The ships piled up and within a very short space of time a serious stress test was created for the global supply chains and industrial production, which are normally precisely coordinated. The consequences were felt for a long time. German insurer Allianz calculated that the incident could have cost global trade 6 to 10 billion dollars a week, and the shipping industry was still struggling with the immediate effects a month after the incident, according to media reports.

Crises like the one at the Suez Canal raise the question of how such events can be avoided in the future. One way is through technological innovations, specifically autonomous systems. They are likely to become established in the coming years and make many areas more flexible, more economical and, not least, safer: From industrial production to transportation routes on water and land.

What added value do autonomous systems bring?

However, shipping is just one of many use cases: Autonomous systems will make life safer, more productive and more efficient in all sectors and industries. Many players are working on using autonomous systems to tackle the major challenges of the 21st century - including climate change and digitalization.

For example, autonomous systems can be used for industrial IoT and tracking applications with a variety of sensors. They can operate public transportation and production lines in factories with lower_{CO2 emissions} and efficiently control the electricity consumption of cities. They ensure greater sustainability in agriculture and food production, avoid environmentally damaging land consumption and at the same time increase productivity per cultivated hectare. And they support medical and care facilities in countries with ageing populations and help to close skills gaps in the digital economy.

What are autonomous systems?

The terms "autonomous" and "automated" are often confused with each other. While automated systems use machine learning and artificial intelligence (ML/AI) and operate within well-defined parameters, such as a production line, autonomous systems are able to learn and adapt to dynamic environments. As can be seen in tests with autonomous cars, they react dynamically to changes in external conditions. They use ML/AI for reliable decision-making and have the ability to learn and react to new situations. Autonomous systems intelligently translate predetermined strategies into actions that are appropriate to the situation. Autonomous systems can perform heavy physical labor, enabling humans to work closely with machines and things to solve complex problems.

Studies by Nokia Bell Labs Consulting predict that digital transformation, artificial intelligence (AI) and machine learning (ML) will create new types of jobs. For example, connectivity with low latency and high 5G data rates will enable maximum efficiency and flexibility in building a factory. Typically repetitive or dangerous tasks, such as mining or handling hazardous materials, can either be replaced by machines, or machines can help workers perform their tasks safely. Similarly, some activities that were previously carried out by specialists can be expanded and made more efficient by AI/ML.

Autonomous systems can also increasingly protect companies from cyberattacks. In May 2021, for example, the DarkSide ransomware attack on the Colonial Pipeline in the south-east of the USA forced the operator to shut down operations. This resulted in supply problems, which led to panic buying and rising prices in some US states. Autonomous systems could have helped here through early detection and the initiation of countermeasures. They are able to use artificial intelligence to learn what is "normal" or unusual for a company without having to rely on specific prior knowledge of threats. Ideally, they will recognize unprecedented threats and fend them off before any damage is done.

What does autonomous production mean?

Production and logistics companies are among the pioneers in the use of increasingly autonomous systems. First of all, they are automating supply chains and warehouse processes in logistics and adapting them to production and delivery requirements, resulting in safety and efficiency benefits. The use of autonomous systems increases the quality of forecasts and process stability, optimizes purchasing, distribution and logistics, reduces the error rate and minimizes the time required for sorting, picking and storing stock. Many of these elements can already be observed in Nokia's Conscious Factory in Oulu.

A look behind the scenes of autonomous 5G systems

In addition to ML/KI, 5G technology makes many scenarios possible, particularly through high-speed wireless connections on factory floors. The upcoming 5G standard 3GPP Release 18 is expected to reduce latency to less than 10 milliseconds and reduce the accuracy of positioning indoors to 1 cm and outdoors to 10 cm. The standard is expected to be adopted in 2023. Products for use in industrial applications should be available around two years later. This makes the 5G standard ideally suited to many of the emerging use cases in connection with autonomous systems. For example, the ultra-fast responsiveness and high-precision positioning of 5G makes it easier and safer for driverless transport systems and other machines and robots to work with each other and with people. Sensors in automated guided vehicles and 5G-enabled devices ensure that these systems do not interfere with the people around them, and in the event of an emergency, full wireless shutdown can take place without delay. This 5G-based use case for manufacturing companies is of great importance to them and is about to be introduced by Daimler and Bosch, for example.

In addition to technological changes, autonomous systems also require changes in business logic and key issues such as customer relationship management, supply and demand management, and production and supply chain management. The development of autonomous systems is complex; it requires technology investments and a new way of thinking in terms of collaboration and ecosystems.

What happens next?

As soon as autonomous systems determine decisions and actions, the number of parameters that need to be taken into account, for example in comparison to automated systems, increases. It is important for companies to understand how they can ensure transparency, safety, legal responsibility and the ethics of decisions made by machines.

Because no matter how well we build and program systems: Mistakes will happen. This can mean that an autonomous vehicle collides with a fixed object on the factory floor or causes an accident, which is why the issue of safety goes hand in hand with legal responsibility. Who is responsible if a robot causes an accident? Is it the operator, the manufacturer, the software developer, the AI or the network connection? If human lives depend on machine decisions, who assumes the insurance risk? These legal questions need to be clarified before widespread introduction can take place.

So, at its core, it is about the ethics of artificial intelligence. If an autonomous system uses learning algorithms to achieve the best results, how is it determined what is "best" or "right"? The responsible use of technology and data, the ethics of AI and the division of responsibility are important questions. Standards are needed to ensure that different systems can be integrated and communicate with each other and together provide added value. For example, autonomous systems should only be used for the system for which they were developed to avoid misuse. We must always check them for potentially negative effects on individuals and society. And because autonomous systems are changing the future of work, political decision-makers must ensure that the machines and the software and algorithms that control them are taken into account in legislation. And the decisive factor: Humans must retain control over the machines.

In the longer term, autonomous systems then have the potential to help companies go beyond the production of goods and services. For example, the EU has launched a research and innovation project, Industry 5.0, which focuses on the business model of shared value creation. The well-being of workers is at the heart of the production process here, which uses new technologies such as 5G and other digital technologies to create new jobs.

Although technological breakthroughs are rarely characterized by a single event, in a few years' time we will perhaps see the Suez blockade as a crucial piece in the mosaic for the rise of autonomous systems. The change is already underway and profound, thanks to state-of-the-art software, sensor technology and, not least, communication technology.

Harry Kaib, Head of Marketing for Germany at Nokia