These skills are important

Jakob Ilg from CyberForum e.V. talks to Marco Baumgartner from Karlsruhe University of Applied Sciences about Future Skills.

Companies are always faced with new technologies and challenges, so what's so different about AI?

In essence, I see three central points. First of all, the term "artificial intelligence" is not yet well defined, although I see a great need for it. The term is broadly defined and appears in a wide variety of forms. AI is initially immaterial and therefore not tangible. A second point for me would be that AI systems change independently on the basis of data, and this does not usually happen transparently. There is often talk of a black box. The third point for me would be that the public debate on this topic is currently also very charged.

What these three points mean for companies is difficult to verify. The question of whether you are ready for AI depends on many issues. Are we prepared for change? Which AI technologies are suitable for which use case? Which specialists do I need for this? The issue of a lack of transparency or the "black box" is also relevant. We know this from the private context. For example, when I think of a Google search, I don't know why the Google algorithm suggests certain results to me. I may not need to know that either, but it can become more important to check how valid such an AI-based suggestion is when making business-relevant decisions.

Are there ways to make AI transparent and avoid the black box?

There are indeed attempts to make the creation of proposals more transparent. This is referred to as explainable AI, but it is currently very technically demanding and the solution can of course only be presented in a simplified form. However, explainable AI is particularly relevant when it comes to interaction between people in companies and AI. This leads me to the last point, the public controversy and the associated expectations of AI systems.

Depending on the image employees have of AI, expectations can be too high, which can also lead to frustration if the AI performance is significantly worse. This is why it is particularly important when introducing AI, even more so than with other technologies, to inform employees properly, to train them accordingly and to communicate the goals of the AI introduction transparently, as well as to allow employees to have a say in its design.

The issue of expectations is of course also important for managers. Due to the public debate, managers often expect to find the jack-of-all-trades, but are then disappointed because the possibilities of AI are currently still limited and the obstacles are very high when it comes to providing valid data, for example.

Employees will have to deal with AI in many different areas in the future. If those affected are to become stakeholders, what skills will be important in the future? What do employees need to learn and what skills will be in demand in the future?

In our research, we look at different phases. The phase before the launch, the phase during and after the launch. We have identified different types of skills in the phases. These are AI-specific skills that really have a direct connection to AI. However, there is also the field of leadership and moderation skills to be able to accompany this change and take the employees with you accordingly. We also have the skills to use AI in our daily environment. Ultimately, this also addresses the users. In addition, basic skills are required, especially in the project team, in order to be able to handle AI projects properly. From this, we identified a list of around 30 competencies. The majority of these skills are of a non-technical nature.

User companies are not yet developing AI solutions themselves. The know-how is obtained from external service providers. That's why we currently believe it's more important to develop a basic understanding and knowledge of AI at the decision-making level, but also within the company itself, so that the topic can be properly assessed.

What has now also become very relevant from our research is the topic of mediation skills. People are needed who can bring together different parties in an interdisciplinary manner and who can also get future users on board when formulating specific requirements for the AI system. They ensure that you develop a consistent vocabulary when talking about the topic.

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