Cross-cutting issues

The use of artificial intelligence raises many questions in areas such as interoperability, data quality, data protection, datability and data contract law. Identifying and addressing these cross-project challenges is a key task of the accompanying scientific research. In this context, it is possible to build in part on existing findings from the scientific monitoring of predecessor programme such as PAiCE or Smart Services World - but AI deployment also raises many new questions.

This includes, for example, the handling of small data volumes (small data), concepts for trustworthy data sharing between companies, or the handling of AI methods whose results are not self-explanatory. The latter directly touches on issues of acceptance and trust in AI-based solutions and decisions. The explainability and transparency of AI methods is therefore an important cross-cutting issue to be addressed in the accompanying research. In this context, an important topic area is also the question of certification of AI algorithms, which is a new challenge in self-learning systems.

The accompanying research will set up specialist groups to work jointly on these topics, which will also be supplemented by external experts from companies, associations, scientific institutions and from social partners.