Artificial Intelligence and Employment: Does the rise of Artificial Intelligence cause a fall in employment and earnings?

The answer is not straight forward, which is why “it depends” is a frequently used phrase by economists for many questions pertaining to AI. For people involved in operations which are repetitive and which can be learned by an algorithm, the future may be less bright.

Artificial intelligence is making its way into almost every industry, from McDonalds introducing self serving kiosks to sophisticated robots being trained to perform surgeries. This is good news for many firms as AI has caused a startling rise in efficiency. The benefits include AI tools not only being able to work longer hours (24/7) but also with lower error rates than humans. For example, in a study conducted by the National Bureau of Economic Research it was found that customer support agents using a generative pre-trained transformer (GPT) AI tool saw a nearly 14% increase in their productivity. This benefits a wide spectrum of professions, industries, businesses, and skill sets — from healthcare professionals and legal experts who analyse and disseminate information on medical and legal matters to craftsmen like carpenters and plumbers who design and execute practical solutions. AI also impacts various administrative, managerial, and clerical roles such as project management, human resources, and financial management. A report by Goldman Sachs states that for many companies, there will be cost savings thanks to AI. They can deploy these surplus resources toward building and growing businesses, ultimately increasing annual global GDP by 7%.

However the rise of AI is a double edged sword. The same report by Goldman Sachs states that over 300 million jobs could be lost to automation around the world. So which are the professions at risk?

Here the answer is contrary to past experience with technology fueled transformations of the jobs landscape. In the past the new jobs created during technological advancement tended to be white collar jobs, while blue collar workers left out. According to a study by the National Bureau of Economic Research, automation technology has been a primary cause of income inequality over the last 40 years. The report claims that 50% to 70% of changes in U.S. wages since 1980 can be attributed to wage declines among blue-collar workers replaced by automation. Individuals with a college education and white-collar jobs have largely avoided the economic challenges faced by those without higher education.

However, this is different in the AI fueled revolution which seems to impact white collar workers in certain professions more than blue collar workers. According to the Economic Times, AI could be deployed to handle around 30% of the tasks involved in some white-collar roles. For example, roles focused on data analysis, bookkeeping, technical writing and repetitive administrative tasks are highly susceptible to automation. Even tasks like synthesising large volumes of information done by legal assistants and creative work like clothes design can be done by AI quickly.

A study by the Pew Research Centre suggests that those with a college education are more at risk of losing their jobs due to AI. Individuals with a bachelor’s degree are more than twice as likely than those with only a high school diploma (12%) to have their jobs affected negatively by AI. “AI is distinguished from past technologies that have come over the last 100-plus years,” said Rakesh Kochhar, a senior researcher at Pew Research Center. “It is reaching up from the factory floors into the office spaces where white-collar, higher-paid workers tend to be.”

In comparison, less than 1% of a blue-collar worker’s job in a working week can be done by AI. Plumbers, hairstylists, electricians, gardeners are unlikely to be negatively affected by AI, in fact AI is expected to help them improve productivity and wages.

However, it can be argued that AI creates as many jobs as it takes away. The World Economic Forums, “Future of Jobs Report 2023” predicts a 40% jump in the number of AI and machine learning specialists, a 35% rise in demand for roles such as data analysts and big data specialists, and a 31% increase in demand for information security analysts by 2027. This would add a combined 2.6 million jobs.

So what can be done to support the people who lose out because of AI? We cannot stop the spread of AI so countries must develop reskilling schemes. Individuals need to be equipped with the necessary skills to perform these new tasks. Some firms have taken it upon themselves to reskill their workers. For example Walmart has launched an Academy and has retrained 720,000 employees in advanced retail skills, leadership and change management over a two year period. A large part of this burden will fall on the government. In 2019 The World Economic Forum predicted that with an investment of $20 billion, the US government could reskill 77% of workers with a positive cost-benefit balance.

A recent study by economist David Autor found that 60% of today’s workers are employed in occupations that did not exist in 1940. This implies that more than 85% of employment growth over the last 80 years is explained by the technology-driven creation of new positions. While innovation inevitably disrupts existing job markets and may lead to temporary unemployment, it also paves the way for the creation of new, often unforeseen opportunities. For high school students making choices about careers, it is important to reevaluate what the sought after skills in the future may be before plunging in. From an economic perspective, what used to be a sought after and safe profession may not be anymore.

While innovation from AI may cause short-term disruptions, it ultimately fuels societal progress and economic development, provided that strategies are in place to ensure that workers can effectively navigate and capitalise on these changes.

Shivi Vikram – A Level – CS International.
Cover Illustration – DALL·E, an AI system that can create realistic images and art from a description in natural language.