How artificial intelligence changes work and personal life

Many people have been talking about artificial intelligence for quite some time now. However, far fewer people are capable of explaining what AI actually is. So, what’s it all about? … The term Artificial Intelligence was coined by the U.S. mathematics professor John McCarthy in 1956. So the concept is by no means as new as people think. The topic captured more public attention in 1997, when the chess computer Deep Blue beat the world champion in chess at that time, Garry Kasparov. That was more than 20 years ago, and chess computers are no longer really revolutionary.

A recent example shows what AI can do today. Compared to chess, the Chinese board game Go for a long time was considered too complex to be played by computers. This complexity is due in part to the fact that the number of possible combinations of playing pieces on the board exceeds the number of atoms in the entire universe. However, in 2016 the AI-supported AlphaGo program beat the world’s best Go player by 4 to 1. This feat attracted attention. However, an even greater stir was caused by an enhanced version of this program, AlphaGo Zero, which was matched against AlphaGo, so that two computers were competing against each other. What made the enhanced program notable is that it had learned the optimal strategy not from previous games played against human players, but by playing against itself. This type of machine learning is referred to as reinforcement learning. The astounding result of this match is that AlphaGo Zero beat AlphaGo 100 to 0. This example was taken from the book Realitätsschock (The Shock of Reality) by the German blogger and writer Sascha Lobo. It impressively demonstrates the potential of AI.

Steven Peters heads the Artificial Intelligence Research team at Daimler’s Group Research. For years now, Peters has been working on specific projects that use AI as a tool for the development of new automobiles. But even for a researcher like Peters, the dynamic development of AI in recent years is breathtaking. When asked exactly what AI is, he replies, “The AI processes of today are basically machine learning, which is also referred to as statistical learning. This shows that AI is ultimately a field of mathematics. Today’s cutting-edge IT systems can process gigantic amounts of data. AI uses this data as a basis in which it can recognize complex patterns. The complexity and the quality of the patterns depends on the quality of the data.” Will this technology that can learn new things be used more and more often in business and in various other areas of life? Almost certainly! That’s one of the reasons why it pays off to take a close look at AI and its impacts. Another reason to take note is that technological developments don’t only cause rejoicing — they also always have the potential to generate vague fears.

New technology, old fears

“Man proposes, God disposes,” as the old saying goes. However, many people are disturbed by the idea that we are handing over at least some of the “proposing” and “disposing” to machines and computers. It’s a very distinctive fear of the possibility that the technology we once created to serve us could one day turn against us. It’s not only Hollywood movies such as The Matrix and Terminator that embedded this fear in the collective consciousness; Goethe’s Sorcerer’s Apprenticetoo was unable to get rid of the spirits he had summoned: “Ah, my terror waxes stronger!” People who dislike cinematic or lyrical references like these may point to a chilling real-life example: nuclear energy, which ultimately cannot be completely controlled either and harbors many risks despite the many advantages it brings.

Of course it’s no news that technical innovations always encounter some skepticism and fears. That was the case with the invention of the telephone (fear of espionage and lightning strikes), the radio (fear that people might no longer be able to concentrate), and, of course, the automobile. When Carl Benz first presented his Patent Motor Car to the public in 1886, the new technology caused a great deal of concern. The vehicle was noisy and smelly, and the fuel it required was an explosive mixture. On the other hand, people had been well accustomed to horses for centuries. Horses fed on hay, neighed at the most, and even though the smell associated with their use wasn’t sweet it was at least very familiar. Today telephones, radios, and automobiles are an integral part of daily life. They symbolize technological progress, and they have been continuously enhanced and adapted to people’s needs. Although nobody would want to do without them, it’s nonetheless still important to use them discriminately, even after more than 100 years. This is particularly evident in many people’s almost omnipresent use of the smartphone — a highly evolved telephone.

From a niche product to a mass market

“We have to demystify AI. By that I mean we have to educate people in order to take away their fears, show them what the actual opportunities are, and at the same time dampen exaggerated expectations,” responds Patrick Klingler, who works as an innovation manager in Daimler’s IT unit. As an expert on AI, Klingler’s task is to implement data-driven products, services, and processes — or, as people say at Daimler, “put products on the road.” This saying can be taken quite literally. As Klingler puts it, “Artificial intelligence is no longer science fiction; it has grown up. It’s not about creating technical gimmicks but about developing more efficient processes as well as better products and applications for customers.” AI can already be very useful in these ways, and it will become even more useful in the future. However, additional investments in this technology — and in the realm of culture — will be needed before AI’s full potential can be exploited, Klingler explains.

