Race to Catch Up in Artificial Intelligence: “Without a Rethink, Germany Will Fall Behind the Global Front Runners”
- Dr. Ariane Reinhart, Continental Executive Board member for Human Relations: “Graduates of AI-oriented courses are not sufficiently trained in practice-oriented aspects. Without a rethink, Germany will fall behind the global front runners when it comes to technology”
- Continental calls for universities to focus more on practical requirements
- Kristian Kersting, professor of artificial intelligence: “Science needs better access to ‘real’ data and greater connectivity of research institutes and institutions”
- Qualification and attractive projects are key to winning and retaining AI specialists
Hanover, July 19, 2021. In order for Germany to catch up in the area of artificial intelligence (AI), Continental is calling for a fundamental shift in the training of AI specialists in universities. “AI is a key success factor for Germany as a business location. Without a fundamental rethink, Germany will fall behind the global front runners when it comes to technology,” explained Dr. Ariane Reinhart, Continental Executive Board member for Human Relations. “In order for the economy to have a sufficient number of AI graduates available, universities must focus their training more on practical requirements. Otherwise, our national economy risks losing ground on other leading economies when it comes to technology.”
Dr. Ariane Reinhart, Continental Executive Board member for Human Relations: “AI is a key success factor for Germany as a business location. Without a fundamental rethink, Germany will fall behind the global front runners when it comes to technology.”
As things currently stand, universities may indeed produce many, often highly distinguished AI scientists. However, due to the lack of practical expertise, these scientists are not directly available to industry. “Measured in terms of the requirements of the economy, the graduates of AI-oriented courses are not sufficiently trained in practice-oriented aspects,” said Reinhart. “We have to systematically introduce AI specialists coming from universities to actual practice. This requires a further three to five years of additional training – which is a lot of time in view of the speed at which the use of AI is developing in all areas,” explained Reinhart.
Continental spends tens of millions on the training and further training of its more than 1,000 AI specialists each year. “The economy must let go of the idea that the universities are producing fully trained AI specialists. Due to the high rate of innovation and strong cost pressure, it is, however, increasingly the case that fewer companies are in a position to permanently invest large sums in the training and further training of their AI specialists,” said Reinhart.
“AI demands a different form of collaboration between the economy and industry and a culture of sharing. In this respect, we should follow the lead set by countries such as the USA and China. In those countries, for example, companies provide data so that science can develop and validate AI programs and algorithms based on that data,” continued Reinhart.
Science needs access to real data
Kristian Kersting, professor of artificial intelligence and machine learning at the Technical University of Darmstadt and codirector of the Hessian Center for AI, supports this approach but also criticizes the lack of an AI culture in the economy: “Companies are ‘somehow’ relying on AI without understanding how it works at its core. Everybody involved must converge and jointly drive development,” said Kersting. For him, it is not only better collaboration between universities and the economy that counts in order to test scientific projects and models in practice. “It is equally important for universities and research institutes to have better access to real data and for there to be greater connectivity of scientific institutes and institutions among each other in the area of AI, according to Kersting. “However, the state must also contribute its share and support the AI departments and AI institutes with higher budgets so that they can improve and expand their IT infrastructure, for example.”
Continental as a pioneer in AI qualification
Continental runs its own software academy in order to train AI specialists in practice-oriented aspects and to continuously keep their qualifications up to date. Using this internal platform, the company provides training as well as in-house courses and seminars, but also ‘tech talks’ with speakers from renowned universities. “Particularly in the area of AI, qualification is the decisive factor so as not to fall behind technologically and to be attractive as an employer,” said Reinhart. “Through our commitment and our initiatives, we are showing that German companies are not just in a position to win over AI specialists in sufficient numbers but are also able to keep them in Germany with attractive tasks. This concept from Continental can be a model for other companies.”
Furthermore, Continental is also accelerating the development of AI-based future technologies in the area of assisted, automated and autonomous driving by deploying its supercomputer. The investment that it has made in the automotive industry’s most high-performance computer system is a further step in the company’s strategy for the future: concentrating on key areas for innovation, such as software and digitalization. Around 20,000 of the more than 51,000 engineers working for Continental are already experts in the areas of software and IT. In addition, the company wants to increase the share of AI experts from currently more than 1,000 to 1,600 by 2023.
