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Low-emission mobility, climate-friendly energy supply, clean industrial production or optimized circular economy - Artificial Intelligence (AI) can contribute to climate protection in many ways. At the same time, the development and deployment of AI systems is often itself accompanied by high resource consumption. Where the technology can best unleash its potential and what needs to be done to keep the ecological footprint of AI applications low is explained in an interview by Oliver Zielinski, head of the Competence Center AI for Environment and Sustainability (DFKI4planet) and member of Plattform Lernende Systeme.

Artificial Intelligence (AI) supports people in medicine, mobility and everyday work. The basis for AI systems is training with data – often also personal information. The method of distributed Machine Learning (ML) can improve data protection in the development of AI applications because the data used is not bundled centrally, but remains on the end devices and thus with the users. However, this can also create new points of attack for cybercriminals. A concise overview of the potential and risks of distributed Machine Learning is provided in the first issue of AI at a Glance, a new publication series of Plattform Lernende Systeme.

Artificial Intelligence (AI) can help companies to operate in an ecologically compatible, socially just and successful manner. On the other hand, the use of AI systems can also run counter to operational sustainability goals, for example due to the high resource consumption of the technology itself. With its new publication, Plattform Lernende Systeme provides companies with strategic recommendations and numerous practical examples that show how the sustainable use of AI in the company can succeed. The experts advise strategically linking innovation and sustainability management in the company. This requires a comprehensive data infrastructure and digital skills.

AI systems can help find tumors, control insulin pumps or assist during operations. But on their way from research to healthcare, AI innovations in Germany have to overcome many hurdles. Karsten Hiltawsky explains the challenges facing manufacturers of medical AI products and what needs to change so that people benefit more quickly from the innovations. He is Head of Corporate Technology and Innovation at Dräger and head of the Health Care, Medical Technology, Care working group of Plattform Lernende Systeme.

Artificial Intelligence (AI) is changing everyday work in offices and factories. It is not only in industrial production that intelligent robots support people with heavy tasks. In the near future, AI-based assistance software will also be able to take over monotonous routine tasks and employ people at their desks. At the same time, its use poses challenges for all those involved - for example, in the handling of personal data or the humane design of working conditions. A fictitious application scenario from Plattform Lernende Systeme shows how employees benefit from a so-called information butler and how its introduction in the company succeeds.

Artificial Intelligence (AI) is already making our lives and work easier today - as a driving assistance system in cars, as a control element in production or as a recommendation system for online shopping. For the future, self-learning algorithms are considered a key technology for whose development and application specialists are urgently sought. Many universities have already launched corresponding courses of study. On the occasion of the nationwide Girls' Day, Ute Schmid explains why girls and women in particular should concern themselves with Artificial Intelligence and what role models there are. She is Professor of Cognitive Systems at the University of Bamberg and a member of Plattform Lernende Systeme.

Artificial Intelligence (AI) can improve medicine and care. Commercially viable business models help to bring AI innovations to the breadth of the healthcare system. However, the financing and approval of AI applications poses major challenges for medical technology companies, many of which are medium-sized. A recent white paper from Plattform Lernende Systeme discusses new business models and innovation processes that take into account the specifics of AI. In order for patients to benefit from the opportunities offered by this key technology, new instruments for cost coverage and advice centers for small and medium-sized enterprises are needed, it says.

Artificial Intelligence is a helpful tool that can make people's work and everyday lives easier in a variety of ways. At the same time, AI systems, which are often highly networked and partly embedded in other systems, can also be used for illegal purposes. Protecting them from misuse is an important task. Using the example of digital image processing, Detlef Houdeau (Infineon AG and member of the IT Security, Privacy, Legal and Ethical Framework working group) outlines how AI algorithms help professional and amateur photographers to take better pictures - but can also be used with criminal intent to forge travel documents.

Artificial Intelligence (AI) can make an important contribution to a sustainable orientation of the economy and society. The use of the technology opens up new business models for companies that support the success of the energy transition, low-emission mobility or environmentally friendly agriculture, for example. However, the energy consumption of the AI systems themselves is often high. A current white paper by Plattform Lernende Systeme shows how sustainable business models can be created with the help of AI and identifies design options that can reduce the ecological footprint of AI systems. In addition to technological measures, the experts recommend a broad exchange of data between companies, research and public authorities.

The EU Commission wants to regulate by law what Artificial Intelligence may and may not do. In its draft AI law, the Commission has defined a catalogue of criteria that will be used in future to assess the risks, the so-called criticality, of an AI system. Depending on the level of risk, an AI system can be banned, must meet certain requirements before it is introduced to the market. Armin Grunwald, professor of philosophy of technology at the Karlsruhe Institute of Technology (KIT) and head of the Office of Technology Assessment at the German Bundestag (TAB), explains why the assessment of risks in Artificial Intelligence is particularly difficult.