Together with his colleagues Steven Peters from Group Research and Johannes Deselaers, responsible for big data and analytics, Klingler wants to make sure that AI in the Group doesn’t become a niche for technology nerds but instead an accepted future-oriented technology that affects everyone. That’s why the company organizes international meet-up to which all interested Daimler employees are invited so that they can get information and ask questions. According to Deselaers, “The concept helps us to take a topic that many people regard as complex, bring it down to earth, and make it transparent. Up to 100 colleagues now come to these meet-ups every month. Currently, their meetings are virtual, due to the Coronavirus pandemic – but still, many join the virtual discussion or follow the live stream. This shows that more and more people are studying this topic and are interested in it.” That applies to the management as well. “We have our own mentoring program, in which we teach the Group’s top executives about this topic. This instruction is not only theoretical; the managers also get some hands-on training and do some programming. This deepens their understanding of the topic and creates a basis for an open dialog,” adds Deselaers, who is delighted about the noticeable cultural shift that has begun at Daimler. “Managers can sometimes be mentees who want to learn about new developments,” he says. The strong interest in this topic is also evident in the AI Community on the Daimler intranet. With almost 4,000 members, it’s one of the intranet’s biggest communities — and one where there is especially lively interaction.

Klingler and Deselaers are representative of a new generation in the automotive industry. They aren’t traditional car guys with the proverbial gasoline in their blood — they’re experts on software and IT. They want to transform the automobile, and to a certain extent the entire Group from the inside, in order to make cars and the Group fit for the mobility of the future. People like them are needed, because Daimler is a company that is increasingly evolving into a software firm. That’s because today’s automobile production involves more than just steel and sheet metal — it’s also a matter of bits and bytes. The two experts are convinced that AI will make daily life and the world of work simpler and more comfortable. This is what’s happened with previous technologies, which have proved to be beneficial for humanity. “But AI doesn’t simply pop up overnight. It is introduced step by step in many areas, and individuals ultimately decide where it’s useful for them and where it isn’t. Because this is a decision AI cannot make for itself. Nor can machine learning make ethical or moral decisions or resolve conflicts. It can only apply rules that it has learned in the past and update these rules on the basis of the latest information,” says Klingler. AI is appreciated not only by IT experts but also by business managers. A recently published joint study conducted by eco — Association of the Internet Industry — in cooperation with the business consulting firm Arthur D. Little forecasts that the use of AI could boost Germany’s gross domestic product by more than 13 percent over the next five years.

However, because there isn’t only one single AI, it is important to distinguish where this new technology will be used or has already been introduced to some extent. Including at Daimler.

Where Mercedes customers are already encountering AI

In recent years, more and more people have gotten their first taste of AI-supported products. Google, Alexa, and the streaming service Spotify are a few examples. All of these systems process data from individual customers in order to understand their behavior so that they can offer or suggest exactly the items or services that will interest them. Thanks to the introduction of the infotainment system MBUX (Mercedes-Benz User Experience), this has also become a reality in more and more vehicles from Mercedes-Benz — if the customer wants it. The customers themselves decide which services they would like to use and which data they would like to disclose. Conversely, this also means that customers can choose to deactivate these systems.

MBUX is far more than simply a voice control system. In some of its aspects it’s also a self-learning system, and thus it is AI-supported. For example, on the basis of the driver’s behavior patterns it can anticipate the next thing he or she might ask for. For example, if the driver often talks on the phone with a certain person on the way home on Tuesdays, that person’s number will be suggested on the display on Tuesdays. And a driver who regularly listens to Rammstein on the way to the fitness studio will receive a selection of the band’s songs as a recommendation. But plans also call for the system to be able to understand and answer complex questions in the near future. They might be questions about sports (“Hey Mercedes, how did Bayern Munich do today?”), the stock market (“How did the Daimler share develop last week?”), or general knowledge (“What’s the population of Heidelberg?”).

But that’s not all. The MBUX Interior Assistant can even recognize and process gestures. A camera captures the hand and arm movements of the driver and the front-seat passenger. If a hand approaches the touchscreen or the touchpad on the center console, the image on the media display changes and individual elements are highlighted. The system can distinguish between the driver’s hand and the passenger’s hand, so it also knows at whose seat the massage function has to be adjusted, for example. There are also functions that can be controlled by means of simple hand movements. For example, the reading light can be switched on and off by moving a hand toward the interior mirror. And the driver as well as the passenger can each register a favorite personal function such as “Navigate to home” or “Call the office.”

And the new Mercedes-Benz S-Class, which will enter the market later this year, will bring MBUX to a completely new level. An exclusive glimpse into the digital cockpit of Mercedes’ new flagship  was already part of Daimler’s Virtual Annual Shareholder Meeting four weeks ago.

