Global Wage Arbitrage vs. Algorithmic Arbitrage: How AI Rewrites Comparative Advantage in the Homework Economy

For almost 20 years, online assignment help has grown through outsourcing jobs from advanced economy countries to lower labour cost economies such as India, Kenya, Pakistan and the Philippines. Homework assistance has been increasingly outsourced (as an example) since the 1980s, along with essay writing, proofreading, basic tutoring for businesses and companies in advanced economy countries and their respective locations, and ultimately to those countries with similar economic environments to those of the U.S., U.K., etc.

In the past, the classic theory of wage arbitrage and the theory of comparative advantage have been used to obtain the maximum benefit from outsourcing. The factors listed above created a large pool of unskilled but English-speaking workers in these countries that allowed access to academic services at low prices but of lower quality than academics who offered the same service from developed countries for much higher premiums, which resulted in greater costs for consumers.

Three years ago, however, the evolution of the economic model in a micro-economy started to change how it functions. The continual drop in the cost of automating jobs via artificial intelligence has reached the point where low-wage jobs cannot compete against automation, even in countries with the lowest wages.

The transition from a wage arbitrage-based Economic Model to a Machine Algorithm-Based Economic Model represents new Economic Forces that are changing an entire Digital Labour Market, specifically within the Digital Services Sector. The changes from WAGE-BASED Arbitrage to Machine-Algorithmic-Based Arbitrage have raised substantial questions as to the impact of artificial intelligence on Comparative Advantage as well as Productivity Discrepancies between machines and humans.

Algorithmic Efficiency, Offshore...

In this blog, we'll talk about the impact of Offshoring on productivity, and also about how algorithms have enhanced the productivity of many of these companies. We are seeing many of the new online essay writing and tutoring service companies emerge today, particularly in the past ten years, as they compete with existing companies. For instance, in October 2020, the average cost of a writer based in the United States was $15-$30, compared to $5-$10 for a writer living outside of the United States. With this price differential, many companies have taken advantage of the opportunity to create products targeted at students that can benefit from them at a lower price-point, creating jobs for many low-wage workers in those countries. In fact, a survey from 2021 found that there are more than 20,000 people working either full-time or part-time in Essay Writing or Tutoring Services in Kenya. The increased demand for both tutoring and writing services during the peak periods of college semesters in the United States has resulted in the exponential growth of the Essay Writing and Tutoring Services industry in Kenya, and other countries with similar wage levels.

In summary, this model has survived and thrived because of the price disparity between the costs associated with hiring workers in developing nations as opposed to their counterparts in developed countries. According to the theory of comparative advantage, every country will continue to produce either a product or service that can be produced/exported efficiently.

With the introduction of Artificial Intelligence (AI), the theory of comparative advantage has been disrupted. Now that a model for writing essays, offering a solution for problems or explaining math concepts has been created, there is almost no incremental cost for creating more of the same. As a result, the incremental cost of making additional products using the model will continue to decline because only the cost of processing and the supporting costs of operating the model will remain for the production of future products.

The difference in cost is shocking.

For example, a worker in Kenya can produce an essay for $7, while a tutor in the Philippines can complete the same essay for $3. However, an AI model can generate an identical product for just a couple of pennies (processing cost) and will be produced nearly instantaneously. Furthermore, there are no longer any restrictions on the speed at which the additional products can be produced due to the limits of time, human fatigue and exhaustion, or any other hindrances experienced by humans.

A Comparative Advantage Shock: How Machines Compete With Nations

The long-standing principle of comparative advantage in international trade is based primarily on the differences in the levels of productivity of each country's labor force; yet today, thanks to Artificial Intelligence’s ability to take the place of human workers, companies can produce the same products in every country with far less human labor being expended. As a result, relative productivity levels for a vast majority of countries have converged. Simply put:

Machines produce the least-price goods in every country, meaning the use of machines will level the playing field concerning the respective comparative advantages of all nations.

This has serious consequences for:

Businesses operating in developing nations that have relied upon content moderators, search engine optimizers (SEO), beginner-level graphic designers, and writers (who would supply school assignments) have seen their demand surge and job postings decline dramatically with the advent of large language models since 2023. Emerging labor market reports show that the number of job postings for entry-level writers on major freelance websites has declined 15-30% in just three years. As a result, individuals who previously relied on workplace wage differentials as a means to compete now find themselves virtually competing at "zero marginal cost" due to the reality of AI-provided services, rendering their business models untenable.

Global Income Disparities and Export Losses

Displaced workers in the high-income nation are now able to afford very low-priced artificial intelligence products in place of very low-priced labour. Meanwhile, the low-income countries are going to lose all export revenue from providing digital services. Many displaced persons, who were relying on the opportunity of low-wage employment as writers and tutors based out of urban areas like Nairobi and Dhaka, will now lose those opportunities.

There are considerable parallels between the experiences of textile industry workers who became unemployed as a result of automation and the way digitalisation has displaced workers. However, the key difference today is that there are very few geographical barriers for the rapid distribution of jobs that have been displaced.

The Future—Complementarity Adaptation vs Last Mile Human Capital

In the long term, the question is whether all future displaced workers will be able to transition to complementary job roles (e.g., editing and verifying) as well as specialty tutoring, high-touch guidance, etc., or whether those types of roles will eventually be rendered obsolete by advancing technology. According to historical precedent, complementary roles are found where a high level of reliance on judgement, trust, and interpersonal relations is present, which suggests that the opportunity to develop these roles may be of very short duration.

Conclusion

The movement away from wage arbitrage globally to algorithmic arbitrage represents a fundamental change in how international labour economics operates. Not only does artificial intelligence reduce the demand for labour, but it also completely nullifies the comparative advantage enjoyed by low-skill digital employment. The primary challenge presented to developing economies by future displaced workers comes from identifying which human capital roles will be able to maintain defensible value, while policymakers need to recognise that, compared to historical patterns of displaced workers because of offshoring, future job displacements will be experienced globally, will have a transnational nature, and will exist within the context of a purely technology-driven environment.