Germany AI Strategy Report

In November 2018, the German Federal Government launched its National AI strategy jointly developed by the Federal Ministry of Education and Research, the Federal Ministry for Economic Affairs and Energy, and the Federal Ministry of Labour and Social Affairs (Germany, 2018).

The strategy presents the progress made in terms of AI in Germany, the goals to achieve in the future and a concrete plan of policy actions to realise them. The range of policy initiatives outlined in the strategy aim to achieve the following goals:

• Increasing and consolidating Germany’s future competitiveness by making Germany and Europe a leading centre in AI;
• Guaranteeing a responsible development and deployment of AI which serves the good of society;
• Integrating AI in society in ethical, legal, cultural and institutional terms in the context of a broad societal dialogue and active political measures.

The German Federal Government published an interim report presenting the main measures that have been implemented of the German AI Strategy after one year in November 2019. It provides facts and figures on the implementation of the strategy, fields of actions and perspectives for the coming years.

In October^, 2019, the Federal Governments Data Ethics Commission presented its ethical guidelines and specific recommendations on AI, algorithm-based decision making and the use of data.

In October 2020, the Study Commission on Artificial Intelligence - Social Responsibility and Economic, Social and Ecological Potential of the 19th German Bundestag presented its final report with specific recommendations for action, on which the German Bundestag concluded its deliberations on 5 November.

In December 2020, the German Federal Government has adopted an Updated AI strategy (Germany, 2020). The review draws up an interim balance, shows relevant developments at national, European and international level, and sets out concrete measures to be implemented by 2022. The update report focuses on the following fields of action: research, knowledge and expertise, transfer and application, regulatory framework and society. In addition, new initiatives will inter alia focus on sustainability, environment/climate protection, pandemic control and international/European cooperation.

With the Economic stimulus and future package, the German Federal Government committed to increase the planned expenditure of EUR 3 billion for the promotion of AI by an additional EUR 2 billion, resulting in a total of EUR 5 billion by 2025.

The summary below aims to provide the most recent and updated picture of ongoing AI policies in Germany.

Germany AI Policies on OECD.AI dashboard

The German strategy proposes several policy reforms and initiatives for formal training and education, with special focus to the formation of educators, trainers and the general public in order to guarantee a high-quality level of education in AI:

• Expanding learning platforms such as the AI Campus to develop a solid skill base in AI through courses, videos, podcasts and knowledge exchange;
• Creation of at least 100 additional professorships in the field of AI to ensure that AI has a strong foothold within the higher education system. AI professorships are for instance planned at the centres of excellence for AI and in the scope of the Tenure Track Programme and the Excellence Strategy;
• Getting students more involved in STEM subjects as outlined in the STEM Action Plan.

On top of formal education and training reforms, the German Federal Government proposes a broad-based set of instruments to expand and upgrade AI-related skills of the workforce. As the required skills of individuals will change significantly with the upcoming AI technologies, the German Federal Government launches some large-scale qualifications initiatives with attention for lifelong learning and for reskilling and upskilling employees across their entire careers:

• The creation of the National skills strategy to promote advanced vocational training in digital and AI-related aspects among others. The Mittelstand 4.0 centres of excellence for SMEs has successfully deployed and expanded AI trainer programmes to support skills development for businesses;
• The creation of further education and training programmes in AI and data science methods for researchers such as the Helmholtz Information & Data Science Academy;
• The launch of INVITE (Digital Platform for Continuing Vocational Training) innovation competition projects for the design of an innovative, user-oriented and coherent digital continuing education and training area;
• The formation of regional Centres of Excellence for Labour Research studying and organising labour in an AI working environment and imparting the necessary skills to management and the workforce;
• The expansion of AI education programmes such as the online course on Elements of AI (with a governmental patronage).

Other policy instruments aim to identify upcoming skills demand and to respond in a flexible way to the digital and demographic changes of labour demand on the job market. Hence, these initiatives aim at satisfying and bridging the needs of both the workforce and companies:

• The creation of a Skilled labour strategy: a skills monitoring system to identify which skills are needed in the future;
• The formation of regional Hubs of tomorrow to address companies and employees with tailored information and innovative learning approaches in order to shape change.

The German Federal Government also pays attention to the possibilities and impact of AI in the cultural and media sector. These include the funding and expanding of AI projects for the preservation, development, accessibility, networking and communication of cultural programmes as well as the development of AI skills in categorising and verifying media content to ensure diversity of opinion.

