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Generative artificial intelligence (AI) is rapidly changing our society. Applications such as ChatGPT, Gemini and DeepSeek create realistic-looking images, compose music, conduct human-like conversations and translate almost in real time. Generative AI is thus not only shaping how we work, learn and communicate, but also increasingly how we as a society understand knowledge, creativity and responsibility. At the same time, however, its use raises social and ethical questions: How can human competence remain at the centre? How can we ensure authenticity and trust when AI content appears deceptively real? And what rules are necessary to combine innovation with fundamental ethical values, sustainability and social justice? The new brochure from Plattform Lernende Systeme shows how a value-oriented approach to generative AI can succeed and provides guidance, perspectives for action and food for thought.

Artificial intelligence (AI) is to be specifically expanded as one of the key technologies by 2030, according to Germany's Hightech Agenda. Together with Dorothee Bär, Federal Minister for Research, Technology and Space, key measures to strengthen technological sovereignty, particularly in the field of artificial intelligence, were discussed at the 16th meeting of the Steering Committee of Plattform Lernende Systeme (PLS) in Berlin. The key factors are the definition of measurable targets and interdepartmental coordination. The meeting was chaired by acatech President Claudia Eckert.

As a pioneer in AI research, Germany has been well positioned and internationally networked for many years. Not only science, but also the German economy – from start-ups and SMEs to large companies – is increasingly exploiting the potential of AI. At the same time, key questions arise: Where is the technology heading, and what fields of application are emerging? How can Germany and Europe remain competitive in the global arena in the long term – while at the same time acting in a value-oriented manner? How can we remain technologically sovereign, and how is AI changing society? Plattform Lernende Systeme discussed these questions with over 200 guests at its conference ‘KI & WIR.: Stärken nutzen, Vertrauen sichern, Souveränität bewahren’ (AI & US Conference: Leveraging strengths, securing trust, maintaining sovereignty) on 30 September in Berlin.

AI-based medical devices support modern healthcare in many areas and automate routine tasks. They reduce the workload on specialist staff, enable more accurate diagnoses and improve patient care. However, their development and market launch are subject to strict regulatory requirements. With the AI Act, which has been in force since 2024, additional requirements for the introduction and use of AI have been added to the existing Medical Devices Regulation (MDR). This poses considerable challenges for the German medical technology industry, which is predominantly made up of small and medium-sized enterprises, and for start-ups. The current discussion paper from Plattform Lernende Systeme outlines the key requirements of the AI regulations for medical technology, highlights their implications and explores the question of how patient safety and the promotion of innovation can be reconciled.

The use of artificial intelligence (AI) is changing processes, task allocations and organizational structures in companies. AI is fundamentally changing the interaction between people and technology and is therefore also having a lasting impact on corporate culture. The changes are particularly evident in the culture of innovation, internal communication and cooperation. A current impulse paper from Plattform Lernende Systeme shows the company levels at which AI is driving cultural change in the company and which changes are necessary to make the use of AI human-centered. Use cases illustrate how employees' reservations regarding the introduction of AI can be successfully overcome and how they can be actively involved in processes.

With the rapid spread of chatbots, artificial intelligence (AI) has become tangible for many people in their everyday lives. How and why ChatGPT and other AI-based systems achieve their results often remains opaque to users. What exactly happens in the ‘black box’ between model input and output? In order to make the results and decision-making of complex AI systems comprehensible, algorithmic decisions must be explainable. This can improve model quality on the one hand and strengthen trust in AI on the other. A current white paper from Plattform Lernende Systeme shows which methods and tools can be used to make AI results comprehensible for different target groups and provides design options for research, teaching, politics and companies.

Federal Research Minister Dorothee Bär and acatech President Claudia Eckert form the new dual leadership of Plattform Lernende Systeme. As co-chairs of the steering committee, they will steer the strategic and content-related direction of the network of experts on the topic of artificial intelligence (AI). They succeed former Federal Minister Bettina Stark-Watzinger and outgoing acatech President Jan Wörner.

The first provisions of the AI Act have been in force since February 2025 - among other things, providers and operators of AI systems are obliged under Article 4 to train their employees in the use of Artificial Intelligence (AI). This concerns the need to impart sufficient technical AI skills and to ensure an understanding of the social, ethical and legal aspects of the use of AI. In this interview, Uta Wilkens explains what this means in concrete terms for companies, what skills should be taught and what challenges remain. She holds the Chair of Work, Human Resources & Leadership at Ruhr University Bochum and is spokesperson for the HUMAINE competence centre as well as a member of the ‘Future of Work and Human-Machine Interaction’ working group of Plattform Lernende Systeme.