Another example of AI-supported technology for customers is the chatbot “Ask Mercedes.” Cars are becoming more and more technically complex. The virtual assistant’s job is to help drivers quickly get their bearings inside their new cars without having to study a thick manual. This is how Klingler explains the practical utility of the virtual assistant: “With the help of a smartphone app, the driver can ask questions about how to use the car. For example, ‘How can I use Bluetooth to connect my smartphone with the car?’ ‘How can I change the interior lighting setup?’ Or, ‘How does the automatic parking assistant work?’ The chatbot knows the answers to customers’ most frequently asked questions, and it’s always learning more. This is real added value for the customer, and it also draws customers’ attention to the innovative functions of the vehicle so that they can enjoy using them on a daily basis.”

AI is also playing an increasingly important role in vehicle sales, for example in the loan approval process. Today work is already being done to develop an Artificial Intelligence Credit Agent. “In the future, we want the AI Credit Agent to conduct the entire credit process automatically. That will be a crucial first step toward establishing successful online sales processes. Within a few seconds, interested potential buyers will receive a response to their inquiry, including alternative offers. Our goal is to simplify and accelerate the loan approval process,” explains Tobias Deegen, who is developing the AI Credit Agent together with his team at Daimler Mobility.

Where the journey could lead

At the recent Consumer Electronic Show (CES) in Las Vegas, Mercedes-Benz impressively showed what a connection between human beings and their cars could look like some decades — with the Vision AVTR. Its name is not only an homage to the blockbuster film “Avatar” but also stands for Advanced Vehicle Transformation. In fact, the AVTR was created in cooperation with the team of the filmmaker James Cameron. In addition to the futuristic design, what makes this car so special is primarily its interior. Instead of the traditional steering wheel, there is a multifunctional control element in the center console. At the touch of a hand, the car’s interior comes to life, and the vehicle recognizes the driver by means of his or her breathing pattern. When the occupant’s hand is lifted, a menu is projected onto the palm of the hand so that he or she can intuitively choose between various functions. For example, 3D graphics can be used in real time in order to explore the fictional world of Pandora (or, theoretically, the real world of a town such as Castrop-Rauxel) from various perspectives. The curved display creates a visual connection between the vehicle occupants and the outside world. The energy concept is equally progressive: Sensors and chips, their design inspired by the human brain, reduce the vehicle’s electronic energy requirement to only a few watt-hours.

It is powered by the temporarily stored electricity that has been generated by the solar panels mounted on the rear of the vehicle. The 33 movable surface elements serve as bionic flaps. Thanks to organic cell chemistry, the battery does not need any rare earths or cobalt. The materials are compostable and fully recyclable. Naturally, all of this is a dream of the future, and the AVTR is only a study. But it does show how fascinating the connection between human beings, machines, and the environment could become very soon if the further development of sensor technology and elements of artificial intelligence continues.

Automated driving is impossible without AI

People who are seriously talking about automated driving know that it won’t work without AI. The Active Distance Assist DISTRONIC already uses data from camera and radar sensors. The crucial element here is the interaction of the functions — that is, between the sensor system and the navigation system. That’s what enables the system to take foresighted action regarding other road users, road markings, occurrences along the route, and traffic signs — and to intervene in the traffic situation when necessary. But does this mean that AI is already in operation? Markus Enzweiler from Research and Development at Mercedes-Benz has a nuanced answer to this question: “It’s not easy to clearly differentiate these concepts. What we can say is that on the basis of the patterns it has learned, a system of this kind can already understand today the information sent to it by various sensors and interpret it correctly. We call this ‘deep learning.’ However, in its current status the technology has not yet reached the goal of understanding traffic situations in the human sense of the word.”

As a result, in partly automated driving the responsibility continues to lie with the driver, who must be able to react to every new situation at any time. However, it’s undeniable that in the future even more wide-ranging automated functions must be able to collect and combine more data. “Fully automated driving can be technically achieved only if IT systems can autonomously evaluate complex situations, simultaneously receive external information, and act on the basis of all this data — for example, if they can autonomously give way to another road user in a traffic circle. All of this would require a kind of machine intelligence that could be subsumed under the concept of artificial intelligence,” says Enzweiler.

The basis for every kind of system decision is always the prevention or minimization of damage. Before vehicles can actually drive fully automatically, numerous legal and ethical questions will need to be clarified, not only at the national level but also internationally. Who will be ultimately liable in case of an accident? The occupant, the manufacturer, or the system provider? At present, no conclusive answers to the above are yet available.

But the development in this direction does continue to gather pace. And the strategic partnership between Mercedes-Benz and NVIDIA, the software specialist company and chip manufacturer from California, signed in June, is further evidence for it. The cooperations aim is a new, software-driven vehicle architecture across all models which will enable automated driving functions with new AI elements and over-the-air updates. Starting in 2024, this technology is planned to be available in new vehicles.

Because one thing’s for certain: automated driving will make future mobility more efficient, safer, and more comfortable. That’s because in some respects — such as reaction time — technology is already superior to human beings today.