Funding schemes and support initiatives to foster research in the field of AI comprise among others:

• Creation of Competence Centres for AI Research: The German Federal Government has established multiple national competence centres for AI research to strengthen excellence and competitiveness and to become a leading centre for AI research. To support their expansion and their development into a national research network on AI the ministry has doubled the funding of the competence centres until 2022. As mentioned in the Updated AI strategy (p. 12), “the plan is to dovetail the existing centres at the universities in Berlin, Dresden/Leipzig, Dortmund/St. Augustin, Munich and Tübingen and the German Research Centre for Artificial Intelligence with other application hubs to be established to form a network of at least twelve centres and hubs”;
• The launch of a Reality Lab for Artificial Intelligence in Civil Protection: operated by the German Federal Agency for Technical Relief (THW). This living lab it is meant to offer an interface between the Security Research Community, AI researchers and industry. It will also link AI research and developments with practitioner needs. The lab aims at testing and developing solutions that make AI based technologies accessible and useable for practitioners. Another core task is the development of data collection concepts, for which specific tools and equipment will be created to enable future AI applications. The THW living lab is funded through special funding of the German Federal Government from 2019 to 2022;
• Gruender platform: online platform to support start-ups – including AI ones – from initial research to concrete AI applications;
• Industrial Collective Research programme fostering joint business and science research on collective AI projects in order to close the gap between basic research and industrial applications;
• Advisory and funding services to foster the growth of AI start-ups (e.g. EXIST programme focusing on university spinoffs) through for instance venture debt (e.g. Tech Growth Fund). This can also include policies to promote company formations in the field of top-rate research in human-machine interaction.

Support initiatives towards innovation and testing include:

• Founding an Agency for Breakthrough Innovations with AI as a focus;
• Developing in-company innovation spaces to promote innovative solutions for digitalisation;
• Strengthening the Central Innovation Programme for SMEs (ZIM): funding programme for SMEs targeting individual and collective R&D projects;
• Speeding up the process of AI innovations by launching so-called transfer initiatives, digital test beds and regulatory sandboxes, and promoting pilot and flagship AI projects, for example those that benefit the environment and the climate.

The German Federal Government also has research and innovation support programmes in targeted areas with dedicated AI policies in specific sectors and geographical areas. The updated AI strategy in 2020 highlights following priority areas: healthcare, environment and climate, aerospace, and mobility. Examples of policy initiatives are mentioned below and in Section 5.11.6:

• Digital innovations for the improvement of patient-centred care in the health care system: Within the funding programme "Digital innovations for the improvement of patient-centred care in the health care system", the German Federal Government has so far funded 22 projects for up to 36 months over the period 2020-2023 with a total funding amount of approximately EUR 50 million. The projects will investigate the benefits of smart sensors, smart data use, smart decision support systems and smart communication in clinically relevant application scenarios. The projects should contribute to demonstrating the potential benefits of AI methods in combination with the use and evaluation of large amounts of data for patient care;
• Research on AI technologies in agriculture, health nutrition, food chain and rural areas: The German Federal Government initiated a government funding of AI technologies in agriculture, health nutrition, food chain and rural areas with a public announcement in February 2020. A total of 82 plans were submitted with overall 305 subprojects and a total funding about EUR 92 million;
• Real-World Test Field for Digital Mobility: The German Federal Government is funding this large-scale research project that combines elements of classical traffic planning with mobility and innovation management, also using AI. A total of 10 sub-projects on digital mobility are being implemented in parallel and scientifically monitored in order to deduce how digitalisation can effectively contribute to achieving the climate goals in the mobility sector;
• Data Space Mobility Germany: under the direction of the German Academy of Science and Engineering (acatech), a stakeholder dialogue is currently taking place to jointly create a comprehensive Data Space Mobility Germany by the end of 2021. Among other things, the aim is to make available mobility data (real and synthetic training and test data) that can be used across competitors for the research, development, validation and certification of reliable AI algorithms in order to promote the development of autonomous driving in Germany.

The German strategy highlights a wide range of policy initiatives to foster networks and collaborations across the business community, academia and public research centres. The aim of networking is to encourage the development of multidisciplinary cutting-edge research and innovation projects and to fully exploit synergies and diversities across institutional players by promoting knowledge dissemination and transfers.

