negotiating the algorithm’: Automation, artificial intelligence and labour protection. Artificial Intelligence and Labour Protection (May 16, 2018). Comparative Labor Law & Policy Journal, 41(1).
Hepaktan, C. E., & ÅžimÅŸek, D. (2022). Industry 4.0 and the Future of the Labor Market. Ä°zmir Sosyal Bilimler Dergisi, 4(2), 80-88.
Keynes, J. M. (1937). The general theory of employment. The quarterly journal of economics, 51(2), 209-223.
Othman, F., Bahrin, M., & Azli, N. (2016). Industry 4.0: A review on industrial automation and robotic. J Teknol, 78(6-13), 137-143.
Thames, L., & Schaefer, D. (2017). Cybersecurity for Industry 4.0 and advanced manufacturing environments with ensemble intelligence. Cybersecurity for Industry 4.0: Analysis for Design and Manufacturing, 243-265.
Violante, G. L. (2016). Skill-Biased Technical Change. In The New Palgrave Dictionary of Economics (pp. 1-6). London: Palgrave Macmillan UK.
Webb, M. (2019). The impact of artificial intelligence on the labor market. Available at SSRN 3482150.