Nine mentors supervised nine mentees, actively involved in shaping policy for a United Europe in form of webinars, opinions and articles published on United Europe’s website. After Katharina Hug’s Brexit analysis and Rafael Stein’s “Five lessons for an EU career”, we continue the series with the last article “Why the answer to global challenges with Megatrends on the verge should be a European one” by Michael Suckow, Senior Consultant at Zum Goldenen Hirschen, Germany. Michael was coached by Paul van Son, active for more than 40 years on supervisory boards, executive boards and in operations management positions in the international energy business.
In 2022, there will certainly be no shortage of forward-looking technologies and ideas that have now developed into megatrends to address fundamental societal challenges – such as climate change or digitisation – and to solve problems even more easily in the future and to improve processes based on the findings. Artificial intelligence (AI) will undoubtedly be one of the key technologies of the coming years. The EU Commission Vice-President Andrus Ansip, responsible for digital, has predicted that AI will change the world as fundamentally as the steam engine or electricity did. Self-driving cars and robots will most likely be the norm in the future, and countless smartphone apps already contain self-learning algorithms that constantly improve the products we use every day.
In my day-to-day work as a senior consultant in a creative agency, I very often meet employees of federal ministries and top federal authorities in Berlin. I get an insight into administrative processes – a practical teaching example of Max Weber’s ideal type of bureaucratic organisation. And yet I firmly believe that this rigid apparatus can modernise itself and question and leave behind the established behavioural patterns of the past century.
Modern technologies – especially artificial intelligence – can play a decisive role in this process. The challenge for governments and leaders is to redesign how people and machines work together in process chains and mixed teams. At the same time, the application of AI is an occasion – or rather an opportunity – for employees to reflect on their own strengths and develop them further.
With this article, I want to set a positive example. I want to show that despite all the challenges and concerns that arise from the use of modern technologies such as artificial intelligence, these technologies do indeed have enormous potential to sustainably improve both our everyday and our working lives, and that we should approach them positively. All in the knowledge that we will find our own – a common – European answer.
AI is here to stay
Do you remember the time when we used to try and find our way on a map during long car trips? Countless maps for different countries and areas in Germany and Europe. AI has drastically changed the way we travel. We use Waze, Google or Apple Maps on our smartphones as a matter, of course, to get to our destination. So how does the application know where to go? And what’s more, find the optimal route and avoid road barriers and traffic congestion. Not too long ago, only satellite-based GPS was available, but now, artificial intelligence is being incorporated to give users a much more enhanced experience. Using machine learning, the algorithms remember the edges of the buildings that it has learned, which allows for better visuals on the map, and recognition and understanding of house and building numbers. The application has also been taught to understand and identify changes in traffic flow so that it can recommend a route that avoids roadblocks and congestion. It’s almost unthinkable that we would have to do without it in the future.
We use social media for more than two hours a day without giving much thought to the fact that our user experience is influenced and optimised by AI. Social media applications use AI support to monitor content, suggest connections and serve advertisements to targeted users, among many other tasks, to ensure that you stay invested and “plugged in”. AI algorithms can spot and swiftly take down problematic posts that violate terms and conditions through keyword identification and visual image recognition. The neural network architecture of deep learning is an important component of this process, but it doesn’t stop there. Social media companies know that their users are their products, so they use AI to connect those users to the advertisers and marketers that have identified their profiles as key targets. Social media AI also can understand the sort of content a user resonates with and suggests similar content to them.
These examples of artificial intelligence show why AI is talked about everywhere – why it’s used everywhere. Nearly every part of our day is touched by AI. Instagram might show you a new video while you’re on your lunch break. Whereas Google Maps directed you to the new restaurant where you’re having your lunch break. The list could go on forever, but these few examples of AI show what it is and how we are using it.
The dilemma – and the European answer
Artificial intelligence has become a foundation of the digital transformation and plays an essential role in a large number of business models in the digital economy. However, the solution to the challenges cannot be solved by politics alone and requires the close and trusting cooperation of civil society, science and the media landscape. Artificial intelligence reveals one of the key global challenges when it comes to generating added value for society when taking a united stand against fundamentally threatening scenarios such as global climate change and in preventing and – where this is no longer possible – at least reducing the negative consequences in the future.