Support initiatives of the German Federal Government to encourage collaborations include:

• The formation of a Franco-German R&D network (“virtual centre”): bilateral funding and training programme with bilateral AI clusters in specific industries (e.g. healthcare, environment, robotics, mobility);
• Expanding the Plattform Lernende Systeme into an AI platform to host dialogue and networking between science, business community, civil society and the government. To foster networking and increase the international visibility of German’s AI research, the German Federal Government launched the map on AI. This map allows to discover innovative applications and projects on AI and to identify and learn more about all research institutions active in AI (including the AI competence centres and Digital Innovation Hubs);
• Platform Industrie4.0: a platform with a holistic approach to the shaping of digital ecosystems. It aims at supporting and promoting innovations and collaborations in a digital economy, with recently a more targeted focus on AI technologies;
• The development of Next Generation Clusters: The aim of the initiative is to transfer fundamental, developable results from cutting-edge research into products and services, with a strong emphasis on collaborative partnerships;
• Further development of the Digital Hub initiative and the Hubs for Tomorrow initiative in Germany, in particular those related to AI, cybersecurity and other AI-related fields;
• Establishment of the “Civic Coding - Innovation Network AI for the Common Good”: The German Federal Government is developing an innovation ecosystem that aims at fostering "AI for the greater good". It aims at providing know-how, financial assistance to AI projects, a matching platform that brings together start-ups, NGOs, scientists and governmental agencies, as well as a collaborative data exchange infrastructure for non-profits and civil society actors. The German Federal Government will combine different specific expertise, synchronize funding strategies and provide support with a targeted infrastructure. It will establish Civic Tech Labs for Green, which will focus on developing sustainable and broadly accessible IT infrastructure and tools. Moreover the German Federal Government will facilitate data exchange among civil society actors by means of a newly established Civic Data Lab. A Civic Innovation Platform, which serves to provide a marketplace for ideas on the use of AI-technology for the common good and facilitates access to funding opportunities. The joint project is currently underway with a variety of pilot projects and the establishment of project infrastructure. The innovation network was officially launched in May 2021 and start operations at the end of 2021.

Another field of action is international cooperation on AI:

• The German Federal Government is working to ensure that the further development and use of AI is aligned with the Sustainable Development Goals (SDGs). International networking and collaboration with developing and emerging countries plays an important role to enable everyone to participate in the use of AI technologies and to develop AI applications for sustainable economic, ecological and social development. The German Federal Government is strengthening AI capacity building and better access to open AI training data in the Global South to support inclusive and fair AI innovation. In addition to this, its initiative FAIR Forward is supporting the development of suitable political and regulatory frameworks for AI, such as the framework by the governmental alliance “Smart Africa”, which is developing regulatory recommendations on AI for 30 African member countries;
• The German Federal Government supports the establishment of international and multilateral structures for networking and cooperation in the area of AI: Germany is one of the founding members of the Global Partnership on AI (GPAI), an international initiative to spur a responsible development and use of AI in full respect of human rights, inclusion, diversity, innovation and economic growth. The GPAI brings together experts from industry, civil society, governments and the academic world. This initiative is stirred by a secretariat, hosted by the OECD in Paris, and it accounts for two Centres of Expertise in Montreal and in Paris;
• Germany also contributes to the ongoing work of the OECD on AI. AI is a priority area of the OECD’s work in the field of the digital transformation. In May 2019 the OECD adopted its Principles on AI, the first international standards on AI agreed by governments. The OECD.AI Policy Observatory, launched in February 2020, aims to help policymakers implement the AI Principles and is supported by a Network of Experts on AI (ONE AI). The German Federal Government supports the OECD programme Artificial Intelligence in Work, Innovation, Productivity and Skills (AI-WIPS), whose results and findings will make a major contribution to shaping the global AI debate.

Concerning efforts to foster the international attractiveness of the country, the German Federal Government aims to improve working conditions and remuneration to draw in and retain and attract the brightest minds. Along this side, the German strategy also proposes reforms of legislation to facilitate immigration procedures for skilled workers. Notable policy initiatives to attract AI experts and researchers, include:

• Alexander von Humboldt Professorship: With a value of EUR 5 million, the Alexander von Humboldt Professorship is the most highly-endowed research award in Germany and draws top international researchers to German universities. From 2020 to 2024, additional Humboldt Professorships can be awarded in the field of AI;
• Support to young female AI researchers: In order to increase the participation of women in German research on AI, women will be promoted in leading interdisciplinary research groups, with a particular focus on reconciling work and family life. The selection process will be competitive.

