Written by Advay Singh
Artificial intelligence (AI), is a rapidly expanding field, often considered the fourth industrial revolution (Li et al., 2023). Taking automation to the next level, it’s hardly an inconspicuous innovation. Its impacts on several disciplines garner praise as well as criticism; there are many conflicting viewpoints of the impact of AI on the economy. Economics has several subfields. The subfields’ importance is determined by the viewer in question. As such, there are simply far too many economic aspects necessitating analysis. Nonetheless, an economic segment, the labor market, is of importance to virtually the entire human population. Furthermore, AI has a considerable effect on the labor market. Therefore, the question arises: what are the impacts of the rapid expansion of AI on the labor market?
Briefly, AI is the usage of statistical methods to generate a multitude of predictions relating to the task at hand. Additionally, the labor market is the supply and demand for labor. It encompasses two noteworthy entities: suppliers and demanders. The suppliers, in this case, are the laborers while the demanders are firms seeking said laborers.
Koo et al. conducted a sequential study comprising surveys on hotel workers in the U.S. to analyze job insecurity (the anticipation of an event relating to involuntary loss of one’s job). They discover that job insecurity is heavily linked to aspects of self-determinism: “a quality of human functioning that integrates intrinsic/extrinsic motivations based on one’s capacity of choices” (Koo et al., 2021). Workers with external determinations tend to have increased job insecurity, often concluding that rather than a substitute, AI should serve as a complement to jobs in the hospitality sector. Workers should be provided learning opportunities in which they are better equipped to employ contemporary technology. They endorse that appropriate incorporation of AI in firms has a meager impact on the demand curve. Its data collection capabilities are advantageous for firms; reacting to newly discovered data can help them improve their services, a task which may even increase the demand for laborers. However the labor market for the hospitality sector doesn’t remain stationary: many externally determined workers rejecting the idea tend to have negative expectations for future stability, decreasing the labor supply. This perpetuates the addition of AI and may cause a shortage of jobs.
Amusingly, some argue that there are more jobs being created than lost. Mustafa Ergan, a scholar at the Istanbul Technical University, decodes AI, highlighting the chronicles of AI and its impact. Ergan claimed that “AI will create more jobs than it will destroy” (Ergan, 2019). He bases his claim off of a Forbes statistic illustrating that while 85 million jobs will be replaced by AI by 2025, 97 million jobs will be created. This corresponds to a rightward supply shift. This newfound labor shortage necessitates increasing wages. I.e., if Ergan’s claim is reflective of the job market, real-world firms not only demand more workers, but recompense them more handsomely thanks to AI.
Opponents of AI argue that there is, in fact, a labor surplus (Au-Yong-Oliveira et al., 2019) and it’s disproportionately affecting different jobs. In their secondary research study, Au-Yong-Oliveira et al. analyze factors such as skill-level and location and their relation to AI’s impact on the labor market, proposing fascinating ideas. Because low-skilled jobs, requiring a far simpler automation process, are more susceptible to succumb to a decrease in labor demand. The consequence: a surplus of workers and increased unemployment. Additionally, workers will receive even smaller wages. Since higher-skilled jobs are likely to see the opposite effect (i.e worker shortage leading to a wage increase), further escalating the socioeconomic gap. Despite this, from a normative economics perspective, Au-Yong-Oliveira et al. concur that automation is advantageous for future society. This is likely due to the myriad of benefits AI offers super specialized positions.
In comparison, super specialized jobs, even those aligning with stereotypical AI capabilities, perceive AI as assurance rather than replacement. Pancreatic cancer imaging is one of various dealing in radiology, a field heavily discussed in tandem with AI’s impact on the labor market. To gauge field specialists’ attitudes in said discussion, a study was conducted by (Chu et al., 2023) proposing a survey, comprising binary, quantitative, and qualitative questionnaires, to radiologists of all ages and demographics, discovering several noteworthy spectacles; only 8% of them credited AI as capable of their job replacement (Chu et al., 2023). Rather than insecurity, their primary concern is the advancement of AI technologies, believing it leads to the betterment of their professionalism. Radiologists’ views directly counteract those of an externally motivated hotel employee because their perceived job security is much greater.
Additionally, prerequisites relating to classification accuracy etc. largely explain why only 30% of medical professionals and radiologists currently employ AI in their tomographic practices (Chu et al., 2023). This figure being less than expected is due to the fine tuning required prior to making AI more ubiquitous and the costs associated with AI’s development and maintenance. The former is actually favorable for the labor market; more fine tuning requires more machine learning (ML) engineering, expanding the associated labor force. The latter however, is more complicated. “39% of respondents reported cost… as serious potential drawbacks of workplace AI integration” (Chu et al., 2023). Bearing this in mind, do firms benefit from AI?
With results opposing Chu et al., Li et al.’s study, conducts an empirical regression analysis on 3185 enlisted Chinese companies’ innovation efficiencies. Li et al.’s study delves further into wider-scoped company logistics, unlike Chu et al. who were focused more on individual laborer expectations, which allows for factoring in the marginal social benefit of AI innovations. Li et al. presents the economic impacts on firms being a result of AI as net benefits rather than marginal costs, providing a more holistic analysis. This generates a more reliable stat regarding AI’s impact on firm level economics. Explaining that “The increased efficiency of resource reallocation within the firm improves the match between supply and demand, reduces the possibility of innovation failure, and thus increases corporate innovation efficiency.” It’s implied by Li et al. that increased efficiency makes up for the cost, even adding to the companies’ benefits. Notably, this benefit stands more conspicuously in companies with larger, lower skilled labor force ratios.
It is denoted that at its current capabilities, AI serves as an accessory to most jobs and only jeopardizes extremely low skilled jobs. Nonetheless, it’s certain that the cost has gone down, and within no time the efficiency of the AI will rapidly increase and severely assist those in more specialized and higher positions, generating much revenue. A likely increase in overall consumer and producer surplus is likely to occur as a result of this despite some labor shortage in lower-skilled professions.
Works Cited
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Areia, M., Mori, Y., Correale, L., Repici, A., Bretthauer, M., Sharma, P., … & Hassan, C. (2022). Cost-effectiveness of artificial intelligence for screening colonoscopy: a modeling study. The Lancet Digital Health, 4(6), e436-e444.
Au-Yong-Oliveira, M., Canastro, D., Oliveira, J., Tomás, J., Amorim, S., & Moreira, F. (2019). The role of AI and automation on the future of jobs and the opportunity to change society. In New Knowledge in Information Systems and Technologies: Volume 3 (pp. 348-357). Springer International Publishing.
Chu, L. C., Ahmed, T., Blanco, A., Javed, A., Weisberg, E. M., Kawamoto, S., … & Fishman, E. K. (2023). Radiologists’ Expectations of Artificial Intelligence in Pancreatic Cancer Imaging: How Good Is Good Enough?. Journal of Computer Assisted Tomography, 10-1097.
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Li, C., Xu, Y., Zheng, H., Wang, Z., Han, H., & Zeng, L. (2023). Artificial intelligence, resource reallocation, and corporate innovation efficiency: Evidence from China’s listed companies. Resources Policy, 81, 103324.
Koo, B., Curtis, C., & Ryan, B. (2021). Examining the impact of artificial intelligence on hotel employees through job insecurity perspectives. International Journal of Hospitality Management, 95, 102763.
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