Artificial intelligence - more opportunities than risks for Germany as an industrial location

Thanks to ChatGPT, artificial intelligence (AI) is on everyone's lips. 2023 is already being called the year of AI. Yet we should remember this technology was born many decades ago. In the mid-1960s, computer scientist Joseph Weizenbaum invented the first chatbot called Eliza. Thirty years later, IBM's AI computer Deep Blue made headlines because it was able to defeat the world chess champion Garri Kasparov. Another milestone was the development of facial and speech recognition. All these innovations build on each other and have brought AI technology great steps forward.

So far, we have been talking about analytical AI, which recognises and applies patterns from a finite data set. The quantum leap we see today is the breakthrough of generative AI, which can process enormous amounts of data and generate new texts, music or images. Applications based on this, such as ChatGPT or Dall-E, are experiencing real hype. It took Facebook 54 months to reach 100 million users, TikTok nine months, ChatGPT only two months. The focus of the public debate is on the benefits for the end consumer, the consequences for creative professions and the risks in terms of fake news and data protection. These are important aspects, but especially in Germany as an industrial location, the focus should be more on the opportunities for companies, especially SMEs, and improving the competitiveness of the local economy.

McKinsey has calculated in a study that generative AI technologies can enable an annual productivity increase of 2.6 to 4.4 trillion dollars worldwide. That is roughly the size of the UK's gross domestic product in 2021. Higher productivity is essential to counter the shortage of skilled workers, which affects every second company in Germany. Therefore AI is one of the key technologies that will help determine future prosperity in Germany.

AI has been a feature of modern companies and factories for a long time and is already delivering significant productivity gains. In customer service, for example, a large number of customer enquiries can be processed faster and better. AI-supported image processing is enabling robots to easily grab and sort different objects in warehouses or detecting microscopic defects when welding cars, supporting quality assurance. When it comes to checking welding spots, the AI-enabled robot is 20 times faster than a human. This analytical AI has taken automation to the next level for a simple reason -it does not need complex programming.

Generative AI builds on this and acts as a catalyst for innovation. Robots in industry will become even easier to operate: they will soon be able to generate their own programming code based on their own "experience", allowing them to solve problems without human intervention. In addition, robots will be able to perform tasks using voice commands, offering enormous advantages for small and medium-sized enterprises that do not have programmers in their own ranks.

When we look into the future, the full potential of AI is revealed, and in a wide variety of economic sectors. It will have a huge impact on scientific research, especially in medicine: from Big Data analysis for faster detection of diseases and drug development to monitoring patients' health through virtual assistants. In the longer term, AI's ability to learn could enable us to make more accurate predictions for financial markets, more precise weather forecasts and create greater decision-making autonomy in connected cars.

But what is needed to fully exploit the potential of AI in Germany? We need more openness to technology, we need to invest more in education and training, and we should specifically promote new skills. This starts at school, where basic technology knowledge should be taught much earlier and in a playful way in order to awaken enthusiasm for it among both girls and boys. In addition, Germany has some catching up to do in the promotion of AI start-ups and in the transfer of knowledge between science and business. And finally, we need a legal framework that promotes targeted innovations. We need to distinguish between AI applications for consumers and those used in industry. While the risks for consumers are rightly in the foreground, these dangers are lower in the industrial context. In other words: Germany should not always want to be the world champion in regulation, but should also finally become the world champion in innovation again.

This article was first published in Handelsblatt on 30th June 2023: https://www.handelsblatt.com/meinung/gastbeitraege/gastkommentar-kuenstliche-intelligenz-bietet-der-deutschen-industrie-mehr-chancen-als-risiken/29228084.html