The integration of robotics with Artificial Intelligence (AI) methods takes robotics to a new level. In close cooperation with humans and controlled by voice, gestures or interactive learning, robots can adapt flexibly to different tasks, people and environments. This opens up new fields of application, even in complex environments - for example in care, medical technology or the trades. This is associated with far-reaching economic and social potential. In a new white paper, Plattform Lernende Systeme uses use cases to illustrate specific application scenarios for robots with learning capabilities, describes technological developments and identifies design options for practical use.

The justice system in Germany is overloaded: Between 2021 and 2023, the number of open criminal proceedings increased by almost 30 per cent, according to the German Association of Judges. However, the number of judges and public prosecutors in Germany will decrease significantly in the coming years due to retirement. AI systems promise a wide range of potential applications and greater efficiency for the legal system. In this interview, Frauke Rostalski explains how AI systems can relieve the burden on courts and contribute to fair judgements. She is Professor of Criminal Law, Criminal Procedure Law, Philosophy of Law and Comparative Law at the University of Cologne, member of the German Ethics Council and member of Plattform Lernende Systeme.

Artificial Intelligence (AI) is changing the way we communicate, inform ourselves and make political decisions. This has consequences for a democratic society. The new webspecial www.ki-und-demokratie.de of Plattform Lernende Systeme explains the challenges, but also the opportunities, that AI presents for opinion-forming and political elections. Using numerous examples, video clips and an interactive quiz, it clearly shows where the use of AI affects democratic principles, how AI-generated or falsified media content - so-called deepfakes - are used and how they can be recognised as such. The webspecial is intended as a contribution to promoting media literacy.

When it comes to Artificial Intelligence (AI) in medicine and care, most people think of surgical robots or assistance systems in radiology. Less in the limelight are AI applications that support healthcare professionals with time-consuming administrative tasks - be it documentation, duty rostering or billing. Such software solutions offer great potential and, unlike AI systems for the clinical sector, quickly save time and money. In this interview, Andrea Schmidt-Rumposch explains how AI can make medical and nursing processes more efficient and what hurdles healthcare facilities face when introducing AI systems. She is Director of Nursing at Essen University Hospital and a member of the Health Care, Medical Technology and Care working group of Plattform Lernende Systeme.

Using Artificial Intelligence (AI) locally on smartphones, in vehicles or industrial robots offers enormous opportunities for the German economy and society. Compared to large AI models that are operated centrally on large computing infrastructures, edge AI requires significantly less energy, protects the privacy and data of users and enables reliable applications in real time. Plattform Lernende Systeme recognises that Germany is in a good starting position in international competition to exploit the potential of the technology. However, research and development face technical challenges and hurdles when it comes to transferring the technology into practice. A current white paper provides an overview of the strengths and weaknesses of Edge AI and discusses options for putting the technology into practice.

Artificial Intelligence (AI) can improve organisational workflows in hospitals and medical practices and thus relieve the burden on healthcare professionals. Unlike AI applications for the clinical area, AI solutions for billing, personnel planning or documentation can be used at short notice and immediately save time and costs. A current white paper from Plattform Lernende Systeme uses practical examples to show how AI can contribute to better quality of care in organisational processes. In order for the applications to be used quickly in day-to-day care, they must be tailored to the needs of healthcare professionals and embedded in existing processes.

Skilled workforce shortages threaten competitiveness and prosperity in Germany. Artificial Intelligence (AI) can make a contribution to securing skilled workforce. For example, the technology can be used to reduce the workload of employees and support the integration of people with disabilities and migrant backgrounds into the labour market. A current white paper from Plattform Lernende Systeme uses practical examples to show the potential and challenges of using AI in business and administration. The experts identify the necessary framework conditions for securing AI-supported skilled workforce, such as promoting AI skills at school or investing in data and computing infrastructures.

