In a study for the Commission of Experts for Research and Innovation (EFI), Fraunhofer ISI examined the state of German and European AI research in an international comparison and analyzed AI strategies in selected countries to obtain insights for improving Germany’s AI strategy. The study was based on a strengths and weaknesses analysis of German AI research and application, as well as an investigation of how well German AI activities are embedded in EU policy
The following references to beneficial research, innovation, and industrial policy measures were identified: establishment and expansion of specific AI innovation ecosystems, development of country-specific AI models, AI pilot and lead markets in the public sector, closer integration of research and implementation, and pooling of European and national resources.
The PublicAI project worked with the Mozilla Foundation to examine whether and how public AI infrastructures represent an alternative form of governance that could better promote research, innovation, and learning with AI. The monopolization of large social platforms raises the question arises of which alternatives are at least conceivable for AI, since the privatization of digital infrastructures results in less transparency, mutual learning, and market entry.
In addition to extensive literature research, the project relied on an exploratory qualitative research process based on semi-structured interviews with a large number of different relevant actors in Europe and the US. Discussions focused on the extent to which forms of public AI already exist, what can be learned from them, and what further public AI infrastructures could potentially look like.
In this project for the economic development agency of the city of Aachen, a location analysis of the artificial intelligence ecosystem in the Aachen region was carried out. The city of Aachen is pursuing the overarching goal of creating structurally effective framework conditions for local companies operating in the field of AI.
To support a targeted funding strategy, the AI players in the Aachen region and the AI ecosystem in which they operate were analyzed quantitatively and qualitatively. Based on these analyses, recommendations for action to strengthen Aachen as an AI location were derived.
The EU regulations on data law introduced in recent years have given rise to a complex and multi-layered institutional governance architecture. In an overview of the relevant offices and authorities and their roles, researchers at Fraunhofer ISI highlight the interrelationships and classify developments with regard to the concept of agencification. This buzzword refers to the transfer of regulatory powers to national and European authorities, some of which are independent, so that they can act with a certain degree of autonomy – without ministries being able to issue instructions to them.
The expertise developed in the relevant authorities can lead to more efficient law enforcement on the one hand, and on the other hand, authorities can respond more flexibly to situations. This is exemplified by the implementation of the EU's AI Act. The corresponding supervisory structure is divided on the one hand into a Union level (Commission, AI Office, AI Committee, and Advisory Forum) and a Member State level (competent notifying authorities, market surveillance authorities). On the other hand, the Union level is subdivided into the AI Office, which is directly attached to the EU Commission, the AI Board, which is dominated by the member states, the independent Advisory Forum, and the Scientific Committee.
As part of its data strategy, the EU has created a far-reaching legal basis for digital value creation through data in Europe – including in the energy industry. While the Data Act greatly expands data availability in the energy system, the Data Governance Act regulates trustworthy transaction options for this data.
Under the regulations that will apply in the future, operators of wind turbines, for example, will be entitled to all data generated during the use of the turbines. This includes, for example, extensive sensor data that is essential for operational monitoring and predictive maintenance. Until now, the turbine manufacturer has had exclusive access to this data as the data owner and has also sold the rights of use to the operators.
Together with the Fraunhofer Cluster of Excellence for Integrated Energy Systems (CINES), a white paper was developed that analyzes the effects and potential of the European data strategy, provides an understanding of the new regulations, and outlines specific options for action for players in the energy industry.
Fraunhofer Institute for Systems and Innovation Research ISI