Along the whole value chain in using data for economic purposes, guidelines and tools are required to make the business of the different stakeholders successful, and the end-users confident that none of their rights are endangered. CERTAIN addresses these needs and offers solutions for data holders, dataspaces and AI systems providers, and AI systems deployers.
To make sure that AI-based products are of high quality and reliability, CERTAIN develops security tools and methods, specifically suitable for dataspaces and AI systems. The project delivers guidelines and technical tools to help with compliance, assess data quality, measure biases in datasets, and protect privacy. CERTAIN sets the foundation of AI certification: it translates the regulations to business terms, builds a directory of certification entities per business, develops a platform to streamline the certification process, and develops tools for AI system providers and certification entities so that they can respectively prepare and run a certification process.  
Furthermore, CERTAIN addresses the environmental footprint of the AI value chain. Innovative techniques are elaborated to reduce energy consumption when building and running AI systems, which is beneficial  for the European Green Deal and reduces costs for AI stakeholders. 

Vision

CERTAIN aims to create a cohesive and compliant ecosystem for AI stakeholders, fostering trust, transparency, and innovation in the European data economy. Through collaboration and standardisation, the project aims to empower organisations to navigate complex regulatory landscapes, embrace cutting-edge technologies, and drive sustainable growth in the data market and AI sector. Ultimately, the project seeks to establish a framework that promotes responsible AI development, enhances data governance practices, and maximises the societal benefits of AI innovation for a diverse set of actors.

Objectives

  • Enable traceability of critical information of AI systems
  • Produce guidelines for legally and ethically compliant AI system assessment regarding EU regulations
  • Design tools for dataspace providers and data holders to help them to be compliant with EU regulations related to AI and minimise energy consumption
  • Develop methods to improve and assess the compliance of AI systems with EU regulations related to AI
  • Design certification procedures for AI systems
  • Empirical evidence of the applicability and adequacy of the proposed framework across multiple sectors
  • To enable the development of an open, dynamic, multi-disciplinary and sustainable community around the EU AI ecosystems and liaised initiatives and actions, towards an EU regulation compliance frameworks

The CERTAIN overall methodology