Other initiatives aim to monitor current progress and uptake of AI and to disseminate nation-wide information about digitalisation and AI:

• Strengthening the Observatory for Artificial Intelligence in Work and Society (AI Observatory) to monitor the uptake and impact of AI in society and the future of work. The Observatory was launched on 3 March 2020. Among others, the Observatory conducts impact analyses, scenario development and trend monitoring of the use of AI and provides guidelines and recommendations for enhancing skills, the development of AI and use of it on the shop floor, and social dialogue in the field of AI;
• Monitoring the AI landscape by compiling indicators on the use of AI in the economy and in higher education and teaching and in work and society;
• Establishing a Digital Work and Society Future Fund to set up an information and policy campaign in the field of digital technologies such as AI and to promote multidisciplinary social technology design.

As a body established by lawmakers, the Study Commission on Artificial Intelligence repeatedly examined regulatory issues relating to AI. In its final report, the Study Commission provides recommendations for actions. Among others, the Study Commission calls for sector-specific regulatory regimes for AI, while ensuring principles of proportionality and liability.

In line with these recommendations, the German Federal Government launched initiatives to tackle among others issues related to information management, data ownership, free flow of data, and standardisation. Reforms of the legislation target many domains, including codifying the rights of the labour force, consolidating competitiveness of the industry and developing rules with respect to data use and protection.

Following initiatives provide initial steps towards a legislative framework for AI:

• The launch of a Commission on Competition Law 4.0 serving as a political platform for a debate on how to further develop competition and copyright law. In 2019 the Commission presented its report on “A new competition framework for the digital economy”. The Competition and Digitalisation Act adopted by the Cabinet on 9 September 2020 addresses several of the Commission’s recommendations and implements them where this is essential to ensure functioning competition, for instance when it comes to improving access to data;
• The Federal Data Protection Act codifies data protection regulation and privacy (i.e. safeguard the control on personal data), compliant with EU law;
• Review and if necessary adaption of the legislation concerning the use of non-personal data as well as copyright; inter alia: the German Federal Government’s Data strategy and Open data strategy;
• Implementation of the cyber security directive: this directive properly known as the Directive on security of network and information systems (NIS) requires Member States to adopt a national cyber-security strategy. In Germany it has been implemented by the NIS Implementation Act in June 2017.

The German Federal Government advocates using an “ethics by design” approach throughout all the development stages and use of AI-based applications. It recommends engaging in dialogue with other leading regions to reach an agreement on joint guidelines and ethical standards on AI. Hence, the strategy foresees to work on a legal and ethical framework aligned with European guidelines and where appropriate taking into account recommendations of the national Data Ethics Commission. Several initiatives tried to define ethical guidelines for AI in Germany:

• Guidelines for developing and using AI systems: The Data Ethics Commission (DEC) presented their recommendations in October 2019 containing general principles to ensure the ethical design and use of data and algorithmic systems;
• Ethical requirements to ensure transparency, verifiability and predictability of AI systems (e.g. ethical guidelines for self-driving cars).

Besides ethical guidelines and legislative reforms, standards form an essential aspect of an adequate and effective regulatory framework. Standards ensure high quality products and services. They reinforce security and open up possibilities towards collaboration due to higher degrees of comparability and interoperability. Overall, standards for AI increase the public trust in the use and deployment of AI applications. With respect to standardisation, the German Federal Government proposes the following support initiatives:

• The German standardisation roadmap on AI describes the environment in which AI standardisation operates, identifies existing standards and specifications relevant to the field of AI, and outlines further standardisation needs. Even though it is a national publication, it focuses primarily on European and international standardisation efforts. In addition, it formulates concrete recommendations for action which are aimed primarily at industry, but also at stakeholders in quality infrastructure, research and policy. The Roadmap was developed by the national standards organisations DIN and DKE in cooperation with the German Federal Government as part of the German AI Strategy, along with more than 300 experts from industry, science, the public sector and civil society;
• Funding for the development of data standards and formats to encourage EU-wide collaborations;
• Funding for experts, particularly from SMEs and start-us in order to support their participation in international standardisation processes.

Infrastructure

Regarding infrastructure the German Federal Government foresees to expand the current data infrastructure in order to create optimal conditions for the development of cutting-edge AI applications. The objective of data infrastructure investments is to obtain a trustworthy data and analysis environment to strengthen research in AI and to favour exchanges due to a more flexible data interoperability. In addition, the German AI strategy aims to develop the current telecommunication and digital infrastructure to ensure a better connectivity of the network and to improve cyber security. Lastly, the German Federal Government is setting up funding to foster learning capabilities and experimentation in AI by improving the digital infrastructure in the education system.