Countries around the world are harnessing the transformative impact of AI on their economies and societies. Competition and rivalry between countries with advanced AI research and development (R&D) capabilities are taking centre stage, with talk of an “AI race” between the United States and China. However, the ethical and security risks that will arise if AI is not properly deployed are as great as its potential benefits.
From facial recognition and hiring algorithms that are fraught with a bias to self-driving cars that endanger human lives, the challenges associated with AI governance failures are enormous and require collaborative solutions. So far, Europe is carving a middle path that protects fundamental rights while reaping the benefits of AI deployment. Policymakers recognise the need to foster technological, economic and social innovation. But they also recognise that the use of AI must respect fundamental rights and freedoms, including privacy, data protection and non-discrimination.
The success of AI and new technologies requires acceptance and trust
With all these challenges, it can be said without exaggeration that the broad acceptance of AI and new technologies are not yet deeply enough anchored in society. This would be necessary – at least from a German, if not also a European, perspective – to compensate for the information and technology led by countries such as the United States and China. It is therefore of the utmost importance to explain to society that digital transformation is much more than the introduction of a purely technological stack. The essential momentum lies in the mindset and culture of a society.
It depends on the acceptance of the members – the citizens. And even if there is only a partial rejection, this will have a direct effect on the success of the implementation. The acceptance and trust to be established in automation and digitalisation do not only refer to the design of technology, which is not only oriented to human factors and ergonomics, but also to human information processing and the ethical evaluation of humans. It is important that the highest demands are made on a human-centred design approach and on a continuous assessment of the violation of basic human rights, such as the right to privacy and non-discrimination, to maintain trust and control in the socio-technical system.
Sustainable use of technologies
As digitisation is making its way into almost all areas of life, the world is becoming shapable through modern technology solutions and providing a strong basis for influencing (European) coexistence in a positive and sustainable way. A high innovation dynamic – for example, in the areas of networking, data collection and analysis – leads to hardware components being networked with and controlled by intelligent software. What is important here is the seemingly self-evident integration into social processes. Not only are organisational processes optimised, but political actions, work processes and even human behaviour changes. In other words, in order to develop sustainable digital solutions that put environmental and climate protection into practice, a technological transformation is required along with a simultaneous societal transformation (see figure).
The sustainable use of digital technologies is necessary and can make a significant contribution to achieving the climate targets by 2030, as shown by a study by the digital association Bitkom, which concludes that CO2 emissions can be reduced by 120 megatons in ten years through the targeted and accelerated use of digital solutions. This corresponds to almost every second ton of what Germany still must save to achieve the climate targets it has set itself.
The link between AI and (emission-free) energy
While the topic of AI correlates with almost all areas of life, the sustainable use of digital technologies offers a wonderful gateway to take a brief excursion into the world of zero-emission energy and demonstrate the significant contribution AI to the value chain can make in achieving globally set climate goals. Of course, the topic is not new, however, the level of sophistication is increasing rapidly, giving a glimpse into what could be expected in the future.
The importance of renewable energy to our future is becoming increasingly clear as governments around the world set new targets and regulations to limit carbon emissions. The Global Wind Energy Council’s (GWEC) annual Global Wind Report highlights that the global wind energy industry continues to grow as companies seek to make their networks and processes more efficient – with the help of artificial intelligence. Renewable energy is a growing part of the global energy sector, and the use of new technologies such as AI is key to building a lower-carbon future. Indeed, AI offers the renewable energy industry many opportunities to build stronger, more sustainable and more stable systems.
As renewable energy sources make up an ever-increasing share of our energy mix, predicting capacity levels will become increasingly important to ensure efficient and stable grids. As a growing share of our energy comes from renewable sources, baseload generation from energy sources such as coal, which are responsible for grid inertia due to the presence of heavy rotating equipment such as gas and steam turbines, is decreasing. With little or no grid inertia, power grids could become less stable and more prone to blackouts.
However, AI and automation can help mitigate these risks. Real-time data collected by sensor technologies from wind and solar plants, as well as data sets of historical weather information derived from celestial cameras and satellite imagery, can be interpreted by AI, which can then predict capacity levels and outage times and act accordingly. This, in turn, helps maintain stable power grids. Using AI to analyse data can also enable grid operators to optimise the use of power grids by adjusting operations to weather conditions at any given time. Accurate short-term forecasts can lead to greater dispatching efficiency and better block use, which improves reliability and reduces required operating reserves.