Robots that learn independently and work closely with humans - the combination of robotics with Artificial Intelligence (AI) methods has great potential for society and the economy. Robots capable of learning can relieve the burden on employees, alleviate the shortage of skilled workers and support people with disabilities. However, there is still a long way to go before AI-controlled helpers become part of our everyday lives. In its new web special, Plattform Lernende Systeme provides an overview of adaptive robotics: a dashboard shows areas of application and developments, while experts from the platform shed light on opportunities and hurdles from various perspectives.

Artificial Intelligence (AI) can accelerate the development of medicines and promote personalised medicine across the board. In this way, better and individualised medicines can be brought to market more cost-effectively. However, before the population can benefit from more favourable drug prices and innovative medicines, sufficient high-quality data from patients must be made available for research in addition to data on active ingredients, and a legally secure regulatory framework must be created. A current white paper from Plattform Lernende Systeme uses practical examples to show the potential of AI in drug development and addresses design options for overcoming the existing hurdles.

Large AI models that generate texts or images based on huge amounts of data and machine learning continue to cause a stir. However, data-based AI approaches also reveal limitations, for example due to their resource-intensive training or the lack of transparency of the AI system. Hybrid AI offers a promising alternative for sensitive areas of application such as medicine: it combines data-driven AI approaches with human knowledge and promises energy-efficient, robust and explainable AI systems. Plattform Lernende Systeme explains what hybrid AI is and the potential and challenges associated with it in a short publication.

Around 7.9 million people with impairments lived in Germany in 2020; about one third of them of working age. Their integration into the world of work is not only ethically and legally necessary, but also economically essential in view of the shortage of skilled workers. Artificial intelligence (AI) can help people with impairments to cope with their tasks in everyday working life. Angelika Bullinger-Hoffmann explains in an interview how participation can be improved with the help of AI technology - and which hurdles have to be overcome along the way. She is Professor of Work Science and Innovation Management at Chemnitz University of Technology and a member of the Future of Work and Human-Machine Interaction working group of Plattform Lernende Systeme.

Many SMEs are still reluctant to use Artificial Intelligence (AI). A first starting point is the analysis of their own value chain: Where and how can AI support them as a powerful computing tool? Professor Dr. Alexander Löser explains in an interview how SMEs can benefit from AI in concrete terms, what process steps are involved and why the introduction of AI requires a willingness to fail. He is the founder and spokesman of the Data Science Research Center at the Beuth University of Applied Sciences Berlin and a member of the "Technological Enablers and Data Science" working group of Plattform Lernende Systeme.

Artificial Intelligence (AI) will shape all areas of our lives in the future. With the current technological leaps in large-scale language models and robotics, many questions also arise: What do we want to use AI for? How can responsible use of AI be promoted? And how can Germany and Europe catch up in the international competition for AI? Plattform Lernende Systeme discussed these questions with more than 200 guests at its conference "Pioneering: Fit for the Future with Artificial Intelligence" on June 14 in Berlin.

Artificial Intelligence (AI) is a key technology for a sustainable economy and society. At the same time, AI systems also harbor risks. In the current debate about ChatGPT and other generative AI models, there are calls for regulation of the technology. An overview of possible forms and current regulatory initiatives - from the European AI Act to industry standards - is provided by a new web service of Plattform Lernende Systeme.

Artificial Intelligence (AI) can relieve healthcare workers and improve patient care. Medical and nursing professionals are generally open to the use of the technology, but demand technical and organizational changes in everyday inpatient and outpatient work so that patients and specialist staff can benefit from AI systems. This is the result of a qualitative survey of healthcare professionals conducted by Plattform Lernende Systeme which was presented today at the DMEA healthcare trade fair in Berlin.

The ChatGPT language model has brought Artificial Intelligence (AI) into the public eye. The text bot is part of a new generation of AI systems that compose texts, generate images and videos, or program codes. Whether in companies, medicine or the media world - the possible applications of so-called large language models are manifold. In the new web format "Perspectives on AI," experts from Plattform Lernende Systeme discuss the technological progress they promise, their potential for business and society, and the ethical and legal challenges associated with their use.

Artificial Intelligence (AI) can support balanced, trustworthy journalism in the digital age. Self-learning AI systems relieve journalists of the burden of researching, disseminating, and creating media content, thus creating free space for high-quality journalistic activities. At the same time, the use of AI poses challenges for the working reality of media professionals and the open formation of opinion in democracy. In a recent white paper, experts from Plattform Lernende Systeme show how AI tools can be used responsibly in journalism and what framework conditions need to be created for this.