Companies generally expect that the use of AI will place new demands on employees - and want to qualify skilled workers and managers accordingly. Above all, technical skills in dealing with AI systems are not yet sufficiently available in the companies. These are the results of a recent online survey of companies conducted by the Fraunhofer Institute for Industrial Engineering IAO and the University of Augsburg for Plattform Lernende Systeme. The authors of the study warn against underestimating the need for further training of the low-skilled. Employees across all job profiles need to be empowered to work with AI systems. Besides technical skills, it is also about social skills.

Artificial Intelligence is a powerful tool that can be used to improve processes and develop new products and services. Many things are technically possible. But with what goal do we want to use AI as a society? A broad socio-political discourse on this is necessary to create framework conditions within which technical applications can be successfully developed and implemented. Jessica Heesen explains in an interview how this can succeed. The philosopher and media ethicist heads the research focus on media ethics and information technology at the International Centre for Ethics in the Sciences and Humanities at the University of Tübingen as well as the working group "IT Security, Privacy, Legal and Ethical Framework" of Plattform Lernende Systeme.

Artificial Intelligence (AI) is considered a key technology and will change our everyday lives and work. Nevertheless, many citizens have only a vague idea of what is meant by it. The new web offering www.ki-konkret.de from Plattform Lernende Systeme provides a sound introduction to the topic - and explains in a clear way how AI works, where it is already being used today and in the near future, and what challenges it poses for society.

We also encounter Artificial Intelligence (AI) in democratic elections. AI-controlled social bots in social media or deepfakes aim to influence the election decision. On the other hand, AI systems can provide people with individual voting recommendations and assist in detecting fake news. Which AI applications can be used in elections and where their potential and challenges lie is examined by Plattform Lernende Systeme in a current white paper.

Robots have long been a reality in large factories today. In a few years, supported by Artificial Intelligence (AI), they will also be able to assist employees in assembly in small companies. The prerequisite is that collaboration with the learning machines is safe and that people retain motivating, self-determined activities. In a fictitious application scenario, Plattform Lernende Systeme takes a look at the future of industrial work. The interactive graphic illustrates how collaboration with AI-based robot systems will change and what needs to be done to ensure that employees benefit from the self-learning tools.

Artificial Intelligence (AI) is increasingly changing the way we live. AI systems are also being used in democratic elections. In the run-up to the 2021 Bundestag elections, Plattform Lernende Systeme organised a virtual background discussion in cooperation with the Science Press Conference on 24 June to discuss the opportunities, but also the risks, of AI in relation to elections.

Self-driving cars on the roads are only conceivable in a few years. Intermodal testing and learning is still underway. The trust that drivers place in AI-supported assistance systems is crucial for the acceptance of automated vehicles. In the application scenario 'On the Way to Intelligent Mobility' developed by Plattform Lernende Systeme, the interaction between the protagonist Carla and her automated vehicle works well. Dr Corina Apachiţe explains in an interview how trust is created and what challenges still exist. She heads the Artificial Intelligence department at Continental Automotive and is responsible for the overall technical strategy and operational implementation.

There is a need to catch up in the transfer of AI knowledge to marketable AI-based applications. In a recent white paper, experts from Plattform Lernende Systeme show how the exchange of research results and application knowledge between science and companies can succeed and identify design options. They recommend promoting the training and recruitment of AI talent, cooperation between educational institutions and industry, and suitable framework conditions in companies and universities.

More than four million people in Germany are currently dependent on nursing care, and their number will increase significantly in the coming years as a result of demographic developments. Some care tasks could be taken over by assistance robots in the future. Elisabeth André explains which tasks they are suitable for, to what extent their use is to the benefit of professionals and those in need of care, and what needs to be taken into account when developing care robots. She is Chair of Human-Centered Multimedia at the Interdisciplinary Institute of Informatics of the University of Augsburg. At Plattform Lernende Systeme, Elisabeth André heads the working group "Future of Work and Human-Machine Interaction"

Artificial Intelligence (AI) can make our everyday lives easier, traffic safer and healthcare better. But realizing this potential requires trustworthy AI systems that people are happy to use. Certification of AI can increase trust in the technology. Jörn Müller-Quade explains what specifics need to be considered when certifying AI and why not all AI systems need to undergo testing. The professor researches cryptography and learning systems at the Karlsruhe Institute of Technology. He is also head of the "IT Security" working group of Plattform Lernende Systeme.

