Artificial Intelligence: A blessing or a curse? What socio-economic challenges will humanity face in the next decades?

Artificial intelligence will be a blessing for humanity despite the many socio-economic challenges we’ll face in the coming decades. Artificial intelligence “is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy” (Stryker,2024). The recent boom of AI as the new breakthrough in technology in the 2020s has caused huge debates on whether this innovation is a blessing or a curse. AI will provide exponential growth towards the global economy, increasing labour productivity, and quality and saving time. However, the new technology will come at a cost with the disruption of labour markets. Due to the severity and magnitude of the labour market disruptions, there are likely to be many subsequent macroeconomic impacts like changes in regional and international distribution of incomes, and unemployment levels. This essay will argue that the benefit of long-term economic growth of AI will exceed the cost of short-term inequality and unemployment it will initially create.

Firstly, AI will increase productivity in the global economy increasing global GDP, therefore providing a higher global welfare. The use of AI will be integrated by “70%” (Bughin et al,2018) of companies by 2030. One example of this is in the healthcare sector whereby AI can “support clinicians with diagnosis, screening, prognosis, and triaging” (Capraro et al, 2024) which “improves diagnostic accuracy” (Capraro et al,2024). This can be seen with ChatGPT’s responses to medical questions being “higher quality and more empathetic than those of physicians 79% of the time” (Caparo et al,2024). Consequently, the acquisition of AI in the healthcare sector can relieve pressure off the workload, accompanying doctors but not replacing them and thus the increased productivity, ceteris paribus, will be a rightward shift in the supply curve in Figure 1, equaling the marginal social costs (MSC) from Q to Q1. This would cut down global waiting lists, improve the level of care in society, eliminating the deadweight welfare loss (the grey-shaded area) of the production of positive externalities of healthcare to allocative efficiency. Allocative efficiency would mean that employees would take fewer sick days off and be able to work for longer in their lives before retirement.

Figure 1: Positive Production Externality Model

The example in the healthcare sector is just one of many ways AI will improve the global economy in numerous sectors. The replacement of monotonous jobs substituting labour for capital could increase efficiency for allocating firms' factors of production, allowing employees to focus on more complex tasks. Thus, AI will “increase in labour productivity by up to 40%” (Szczepański,2019) and by enhancing worker productivity, firms can produce more goods and services so that their output per given input is greater. Hence, production costs are reduced in the long run, leading to increased potential profits. Furthermore, increased efficiency of a firm provides a further benefit: economies of scale, which are the cost advantages reaped by companies when production becomes more efficient and hence again leading to increased potential profits. This profit will be passed down to an increase in worker's wages as employees are more valuable to the firm increasing efficiency and AI being relatively inexpensive to implement, the prices of certain goods and services will likely reduce as well. These combined effects (lower prices and increased earnings) could, ceteris Paribus, increase aggregate demand (AD) which is shown in Figure 2.

Figure 2: Aggregate Demand & Keynesian Long Run Aggregate Supply Curve

Consequently, in the long term this will lead to an extension in aggregate supply, increasing real GDP from Y1 to Y2 which is adding “$15.7 trillion to the global economy in 2030” (Arnand et al, 2024). With this being the case, an expanding global economy boosts the demand for labour and creates opportunities for displaced workers to be re-employed in the long term. Ultimately with expanding economies, higher wages and lower prices, they lead to greater choice of goods and services for consumers so that they can maximise their utility, providing higher welfare to the global society in the coming decades.

However, in evaluation, this is only valid in certain industries. In many low-skilled professions within capital-intensive industries, like manufacturing, workers are becoming increasingly substituted for AI. Though the exact numbers are disputed since think tanks, companies and research institutes “prognostications are all over the map” (Winick, 2018) with estimations that “400 million to 800 million jobs worldwide could be automated by 2030” (Winick,2018) from a Mckinsey report to “2,000,000,000” (Winick,2018) jobs lost worldwide by 2030 from Thomas Frey. The “low-skilled workers would be worst affected” (Sillars, 2024) as workers have no other transferable skills to utilise in other jobs. This means many jobs are simply displaced, leaving workers unemployed and facing falling into the poverty cycle, further accentuating the “682 million” (Christensen,2023) already stuck in extreme poverty whereby it is nearly impossible to break out of.

Additionally, with unemployment on the rise government tax income and fiscal budgets will shrink. Firstly, the machines that replace humans do not pay income tax thus reducing the government tax income compared to when a human would have that job. Coupled with countries such as the UK with Universal credit, will see more people relying on government handouts due to the lack of job availability. Therefore, Universal credit will be a larger burden than before, which would divert the opportunity cost which could have been spent elsewhere, such as investing in the already struggling NHS. Overall, AI sees a “polarization within income brackets” (Georgieva, 2024), accentuating financial inequality while eroding the public sector.

Moving on, The arrival of AI motivates competition among firms. A competitive society offers multiple advantages, as it creates an environment where firms must innovate to survive and thrive. As a result, firms will increase their investment in capital goods, which initiates the multiplier effect. The multiplier effect occurs when an initial rise in investment leads to a proportionately larger increase in Gross Domestic Product (GDP). Moreover, capital investment is a component of aggregate demand. Hence, ceteris paribus, an increase in capital expenditure directly boosts aggregate demand, resulting in again an increase in actual economic growth revealed by the increase in GDP of “$15.7 trillion to the global economy in 2030” (Arnand et al, 2024).

However, in evaluation, the economic growth will only be reaped by the more economically developed countries such as North America, China and Europe which can access Artificial intelligence. Whereas less economically developed countries in Latin America, Africa and Oceania will lag even further. This is because developed Asia will see an increase of “%26.1” (Arnand et al, 2024) in GDP whilst Africa, Oceania and other Asian markets only see a “%5.6” (Arnand et al, 2024) increase in GDP by 2030. Less developed countries will struggle as their workforce is labour-intensive and low-skilled compared to countries such as the U.S. Consequently, there could be mass unemployment leading to a further disparity of income between countries, Therefore “worsen overall inequality” (Georgieva,2024) as the gap between the developed and less developed world expands.

To combat labour displacement, policies must be put in place so that, firms can “redeploy displaced workers” (Sharps, 2024) from AI to alleviate the socio-economic impact of layoffs. An example of this is Amazon which is increasingly becoming more automated using AI and robotics on their assembly lines replacing low-skilled workers. Amazon has invested “$ 1.2 billion” (Amazon staff, 2024) in workforce training programs for “300,000 employees” (Amazon staff,2024) in the U.S. They are trained in the Technical skills academy to be able to work in other sectors of the company such as a Technical apprenticeship, Mechatronics and robotics apprenticeship, and User experience design and research Apprenticeship. Therefore, if firms like Amazon are willing to train the replaced human labour in areas that AI has limitations in, such as creativity, judgement and common sense, there will be less socio-economic damage to low-skilled workers.

To conclude, AI is a blessing to achieve unprecedented socio-economic for decades to come. The long-term benefits of AI of increased labour productivity, further innovation, and higher global welfare can outweigh the short-term costs. Investments in workforce reskilling, policies to address inequality, and initiatives like those implemented by companies such as Amazon need to be at the forefront of this new era to mitigate job displacement and therefore foster inclusive growth. If societies can cross the bridges of AI adoption, the technology will prove to be more of a blessing than a curse, propelling humanity toward a more prosperous and innovative future in the next decades.