The impact of artificial intelligence (AI) on contemporary economies is profound. Many of the tasks we are assigned will shift or possibly disappear entirely.
Experts predict that smart AI regulation would be necessary in light of this existential upheaval; after all, who could be against smart regulation? However, it’s unclear what forms, how to do them, or even why.
A more thorough framing of the issue could be a good place to start. Perhaps easier said than done, as AI differs greatly from traditional technology advancement in many ways. Not that past technology revolutions don’t teach us anything useful. Consideration should be given to the so-called “lump of labour.”
In economics, the lump-of-labour fallacy is undoubtedly the most extensively refuted, yet remarkably resilient, myth. The theory is that there’s just so much labour to go around. Jobs have to disappear if a quicker, less expensive method of completing this set amount of work emerges. That’s why machines are dangerous.
Read also: ‘Africa’s creative industry on Artificial intelligence’ holds in Lagos
The dynamics of the change
Mechanised farming eliminated jobs in agriculture, industrial automation eliminated jobs in manufacturing, and now artificial intelligence is affecting workers in the service industry. As previously, the outcome will be widespread joblessness, as well as falling living standards and reduced incomes for large segments of the labour force.
The last component, however, has always proven to be incorrect. Indeed, these historic economic shifts contributed to unemployment. Workplaces vanished, workers were uprooted, and victims were left to foot the bill. Nonetheless, overall employment continued to rise, and living standards did too. Why? Since the amount of effort required turned out to be infinitely extensible rather than fixed.
AI will work in the same way. After this type of invention, there are two main routes to increased employment. The most alluring scenario is that AI increases sales for businesses. Their employees are more productive thanks to technology, but because their company is expanding more quickly than their employees’ output, they have to hire more staff members.
Not likely, you say? Think about the more likely scenario, which is that businesses profit more from just using AI to replace workers. Even so, there may be an equal number of newly created jobs in other companies that offer novel, potentially AI-enabled products and services.
In other words, technology not only modifies the supply side of the economy but also generates new demand. The innovation that revolutionised agriculture and industries also opened up markets for completely unexplored products, which increased the quantity of labour required. Before many of those goods were on the market, it would have been impossible to even envisage them a decade or two earlier. I never would have imagined needing a supercomputer in my pocket twenty years ago. It was also difficult to predict many of the services that this technology has made possible. Many people today produce items and services I never would have imagined I would want for a high wage and a lot of work.
In fact, our needs and wants don’t always determine the need for new jobs in many economic areas. When considered in this context, the fact that Yale University, for example, is reported to employ nearly as many “managerial and professional” administrators as undergraduates is almost encouraging. That is a very astounding volume of work being completed. But why limit yourself to one-to-one? Perhaps in a few more years, Yale will have two administrators for every student, all putting in a lot of effort and, no doubt, using artificial intelligence (AI) to do whatever they do.
This line of reasoning makes two policy recommendations. One is to exercise caution when it comes to suggestions that encourage innovation to promote the creation of new duties rather than just automating the elimination of old ones. Numerous jobs we may desire or require are unpredictable; simple automation, when done partially or entirely, has the potential to generate new demands and, thus, new work. In general, innovation should be welcomed and encouraged rather than feared since, although it may temporarily “save labour,” it will eventually likely result in higher pay and living conditions.
Artificial intelligence will revolutionize education, says ChatGPT CEO
More on how AI will change employment
Second, mitigating the effects of disruption rather than preventing long-term mass unemployment is the primary economic issue presented by AI. This makes the case for more robust safety nets, more capital ownership participation, reduced labour market frictions (pointless occupational licencing at the top of the list), and increased focus on vocational education. These are, for the most part, classic neoliberal treatments. They haven’t failed in the past because they aren’t qualified for the position; rather, it’s because their application was too timid.
There is a genuine risk of wrenching dislocation because a wide range of service industries promise to adopt AI soon. The technology could encourage the immediate and ongoing reallocation of work more than its predecessors could. This should make instructional innovation the main focus. Early acquisition of one set of skills will no longer be nearly sufficient. People may be forced by AI to consider having many occupations during their working lives. Education systems are just now beginning to change. AI may assist as they work.
“Microcredentials” are one innovation that is probably going to be essential if societies are to benefit from this shift. These are training modules that can be combined to create a “macro-credential” like a degree. They can also be used to indicate particular vocational abilities, which helps to facilitate job switching in the middle or late stages of a career. Companies and institutions will need to lead the charge in advancing the concept of lifelong learning, but public policy may support and facilitate their efforts, enhancing accreditation and assisting prospective students in locating suitable programmes.
In the US, there is already an enormous array of options, which can be extremely confusing. Predictably, Singapore appears to have gone the furthest in adopting a more methodical and encouraging approach, which is the goal of the European Commission and others.
Although the employment market is just one important area, AI presents many other difficulties. At least in one area, there are more reasons to be hopeful than concerned, and more effective policies might significantly increase the likelihood of success.