{"id":5350,"date":"2024-11-21T15:19:20","date_gmt":"2024-11-21T14:19:20","guid":{"rendered":"https:\/\/www.rivistaeco.com\/?p=5350"},"modified":"2024-11-21T15:19:20","modified_gmt":"2024-11-21T14:19:20","slug":"how-to-prepare-for-the-future-job-market","status":"publish","type":"post","link":"https:\/\/www.rivistaeco.com\/en\/2024\/11\/21\/how-to-prepare-for-the-future-job-market\/","title":{"rendered":"How to Prepare for the Future Job Market"},"content":{"rendered":"

David Card is a professor of economics at the University of California, Berkeley. He was awarded the Nobel Prize in Economics in 2021 for his empirical contributions to labour economics. His research focuses on immigration, wages, education, and labour market disparities related to gender and ethnicity.<\/span><\/p>\n

Interview by Roberto Fani and Matteo Valetto<\/span><\/p>\n

Will Artificial Intelligence Take Our Jobs?<\/span><\/i> Since the Industrial Revolution, the effects of technological innovations on the labour market have moved beyond university discussions to become a central topic in public debate. Of all the issues economic research addresses, labour is the one that most directly affects people’s lives, their families, their economic stability, and their future prospects. Understanding the impact of artificial intelligence (AI) on workers is just one of the topics discussed with David Card. We also explored significant generational shifts in education and professional development for those already in the workforce, and how policy should respond\u2014both today and in the future\u2014to a changing labour market. We examined the role of the minimum wage, even in the context of the new digital giants, and discussed new research frontiers and the critical issue of social and economic inequality, along with the vicious cycles that perpetuate it.<\/span><\/i><\/p>\n

 <\/p>\n

The August issue of <\/b>Eco<\/i><\/b> focused on artificial intelligence. With increasing questions about which tasks might be replaced by technology, how should we view this phenomenon?<\/b><\/p>\n

One of the most common mistakes is to equate people with the jobs they perform. This is an overly simplistic view of the world: people are not their jobs, and they often move from one role to another. For example, the profession of “data scientist” has emerged in the past decade. However, the tasks involved in this role were always carried out by different people within companies. At some point, it became clear that these tasks could be consolidated into a single role, leading to the creation of training programs and job titles. In this sense, especially in tech companies, job titles change more frequently than the jobs themselves. Ultimately, what matters is what happens to people. If they are flexible and capable of acquiring new skills, I believe they can transition between roles with surprising ease. For instance, some of today’s economics graduates in the US have taken courses in SQL, a programming language for large data sets, and are now finding jobs as data scientists.<\/span><\/p>\n

 <\/p>\n

Do you think schools and universities are adapting quickly enough to these changes?<\/b><\/p>\n

No, I don\u2019t think we\u2019re changing curricula fast enough. In economics departments, for example, we should be teaching more data analysis. While we\u2019re moving in that direction, the pace is slow. The skills expected from an “economist” today are very different from those 20 years ago, and they will likely be even more different 20 years from now. This is why static definitions are unhelpful.<\/span><\/p>\n

 <\/p>\n

An interesting phenomenon is the growing wage gap between university graduates and those with only a high school diploma, especially in the US What\u2019s driving this?<\/b><\/p>\n

We have to remember that, in the long run, the composition of jobs in the economy changes. Fundamentally, there\u2019s limited demand for low-skilled workers, and the supply of these workers is relatively abundant. At the same time, there\u2019s a significant demand for highly skilled workers, who remain relatively scarce. Jobs are changing, and they require different skills than they did in the past. Skills acquired through higher education are increasingly in demand and command higher wages.<\/span><\/p>\n

 <\/p>\n

Do you think this influences people\u2019s decisions to attend university?<\/b><\/p>\n

In the US, the return on education increased rapidly from about 1980 to 1995, and it has continued to rise since, though at a slower pace. Today, the differences are primarily based on the type of degree pursued: the wage gap between those studying computer science or economics and those in the humanities has widened considerably over the past 10 to 15 years. This reinforces the need for curricula to adapt quickly.<\/span><\/p>\n

 <\/p>\n

Returning to artificial intelligence, how should we interpret this new technological revolution? How does it differ from past major innovations?<\/b><\/p>\n

It\u2019s a controversial topic. I\u2019m old enough to remember the introduction of the internet and personal computers (PCs). When we first started working, there were mainframes, and no one had a computer in their office. Then, PCs arrived, but they weren\u2019t yet networked. It took years before the internet came along, and at first, only a few computers could connect. What\u2019s different this time is that the company behind ChatGPT (OpenAI) and its founder (Sam Altman) generated enormous publicity right from the launch. We don\u2019t know how it will all play out, but everyone is excited, and countless users are experimenting with ChatGPT. Anyone can ask it to write a short essay on Shakespeare or program a simple game in any programming language. We even tried it: we asked ChatGPT to write a summary on how computers have changed labour markets, and it delivered. Of course, it\u2019s essentially a gigantic imitation of existing scientific literature, so it\u2019s not truly innovative, but people are fascinated by it.<\/span><\/p>\n

 <\/p>\n

And what will the effects on the labour market be?<\/b><\/p>\n

We don\u2019t really know yet. So far, studies suggest that in a narrow range of tasks\u2014like customer service\u2014it\u2019s less-skilled workers who benefit the most from working with ChatGPT, unlike their more skilled counterparts. Other research has found similar results. The same applies to programming: a top-level programmer won\u2019t rely on ChatGPT because it isn\u2019t efficient enough. But if you\u2019re learning to program or are a bit out of practice, it can be a helpful tool.<\/span><\/p>\n