Self-learning robots and AI systems can provide support in space, in the deep sea or in the event of disasters - by exploring unexplored terrain or carrying out work in dangerous regions. To do this, the technical systems must act as autonomously as possible, but at the same time always remain under the ultimate control of humans. Jürgen Beyerer explains in this interview how these requirements can be implemented and where there is still a need for research. He is a professor of computer science at the Karlsruhe Institute of Technology (KIT) and director of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB. At Plattform Lernende Systeme, he heads the "Hostile-to-life Environments” working group.

Artificial Intelligence is on everyone's lips, and Machine Learning is an important driver of current technological development. But how do intelligent computer systems learn to solve tasks independently? An eight-part video tutorial series from Plattform Lernende Systeme conveys this in a clear way. Using catchy examples and supported by modern graphics, three students explain the basics as well as applications of Machine Learning in the approximately five-minute clips.

Artificial Intelligence (AI) is already used in many industries. To exploit its economic and social potential, it is essential that people trust AI systems and the processes and decisions associated with them. Certification of AI systems can help to increase trust in the technology. It is important to choose the right level of certification in order to maintain the innovative strength of Germany as a business location. In a current white paper, Plattform Lernende Systeme shows when and according to which criteria AI systems should be certified and how an effective testing infrastructure can be designed.

Artificial Intelligence (AI) will change the everyday working lives of many employees. The use of AI systems in companies offers many opportunities for both employees and companies. At the same time, the introduction of AI poses challenges for all those involved - such as the handling of personal data or the humane design of working conditions. A current white paper of Plattform Lernende Systeme shows by means of concrete solutions and practical examples, how companies introduce AI systems both in terms of employees and economic success and how change processes can be successful.

Artificial Intelligence (AI) is considered a key technology of the future and will increasingly become part of industrial and private software applications. Closely linked to the development of AI systems is the preparation and analysis of existing data, called data science. This is a future-oriented field of work for high school graduates. The interactive AI map of Plattform Lernende Systeme now shows at which universities in Germany they can find courses of study that focus on AI and data science or only deal with some of them.

The current corona crisis is accelerating digitisation in the economy and society - and thus also the use of artificial intelligence (AI). However, the pandemic is also revealing the weaknesses of digitisation in Europe: where data as a basis for AI is lacking, where bottlenecks in data processing become apparent, the technology cannot develop its full potential. The three-day European Big Data Value Forum 2020, which opened yesterday as part of the German EU Council Presidency, will focus on how secure and high-performance data rooms and infrastructures can be realised across Europe and how successful, trustworthy AI can be created from Europe on this basis. Plattform Lernende Systeme is a partner of this year's forum.

Artificial Intelligence can make our everyday life easier and help to solve global challenges. To what extent AI-based systems are actually used depends largely on whether people trust the technology. Ethical values and principles play a central role here. Plattform Lernende Systeme has now written a guideline and specifies requirements for responsible AI development and application in companies.

The digital age is changing production processes and value chains worldwide - and thus poses great challenges for companies. Small and medium-sized enterprises (SMEs) in particular are often unaware of the data treasures they have at their disposal in their operations - and how these can be harnessed using methods of Artificial Intelligence (AI) and machine learning. Plattform Lernende Systeme shows small and medium-sized enterprises with a special web offer (in German) how they can benefit from the use of Artificial Intelligence and where they can find information, public funding and practical support.

Which AI applications are already in use in Germany today? Where is research being conducted into the fundamentals and applications of Artificial Intelligence? And who supports companies in the introduction of AI in their operations? The continuously expanding Map on AI of Plattform Lernende Systeme provides an overview of AI applications, research institutions and transfer centres in Germany - now also in an English version.

Companies must enrich their physical products with intelligent services and change their business models accordingly in order to remain internationally competitive. This requires new forms of cooperation in so-called digital value-added networks. Svenja Falk, Managing Director at Accenture Research, explains the advantages of these networks and why data- and AI-driven applications are also interesting for SMEs.

In the coming years, Artificial Intelligence (AI) will fundamentally change both entrepreneurial business models and many jobs - in large corporations as well as in medium-sized companies. This is because the intelligent linking of corporate data will enable new products and services to be developed and processes to be optimised. Learning assistance systems can support employees individually in their work. Where we stand on the way to an AI-supported economy and what challenges this poses for entrepreneurs and employees was discussed by experts from Plattform Lernende Systeme in two web-talks with virtual guests on 6 July.

Who protects our data? Who decides what is private and whether there is a right to data ownership? These questions were discussed by Claudia Eckert from the Technical University of Munich and Jörn Müller-Quade from the Karlsruhe Institute of Technology (KIT) - both members of Plattform Lernende Systeme - on June 30th at acatech on Tuesday via Zoom with the guests who were connected. The event was held for the first time together with vhs.wissen live and the Bavarian Adult Education Association.