In particular, the German strategy foresees the following initiatives for the improvement of the infrastructure in AI:

• Improving data sharing facilities by providing open access to governmental data and improving the infrastructure for access to the Earth observation data;
• Building a trustworthy data and analysis infrastructure based on cloud platforms and upgraded storage and computing capacity;
• Setting up a National Research Data infrastructure (NFDI) to provide science-driven data services to research communities;
• Improving security and performance of information and communication systems with particular focus on resilience of AI-systems in case of attacks;
• Providing funding from the Digital Pact for Schools programme to improve digital infrastructure in schools;
• Expanding the Learning Factories 4.0 initiative, which sets up professionally equipped laboratories and puts them at disposal of students for learning purposes in AI;
• Introducing PLAIN – Platform Analysis and Information System by the German Federal Government as a blue print for government big data and AI applications.

Cornerstone initiatives in German’s preparation for the next-generation data infrastructure are the GAIA-X project and the Federal Government Data Strategy. The objective of the GAIA-X project, initiated by Germany and France, is to create a secure, federated data system that meets the highest standards of digital sovereignty while promoting innovation. The Federal Government Data strategy identifies four concrete fields of actions: the improvement of data provision and access, the promotion of responsible data use, the increase of data competencies in society and the development of a data culture for data sharing and use.

Notable examples of support programmes of the German Federal Government to create data infrastructures to boost the development of AI applications, include:

• mCloud: an open data platform that provides free access to data from the mobility, spacial and weather forecasting sectors. The database is constantly updated by the German Federal Government with raw data and takes into account data from private providers from the mobility sector as well. It is primarily aimed at users from administration, research and the business sector;
• Mobility Data Marketplace (MDM): it offers suppliers and users of mobility data a neutral B2B platform to share, search and subscribe to traffic-relevant online data. The platform forwards the data supplied by the data suppliers unchanged to the data clients. With its defined standards for data exchange, MDM is nation’s biggest volume of information on traffic flows, traffic jams, road works, mobility options, parking facilities and more;
• Smart Data Innovation Lab (SDIL): it offers researchers unique access to a large variety of big data and in-memory technologies. Industry and science collaborate closely to find value in big data and generate smart data from it. Projects focus on the strategic research areas of Industry 4.0, energy, smart cities and personalised medicine;
• Research Data Centre (FDZ) at the Federal Institute for Drugs and Medical Devices: it offers researchers and health policy makers access to claims data of all statutory insured people in Germany. This representative and up-to-date database allows research on public health as well as health services research with AI applications.

In terms of ICT infrastructure and high-performance computing, the German Federal Government will work with the different Länder to accelerate the expansion of the Gauss Centre for Supercomputing (GCS) to Exascale capability in addition to developing the National Supercomputing Centre (NHR), especially taking into account future peak demand for AI applications and for analysing large data volumes. Particular attention will be paid to energy and resource efficiency as well as possibilities for industrial use. A connection to GAIA-X and the mobility data marketplace is planned here to create a new and trustworthy bridge to use by business

Climate and environment

The German Federal Government’s National AI strategy explicitly mean to bring benefits for people and the environment, and to fund AI applications to benefit the environment and the climate. To this end, the German Federal Government has developed various support programmes and action plans to foster the role of AI in tackling the climate change:

• Lighthouses of AI for Environment, Climate, Nature and Resources: to boost the high potential of AI to environmental sustainability, the German Federal Government published a funding programme (EUR 40 million) in August 2019. The programme funds solutions that use AI to help solve environmental challenges and promote opportunities to use AI strategically for Environmental and climate protection. It targets application-oriented research projects active in the following digital ecological areas, e.g. in the fields of energy efficiency, resource efficiency, protection of biodiversity, nature conservation, species protection, water management, sustainable consumption or eco-friendly mobility. The projects can be funded for a period of three years with a maximum funding amount of EUR 3 million;
• Remote sensing: the national AI strategy highlighted the need to provide high-performance infrastructure to improve the accessibility of earth observation data (p. 34). To respond to this need, the German Federal Government is funding the analysis and evaluation of remote sensing data with AI-powered methods. Remote sensing enables monitoring activities at distance in existing infrastructure, buildings, vegetation and crowds of people, including in areas that are difficult to access;
• Action plan for Digitalisation and AI in Mobility: To implement the national AI strategy, the German Federal Government has drawn up the action plan "Digitalisation and AI in mobility". It aims to make "Mobility 4.0" effective and sustainable by exploiting the great efficiency potential of digital innovations and AI in mobility for all modes of transport and for the entire mobility system with regards to the climate targets and the European Green Deal. In this context, the German Federal Government promotes, among others, AI innovations for new forms of mobility, for automated and connected driving as well as through the data-based funding programme mFUND. In order to actively support the development of AI-driven mobility, the German Federal Government also plans to establish AI centres for mobility in Germany, which will provide optimal networking for all participants, inspire and facilitate the application of AI in the mobility sector and the rapid transfer from research to practice, and thus strengthening competitiveness in this field.

