Wilhelm Bauer

Mr Bauer, how will AI change everyday working life?

Wilhelm Bauer: Artificial Intelligence is already being used in many ways in the world of work. Think of various internet services, such as search engines or translation tools. They would be inconceivable without AI. Or industrial quality inspection systems based on pattern recognition to reliably detect defective parts.

AI changes everyday working life in different ways. Above all, job profiles change when intelligent machines support humans. I am not worried that we will run out of work due to the use of AI. However, we will tend to work in a more flexible and mobile way.

The everyday work of software engineers, i.e. those professional groups that implement AI systems, deserves a special mention. These AI developers not only have to apply non-linear functional logics; above all, they need a high level of abstraction to grasp problems and model facts. The dynamics of self-learning systems that are constantly evolving pose an additional challenge. Therefore, the results of such systems must always be checked for plausibility and validity - also in foresight and taking into account different possible data situations. Such ways of working require a high degree of autonomy and a sense of responsibility - also among the employees who use such systems.

Which new skills do employees need? And which are becoming less important?

Wilhelm Bauer: In our company survey, we identified a high demand for technical, AI and digital skills in the course of AI implementation. For example, computer scientists will have to master the methods of machine learning and data science. Digital skills, however, are not enough for success at work: so-called industry or domain knowledge is just as important. Anyone who wants to apply AI in industrial production, for example, must have profound production knowledge.

When companies introduce AI, agile project work becomes more important. Social, communicative and personal skills, such as initiative, creativity or problem-solving ability, are in demand here. In addition, the use of AI increasingly raises ethical questions. AI experts must be able to assess the individual or social consequences of the use of technology in order to recognise undesirable or even illegal developments as such and possibly stop them.

To the extent that independent, problem-finding and problem-solving behaviour gains in importance, those competences that are required for the conscientious fulfilment of uniform routine tasks recede into the background.

What is needed to empower people to work with AI systems?

Wilhelm Bauer: Companies pursue different strategies to build up competences: Some develop existing competences through internal qualification measures. Others recruit qualified junior staff or experienced experts on the labour markets. However, both approaches are currently reaching their limits.

As our company survey revealed, current qualification concepts emphasise the integration of workplace learning and action. This should promote the targeted implementation of new experiences in practical application. AI qualification preferably takes place as task-specific "on-the-job training" or in-house seminars. Extensive online training offers available worldwide support such an endeavour.

The high intrinsic motivation of many AI users is striking when it comes to acquiring new skills. Excellent career opportunities may also be decisive for this. This makes it easier for people to successfully master the learning requirements.

However, a mature use of AI systems requires not only knowledge and judgement, but also decision-making and action latitude. AI algorithms turn out to be a kind of "black box" in which the connections between input and output are often difficult or impossible to interpret. "Explainable Artificial Intelligence (XAI)" describes the functionality of an AI model, its expected effect and its systematic errors. It allows users to change the result or even challenge a decision.