Professor Ines Helm researches the effects of AI and the structural transformation of the labor market

10 Oct 2022

A new appointment at LMU, the economist studies the effects of technological progress.

Professor Ines Helm | © Niklas Björling

Which tasks will algorithms perform in the future? How will this affect the employment market? And which jobs will be left over for humans to do? Economist Ines Helm investigates questions such as these. “The upheaval of the labor market by artificial intelligence (AI) has only just begun, and so labor economics research into its effects is still in its infancy.” Among other things, Helm explores what conclusions can be drawn from earlier upheavals caused by technological change – such as automation, computerization, and robotization – that could be relevant for the AI transformation.

Since October of last year, the expert in labor economics has been Professor of AI in Economics at LMU. In addition to labor economics, her main research interests include regional economics, public finance, and applied methods. Helm studied economics at LMU and the University of Tübingen and completed a master’s degree in Econometrics and Mathematical Economics at London School of Economics. In 2016, she obtained a doctorate at University College London and was appointed assistant professor at Stockholm University the same year.

“Effects in the next decade”

Structural transformation is one of the chief focuses of Ines Helm, who received the Young Labour Economist Prize from the European Association of Labour Economists in 2017. “Technological progress has always led to great upheavals in the labor market.” The introduction of AI to the employment market is still in its early days. “But in the next decade, we will feel its effects with greater force.” The main issue currently facing this young field of study, explains Helm, is how we can even measure the operations of AI in the labor market with existing data. Another important task is drawing inferences for the future from past episodes of structural transformation.

“Concerns about effects on the labor market were there in past upheavals such as the mechanization of agriculture or computerization.” Macroeconomically, however, these worries proved to be unfounded. “Change is constant: we went from an agricultural society to an industrialized one, and from there to the information society,” says Helm. “But the workers released from agricultural labor went on to strengthen Germany’s manufacturing sector. And although computerization had a negative impact on the manufacturing sector, it gave a powerful boost to the service sector.”

AI affects highly qualified employees

In relation to the transformation in manufacturing industry, to which globalization was also a contributing factor, Ines Helm has previously shown that the consequences of structural change were not distributed equally. Most of all, it was well-paid jobs for people with low skills that vanished from the jobs market. These workers found it hard to get a new job and were increasingly pushed into the less well paid service sector. Lower incomes were not caused here by losses in specific human capital, for example, but primarily because companies in the manufacturing sector are more productive and give their employees a greater share of their profits through higher wages.

“We know that new technologies always lead to the emergence of new tasks,” says Helm, “and this will undoubtedly happen with AI as well. The difference is that AI will also directly affect highly qualified employees, although personnel with these higher skill levels may be better equipped to adapt to the change.”

An important aspect in all this is the types of new technology that AI engenders. “Are they just purely automation technologies or do they also lead to increases in productivity? Are they complementary to the skills of employees, and do they maybe also give rise to new tasks? And how can workers be retrained so that they can do the new jobs?”

“Complex tasks remain the province of humans”

“If a radiologist has to scrutinize every single scan to identify whether a patient has cancer or not, AI could greatly simplify this task for the radiologist and even be more precise than humans. And although radiologists will still look over the result and the scans, they can reinvest the time saved in the accomplishment of other professional tasks, with all the positive benefits this entails.” In the case of pure automation, by contrast, there are negative effects: “Many call center workers will no doubt be replaced by AI in the future. But here, too, the remaining employees will have more time to deal with more complex queries. And that could lead to more customer satisfaction and increased demand,” says the economist.

“I don’t think that AI will result in mass unemployment, as some people now fear,” concludes Helm. “But as in earlier upheavals, there will be losers – and we must see how we can help them.”

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