Logistics is a highly complex and networked system, which is today still mostly optimized manually, both within and across companies - and is quickly impaired in the event of unforeseen events. Sören Kerner, head of the Automation and Embedded Systems department at the Fraunhofer Institute for Material Flow and Logistics IML, explains how logistics processes can be optimized with the help of AI and what obstacles currently stand in the way.

The corona pandemic poses unprecedented challenges for the economy and society. Solutions and strategies are needed to overcome the current crisis and to create a "New Normal" in the post-crisis phase. The Steering Committee of Plattform Lernende Systeme discussed the potential of digitisation and Artificial Intelligence (AI) in its seventh session, which was held as a web conference. Further topics were the current work priorities of the platform.

Artificial Intelligence methods can contribute in many ways to meeting current challenges of the corona pandemic. Prof. Dr. Frank Kirchner, head of the Robotics Innovation Center at the Bremen site of the German Research Center for Artificial Intelligence (DFKI), provides an overview of potential applications, practical limitations and important research priorities. 

How can Europe move forward in the global race for technological leadership in Artificial Intelligence? Katharina Morik, Professor for Artificial Intelligence at the TU Dortmund University and member of the Plattform Lernende Systeme, coordinates the cooperation of the AI competence centres in Germany and France on the German side. In our interview, she explains why European countries need to join forces in AI research.

Digitisation is not an end in itself for SMEs, but a prerequisite for them to operate successfully in an increasingly networked economy. Many small and medium-sized companies still lack clear ideas about how they should approach the future topic of Artificial Intelligence for themselves. Susanne Boll-Westermann from the University of Oldenburg explains which questions they should ask themselves and why networking with other players is so important.

When the German Federal Government published its National Strategy for AI, it provided a framework for establishing the international competitiveness of Artificial Intelligence made in Germany. To coincide with this, Germany’s federal states are also driving forward the development and application of AI. Putting the knowledge gained from research into practice is a vital factor in commercial success. The AI map created by Plattform Lernende Systeme extends this initiative’s comprehensive overview of AI applications and research institutions, indicating the federal states’ strategic goals and the locations where regional transfer hubs are overseeing implementation.

Self-learning systems will penetrate our everyday life in the coming years, and skilled workers are already desperately needed. Reason enough for young people to think about doing "something with AI" in their careers. Our member Elsa A. explains why the topic is fascinating and what is important in AI development. Kirchner on the occasion of the nationwide Girl's Day.

Cancer patients should be able to benefit more swiftly from research findings. This is the aim behind the National Decade Against Cancer, which was recently launched by the German Federal Ministry of Education and Research (BMBF). In its latest application scenario, Plattform Lernende Systeme demonstrates how Artificial Intelligence (AI) will be able to improve the recovery chances of cancer patients in the near future.

Germany’s federal government today finalised its Artificial Intelligence (AI) strategy. The goal is to establish “AI made in Germany” as a seal of quality for conscientious AI and make up ground lost to international competitors. Plattform Lernende Systeme – Germany’s platform for Artificial Intelligence – is to contribute to broad societal dialogue on AI.

Dieter Spath, President of acatech – the German National Academy of Science and Engineering, is stepping down from his position as Co-Chair of Plattform Lernende Systeme, to be succeeded by Karl-Heinz Streibich, who has been at the helm of the Academy alongside Spath since May 2018.

When it comes to artificial intelligence (AI) Germany has very good prospects on the international stage. If it can quickly turn its well-established head start in research into applications focusing on practical uses, Germany can take the lead in the AI race. This was the message that Plattform Lernende Systeme, Germany’s platform for artificial intelligence, delivered at this year’s CEBIT.

Germany is leading the way when it comes to researching and developing artificial intelligence (AI). If this expertise can be put to use quickly, Germany can secure global technological leadership and drive forward the responsible use of self-learning systems both at home and abroad.

Self-learning systems are the key to meeting the increasing requirements of productivity in an ageing society and to preserving prosperity, says Mr Dieter Spath in conclusion of his presentation on 22 January at the Munich School of Philosophy.

Artificial intelligence (AI) and self-learning systems will become the drivers of industry in the coming years and will at the same time change many realms of society. Fraunhofer-Gesellschaft, in cooperation with Germany’s digital association Bitkom, invited stakeholders to Artificial Intelligence Day, a networking event held in Berlin on 29 November.

The Federal Ministry for Education and Research (BMBF) is reinforcing research on artificial intelligence and launching the forward-looking project “Learning Systems”. As a first step, a new expert platform is being established in order to improve the collaboration between research and application as well as clarify how learning systems can be useful for humans.