Ausbildung / Jobs

Curiosity Remains the Key to Success

It is no secret that the digital transformation is revolutionizing the world of work. And so the joint webinar of the TUM Campus Heilbronn and Stanford University, entitled “Unrevealing Future Skills in the Age of Automation and AI – Expectations and Training”, addressed a highly topical issue. This was also emphasized by host Prof. Helmut Krcmar: “Automation and AI have a very strong influence on our work, but also on the demand for skills,” said the Founding Dean and long-standing Representative of the TUM President for the Overall Development of the TUM Campus Heilbronn. This would also change the requirements for training and its content. But this is where the questions begin: What are the prospects for employees? Are they willing to undergo further training to meet them? What value do skills acquired early in a career have?

Speakers Christina Langer from Stanford University and Prof. Philipp Lergetporer from the TUM Campus Heilbronn tried to answer these and similar questions. While Langer was primarily guided by the question of how the training content must be adapted to the changed framework conditions, Lergetporer focused on the consequences for employees.

Greater skills, higher pay

In her study, Langer examined which skills are taught in vocational training in Germany and how these skills pay off on the labor market later in the employees’ careers. The postdoc at the Stanford Digital Economy Lab and her co-author Prof. Simon Wiederhold from the Martin Luther University Halle-Wittenberg analyzed text data from standardized training plans for 165 occupations. They classified more than 13,000 different skills into five categories: cognitive, social, digital, manual, and administrative. The two researchers then linked their data to the Sample of Integrated Labor Market Biographies (SIAB) from the Institute for Employment Research (IAB), which contains information on employment histories, apprenticeship occupations, and wages of two percent of German employees subject to social security contributions.

The study showed that additional training in cognitive, social, and digital skills is associated with significant wage increases –particularly when it comes to digital skills. However, while acquiring higher cognitive and social skills relates to higher wages in both the short and long term, additional training in digital skills during an apprenticeship yields greater returns in the long term. Langer’s study results also allow to distinguish between general skills, which are mainly taught in the first half of the apprenticeship, and specific skills, which are the focus in the second half: general skills seem to have a greater impact on salary than specific ones. Last but not least, differences between the genders are also apparent: while women benefit most from additional cognitive and social skills, the opposite applies to digital skills: here, men’s salaries increase more than women’s when additional digital skills are imparted.

Automation and lifelong learning

In any case, it is definitely worth it to educate oneself and expand one’s own skills. But are employees aware of the importance of lifelong learning? And do they understand that parts of the tasks they currently perform in their jobs may be automated in the future? These questions were the focus of Philipp Lergetporer’s lecture. The Professor of Economics at the TUM Campus Heilbronn presented results from a large-scale survey of employed individuals in Germany. The study focused on the question whether they realize the risk that some of their occupational tasks could be automated in the future, and whether information about their actual automation potential changes their expectations about the labor market and their willingness to undergo further training. To this end, a randomly chosen part of respondents was informed about the automation potential of their job, based on figures drawn from the so-called “Job-Futuromat” of the IAB.

More willingness to continue training through information

Two key findings of his study: almost 70 percent of respondents underestimate the possibility that their jobs will be automated. Even more worrying: the higher the potential for automation, the less likely those affected are to recognize it. Lergetporer: “Before these people realize that robots or generative artificial intelligence will eventually take over their tasks, they could lose their jobs.” How can this information deficit be remedied? The study shows: When respondents are informed of the actual risk of automation, they worry more about their professional future. At the same time, they are more willing to participate in further training or even retraining.

Lergetporer collected his data in 2022 – before ChatGPT and the upheavals that Generative AI has caused in the world of work. But the core results of his study would have held regardless of current technological developments: “Awareness of the need to participate in training is key to success in the labor market. It is always important for people to update their skills and expand them in a way that complements new technologies – so as not to be replaced by them.”

Curiosity and creativity

Few people foresaw the tremendous changes brought about by ChatGPT, Langer added: “It’s really difficult to prepare for these things. But that’s precisely why we need to remain adaptable in case such changes come our way.”  Curricula updates would need to be implemented more quickly than at present. In conclusion, Krcmar summarized the quintessence of both presentations: “‘Best Practice’ always means ‘Best Practice of the past’. But at the same time, there seem to be timeless meta-skills: curiosity and creativity.”

The complete video recording of the webinar can be found here.

Firmenkontakt und Herausgeber der Meldung:

Die TUM Campus Heilbronn gGmbH
Bildungscampus 2
74076 Heilbronn
Telefon: +49 (0) 7131 264180
Telefax: +49 (7131) 645636-27
https://www.chn.tum.de/de

Ansprechpartner:
Kerstin Besemer
Telefon: +49 (7131) 26418-501
E-Mail: Kerstin.Besemer@tumheilbronn-ggmbh.de
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