AI is also able to predict when energy is most needed by consumers, which means it can also play a big role in battery storage and providing demand flexibility. Storage batteries can be activated very quickly to handle periods of high energy demand. Artificial intelligence can make energy management and storage decisions easier based on its predictions of when energy is most in demand and the data it gathers from renewable energy sources and grid conditions in real-time.
Artificial intelligence also plays a role when it comes to maintenance. It can detect system faults and malfunctions almost immediately. It can recognise what kind of problems are occurring and predict what kind of problems might occur in the future, making grid repair and maintenance much easier and more efficient.
What the European answer could look like – an example
How much carbon dioxide is produced during the manufacture of a car? And how can all production steps be optimised to save resources? The key to more sustainable production is data: on the one hand, machine data that the equipment in the factories continuously generates; on the other hand, mobility data that is generated when suppliers deliver engine blocks, car bodies or components to the manufacturers. The overarching use of this data brings several advantages. Not only does it make entire value chains transparent, but it also reveals which production step can be sustainably optimised.
The automotive industry is focusing on the GAIA-X interface. A project for the development of an efficient and competitive, secure, and trustworthy data infrastructure for Europe, which is supported by representatives from industry, science and administration from Germany and France, together with other, predominantly European, partners. The German Federal Ministry for Economic Affairs and Energy (BMWi) launched the GAIA-X initiative in 2019. The aim is to reduce dependence on American and Chinese IT providers and data-driven, market-dominating platforms. In the meantime, the project has gotten off to such a successful start that it is supported by several European countries and companies worldwide.
GAIA-X can help establish digital sovereignty, open architectures, European standards, and common values. And it is through the cross-sector, self-determined, secure and sovereign sharing of data that the GAIA-X platform comes to life. It enables collaborative and shared work and is one of the pillars of digital business models.
However, there is still a long way to go before the potential of the European data economy is fully exploited and there is a digital (domestic) market. So far, the economic and ecological potential has hardly been exploited. It is not only ownership, manufacturer and competitive interests that are bringing the flow of information to a standstill, but also concerns about the protection of personal data, such as in the healthcare sector. Let’s look at hospitals, for example, that no longer share sensitive medical data. GAIA-X, by providing digital infrastructure, helps ensure that instead of data, AI models are exchanged by doctors.
The goal must be to put Europe at the forefront of digitisation. This includes, for example, the exchange of data in the industry to produce cars more sustainably or the digital scalability of medical advances to improve the chances of healing.
To be more specific, the local economy must become more independent of individual cloud providers. And secondly, political framework conditions must be created that regulate the economic exploitation of data on an industrial scale.
What homework remains?
(1) Competition for talent
Germany has long contributed to academic research in artificial intelligence. But in such a dynamic field, the country must do more to distinguish itself globally. For one, to become attractive to international AI talent, Germany needs to improve its reputation in technology and innovation. Too many of the open AI positions in Germany could either not be filled, could be filled later than desired, or could be filled only with less desirable candidates. Germany is already struggling with a shortage of skilled workers. Especially in the field of AI, it will be even more difficult to find skilled workers.
(2) Upgrading the SMEs
The German government wants to promote the use of AI technology in small and medium-sized enterprises (SMEs) that are so important for Germany. Despite the government’s efforts, the so-called Mittelstand, which according to the Federation of German Industries (BDI) accounts for about one-third of the total sales of German companies, has been slow to embrace the use of AI. A recent study by the German Ministry of Economics found that only about 6 per cent of companies surveyed reported using AI technology.
Positive developments in this area in the future will depend on whether Germany succeeds in making greater progress in digitisation. An area in which it has notoriously lagged behind countries such as China and the United States.
(3) Broad societal dialogue and AI for the common good
As with SMEs, it is critical to support civil society in developing AI capabilities and competencies to harness the potential of AI for the common good. In addition, civil society involvement can foster widespread acceptance and trust in the technology among the population. There should be an institutionalisation of evaluation processes so that best practices can be identified and broad acceptance for the use of AI can be established.
The international race is about quality and speed, but Europe must not succumb to the temptation to emulate or copy. As Ursula von der Leyen, President of the European Commission, says, we must go our own, European way. Then our joint efforts will become an innovative endeavour. Digital technologies have the enormous potential to make our lives safer, better, and more comfortable. But it can also make life more sustainable.
An article by Michael Suckow, Senior Consultant at Zum Goldenen Hirschen, Germany.