COVID-19 pandemic

The German Federal Government is currently funding a wide range of initiatives to foster the role of AI in countering the COVID-19 pandemic and in creating a healthy environment for society:

• The HiGHmed Use Case Infection Control: The infection control use case of the HiGHmed consortium develops a software system to analyse various data sources from hospitals, with the aim to detect potentially dangerous germs as early as possible. This automated early warning system helps to protect patients from new infections, but also to understand their causes and how infectious diseases spread. The software system is adapted to detect the pandemic SARS-COV-2 virus. The German Federal Government is funding the HiGHmed consortium as part of the Medical Informatics Initiative with around EUR 41 million in the current development and networking phase 2018-2022;
• Chatbot/Voicebot at the German customs administration: The German customs administration is planning to deploy an AI module in the field of information provision, which is intended to answer questions from companies and private individuals in different ways. It is planned to use a chatbot on the internet presence of the customs administration as well as the implementation of a voicebot to automatically answer calls received by the hotline of the central information office. The primary goal is to answer those questions without the use of human assistance, which are recurring, clear and homogeneous in content. With the help of the implemented knowledge database, the AI module should be able to cover the entire spectrum of responsibilities of the German customs administration. If automated processing is not possible, the chatbot forwards the query in writing to an officer or the voicebot connects the questioner with a hotline employee. The project is an important contribution to the improvement of the digital infrastructure of German customs in general and can help to avoid unnecessary personal contacts at the customs offices, which can help to maintain the necessary social distance in the event of a continuing pandemic. The project was initiated in June 2020, the technical conception completed in December 2020 and the final system introduction is foreseen for June 2021. Afterwards a permanent use of the AI module is planned;
• Participating in the Global Partnership on Artificial Intelligence (GPAI): Within the framework of the GPAI a working group on AI and pandemic response (AIPR) has been formed to promote cross-sectoral and cross-border collaboration in this area. In November 2020, the working group released a report outlining its mandate and providing recommendations to foster and support the responsible development and use of AI-enabled solutions to address COVID-19 and future pandemics;
• Collaborative project on Imaging using AI: German hospitals are also participating in a collaborative project on Imaging COVID-19 AI. The objective of this project is to enhance computed tomography (CT) in the diagnosis of COVID-19 by using AI. The project group will create a deep learning model for automated detection and classification of COVID-19 on CT scans, and for assessing disease severity in patients by quantification of lung involvement;
• Participation in EU-funded projects including AI and health: Finally, Germany takes part in the EU-funded project EXSCALATE4COV that exploits the most powerful computing resources currently based in Europe to foster smart in-silico drug design while increasing the accuracy and predictability of Computer-Aided Drug Design. Specifically, the project involves three among the most powerful supercomputing centres in the EU: CINECA in Italy, the Barcelona Supercomputing Centre (BSC) in Spain and the Julich Supercomputing Centre (JSC) in Germany. The collaboration also includes pharmaceutical companies and major institutes of biology and bio-molecular dynamics from across Europe.

The German Federal Government is publishing regular updates of its national AI strategy that includes a stocktaking of the current policy actions and concrete steps for its implementation in the coming years.

Germany (2020). Artificial Intelligence Strategy of the German Federal Government – Update 2020. https://www.ki-strategie-deutschland.de/files/downloads/Fortschreibung_KI-Strategie_engl.pdf

Germany (2018). Artificial Intelligence Strategy. German Federal Government. https://www.ki-strategie-deutschland.de/home.html?file=files/downloads/Nationale_KI-Strategie_engl.pdf

Germany on OECD.AI observatory 

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