AI in production

In the future, artificial intelligence will play an ever larger role not only in products but also in the production process itself. Industry 4.0 and human-robot collaboration are being increasingly integrated into state-of-the-art industrial production. Anyone who takes a look at the production halls at Daimler will immediately see that today production processes are more interconnected than ever before, and the number of robots in production is also growing. Incidentally, Germany is in the forefront of this development, according to a study conducted by the International Federation of Robotics (IFR). Germany has 309 robots per 10,000 employees. That puts it in third place globally, behind South Korea (631) and Singapore (488) but ahead of Japan (303). And our “mechanical colleagues” are not only working behind protective glass walls. For a long time now, they have been working hand in hand with their flesh-and-blood coworkers. This doesn’t mean that human beings are handing over their scepter to the robots — only that human beings and machines complement each other, and that machines are able to take on increasingly complex tasks with the help of AI algorithms and thus reduce the workload of human beings.

According to the business consulting firm Capgemini, more than half of the biggest globally operating companies have implemented at least one experimental AI project. Daimler has already implemented many such projects. One of the application examples is logistics planning. For example, the assembly of a Mercedes-Benz A-Class vehicle requires up to 5,000 components. Today AI algorithms are already successfully controlling the related material flow and the supply process. Another example is the development of automated object recognition in production and logistics processes through the use of neural networks. To make sure that the AI can reliably recognize objects such as load carriers, the recognition patterns are not permanently programmed — instead, they are “learned” by means of many sample images. Thus the processes can be optimized by means of camera-based systems.

A third and last application example is that employees in production benefit from suggestions for efficient rework that AI methods can make. This means that a system calculates the current quality status for a certain area from all available production data. Quality management representatives and production workers are proactively informed about this status on their smartphone or handheld device. This system is known as QUALITY LIVE and it is part of Mercedes-Benz Cars Operations 360 (MO360), the digital production ecosystem of Mercedes-Benz. MO360 integrates data collected in the most important production processes and IT systems at more than 30 Mercedes-Benz cars plants worldwide. As a result, employees can not only get the 360-degree overview that the eco system is named after, but they also receive the exact piece of real time information they need for the next production step.

These use cases show that artificial intelligence is helping human colleagues to carry out their routine tasks — but it is not replacing them. AI relieves people of some of their work so that they can focus on the tasks that still require human intelligence. As a result, at Daimler we are certain of one thing: Our use of artificial intelligence will not result in factories whose production halls are devoid of human beings.

Technology with intelligence — use with reason

The examples above do not claim to represent the whole picture, nor do they aim to explain the complex theme of AI from a scientific standpoint — such explanations can be found in the specialist literature. Within the framework of this article, we have aimed to explain in clearly understandable terms what AI is already (and what it isn’t) and where this journey will probably take us in the future. In the process, we’ve tried to avoid myths and fears. One thing seems obvious: Whether it’s in production systems or products, the development of increasingly efficient and technically sophisticated systems will also increase the utilization of AI. It’s less a question of whether, but rather of how this technology will change products, processes, and working methods. The one thing we must always keep in mind is that technology ought to serve human beings, rather than the other way around. Ethical aspects must not be an afterthought — they have to play a central role, long before a technology is launched on the market. As Eva Weber-Guskar, a professor of ethics at Ruhr University Bochum, put it in an article titled “Auch Nerds brauchen Ethik” (Nerds Need Ethics Too) in the newspaper Die Zeit last February, “We need IT specialists, especially AI specialists, who can not only confidently deal with concepts such as intelligence and consciousness but who already know during the product development process where ethical and normative questions will arise and what chains of responsibility will be created.”

For this reason, Daimler has committed itself to four principles regarding artificial intelligence — in order to be able to deal with AI responsibly and sustainably. First, the responsible use of AI must be safeguarded by making sure that it is compatible with our corporate values. Secondly, we commit ourselves to a high degree of transparency in order to promote trust in artificial intelligence. Thirdly, data protection and respect for individual privacy must always be safeguarded — not as an afterthought but already in the development phase. And fourthly, AI-supported technology must operate safely and reliably. That applies especially to cases in which the technology continues to learn or in which it is subjected to attacks from outside.

At Daimler we consider it important to take opportunities and risks into account. That’s why we have an interdisciplinary team (which includes experts in the humanities and communications) in the Integrity and Legal Affairs executive division. It works together with engineers, lawyers, and experts in the fields of data protection, compliance, and strategy to assess the possible effects of technical innovations in advance, sharpen awareness of complex social and legal topics, and develop and implement solutions. At the same time, we are calling for an open and transparent dialog about these topics in order to put the public discussion, which can sometimes become very emotional, on a more objective foundation. We are convinced that this is the only way artificial intelligence will be able to optimally support us and offer significant added value — for our employees as well as our customers.

You can find further information, use cases, and interviews with experts on the topic of artificial intelligence on the AI Hub at Daimler.com