“Developing, piloting and integrating systems, compliance tools and data economy enablers that process the increasing data volumes more efficiently, distill more useful knowledge from data, and contribute to the measurement, labeling, certification and reduction of the environmental footprint of massive data operations (e.g. by minimizing data transfers/traffic, improving energy reuse and/or reducing energy consumption of AI training/machine learning, privacy preservation and other processes). The aim is to provide Common European data spaces and AI data provision with reliable mechanisms to monitor, control and track/record transactions on data, to ensure compliance.
-Associate appropriate technologies and methods such as federated and distributed AI/analytics, with trustworthy AI techniques
-Protect privacy and confidentiality of AI training data as well as energy footprint reduction for these activities
-Enable companies and public sector to easily comply with existing and emerging regulations and create value on data assets that they possess or that they acquire from the market
-Improve citizen confidence in data-driven systems that treat them in a fair, unbiased and compliant way that respects their privacy and other rights
-Define, quantify and measure bias in data sets
-Shorten the time-to-market and reduce development costs of compliant data solutions
-Contribute to open, trusted, and federated Common European data spaces”