 <\/p>\n

The public debate often highlights the negative impacts AI might have on workers. Are you concerned?<\/b><\/p>\n

It\u2019s possible, for example, that companies might try to replace half their customer service agents with a chatbot, while the other half continues working. This scenario has been discussed, but it hasn\u2019t answered the fundamental question: will these agents actually lose their jobs? That remains an open question. In one of his studies, economist Daron Acemoglu suggested that around 20-25% of jobs as we know them today could be affected by large-scale AI adoption, and a quarter of those jobs could be heavily impacted. However, it\u2019s difficult to predict whether these workers will truly be replaced.<\/span><\/p>\n

 <\/p>\n

How should policy respond to the risk that a portion of the workforce might be displaced? Should we invest more in job training and professional development?<\/b><\/p>\n

Over the years, I\u2019ve written many papers on training and skill updates. The investments made in this area are usually modest: training programs typically last a few months, with the longest lasting up to a year (Germany offers some of these). In most countries, an additional year of higher education is estimated to increase earnings by up to 10%. A year spent in a job training program, however, doesn\u2019t compare to a year at a top university, partly because people often participate only part-time. Optimistically, we might increase earnings by 5%, but these programs won\u2019t revolutionisoe people\u2019s lives. They remain relatively low-income, and a 20% increase won\u2019t make them middle class. Job training programs won\u2019t perform miracles.<\/span><\/p>\n

 <\/p>\n

Shifting to labour markets, another interesting phenomenon is the shrinking middle class. Technology seems to have replaced medium-skilled workers in repetitive tasks. What\u2019s your take on this?<\/b><\/p>\n

It\u2019s more complex than it seems. While the proportion of jobs in middle-income occupations has decreased, wages haven\u2019t fallen. Part of this is due to how we define these jobs: professions change over time. If we stick to old definitions, it looks like the number of workers in those specific roles is declining, but it doesn\u2019t mean that people aren\u2019t performing the same types of tasks\u2014they just have different titles now. In healthcare, for example, nursing has evolved: a few decades ago, it didn\u2019t require a degree, but today it does, and the job description has changed accordingly. So, I\u2019ve never fully supported the “disappearing middle class” narrative because it explains job numbers but not wage stability.<\/span><\/p>\n

 <\/p>\n

In Italy, there\u2019s ongoing debate about the minimum wage. Your research has helped us understand its importance. What advice would you give to a government considering its introduction?<\/b><\/p>\n

For Italy, the most relevant comparison might be with Germany, where a national minimum wage was introduced in 2015. The German labour market had significant union coverage, which was weakening, and large regional productivity differences. The Munich area is high-income, while East Germany, near the Polish border, has lower wages. Germany faced many of the same issues as Italy, though Italy\u2019s regional disparities, such as between Lombardy and the South, are more pronounced. I\u2019d suggest studying the German model. While there are empirical challenges in assessing the minimum wage\u2019s effects, my reading is that it didn\u2019t destroy jobs in East Germany, as some feared.<\/span><\/p>\n

 <\/p>\n

The minimum wage has been used in some countries for over a century. Yet, many sectors of the economy have changed, particularly with the growing bargaining power of large digital platforms in delivery and similar sectors. Do you think the minimum wage is still effective?<\/b><\/p>\n

The minimum wage is particularly relevant when companies have excessive bargaining power over wages. If companies indeed have too much bargaining power, then even economists who are usually sceptical of the minimum wage would likely support it in such cases.<\/span><\/p>\n

 <\/p>\n

Let\u2019s talk about digital platforms and their bargaining power. Do you think there\u2019s a role for antitrust policy in the labour market?<\/b><\/p>\n

It\u2019s hard to say. In the ridesharing industry, for example, there are only two main players in the U.S., and one of them, Lyft, is struggling. You\u2019d expect competition based on price, but Uber seems to dominate. It\u2019s one of those industries where network effects matter\u2014the more users, the stronger the platform. If one company dominates, antitrust policies may be difficult to implement. Perhaps we\u2019ll see new ideas from European regulators, who have been quite creative in the past, and European antitrust policy is stricter than American policy.<\/span><\/p>\n

 <\/p>\n

Your research has clarified many labour market phenomena. What are some issues we still don\u2019t understand well and should focus on in future research?<\/b><\/p>\n

There\u2019s still much debate about why different groups have varying labour market outcomes\u2014such as men versus women or minorities versus non-minorities\u2014and why those from higher-income, better-educated families achieve better outcomes. Is it purely a matter of human capital? And how can we help people from disadvantaged backgrounds?<\/span><\/p>\n

 <\/p>\n

Do you think this is related to growing income inequality?<\/b><\/p>\n

There are several features of today\u2019s economy that drive wealthier families to spend more on their children. Harvard, for example, spends $400,000 per student annually, while public universities like Berkeley spend $40,000. So, it\u2019s no surprise that families go to great lengths to get their children into Harvard, investing in extracurriculars like sports or music lessons, which are crucial in the American admissions process. This creates competition that wastes resources, and it\u2019s a big problem. It\u2019s largely driven by inequality, where the rewards for reaching the top are disproportionately high. It becomes especially problematic when access to elite universities is limited, fuelling these perverse dynamics.<\/span><\/p>\n

 <\/p>\n

Bio<\/span><\/p>\n


\n<\/span>Roberto Fani is an economics and finance student at Bocconi University and a member of the student association Economic Society for Bocconi Students.<\/span><\/p>\n

 <\/p>\n

Matteo Valetto is an economics and social sciences student at Bocconi University and a member of the student association Economic Society for Bocconi Students.<\/span><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

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