As AI-based decision support systems spread across public and private sectors in a context of growing inequalities and intersectional discrimination, AI fairness and Trustworthy AI have become central EU priorities because, despite fairness being a core EU principle, there was a major gap in concrete technical, socio-legal and organisational methods to ensure, test and repair non-discriminatory, rights-respecting AI systems
AEQUITAS has addressed this gap by developing a comprehensive, controlled experimentation and governance environment for fair and trustworthy AI, delivering a Fair-by-Design methodology and blocks (covering fairness, fundamental rights and compliance across the AI lifecycle), the Information Flow Model (IFM) for socio-technical analysis, an integrated Experimenter to design and document fairness-focused tests, a synthetic data methodology and engine, diagnostic tools with new bias metrics, mitigation methods, and new benchmark datasets for realistic high-risk domains. These components have been validated in real-world use cases in healthcare, HR, education and services for vulnerable groups, and are now accessible both via the AI-on-Demand platform and as an on-premises prototype, enabling organisations to assess and improve AI fairness directly on their own sensitive data in line with privacy, security and regulatory requirements.
Beyond the project, AEQUITAS has been taken up in EU-level guidance for regulatory sandboxes for Member States, where its methodologies are used as building blocks for fairness- and rights-oriented sandbox design, and it is being integrated into the Italian “AI Factory” initiative as a reference framework for experimentation and pre-commercial validation of trustworthy AI solutions.
Finally, AEQUITAS has produced a substantial body of educational material and actionable knowledge tailored to different stakeholder communities: guidance and tools for civil society and vulnerable groups to understand and contest AI decisions; practical handbooks and frameworks for policymakers and regulators; methodologies, metrics and software for data scientists and developers; and governance models, templates and training pathways for the corporate and industrial sectors. Through this combination of methods, software, benchmarks, policy integration and capacity-building, AEQUITAS has established a reference framework for fair and trustworthy AI, contributing to scientific progress, regulatory readiness and practical impact in high-risk AI domains.
