Discover three new EU funded projects on Explainable and Robust AI (AI Data and Robotics Partnership)

Last month, HaDEA signed three new grant agreements to support robust, safe and reliable AI solutions to help create human-centric AI. The new projects ROBUSTIFAI, AIXPERT, and TRUMAN are funded under the Horizon Europe Cluster 4: Digital, Industry and Space, with a total contribution of €21.4 million available from the EU budget.

The projects aim to enhance AI systems’ robustness, reliability, transparency and explainability, addressing ethical principles and operational limits. The research focuses on advancing AI algorithms for safe, trustworthy use in real-world conditions, incorporating multidisciplinary approaches, accountability and fairness, aligning with European standards and promoting innovation and sharing within the AI community.

All three projects will actively contribute to ongoing EU initiatives on AI, such as the AI-BOOST project on AI challenges and the AI-on-demand platform.

Discover the projects

ROBUSTIFAI 

Robustifying generative AI through human-centric integration of neural and symbolic methods

Generative AI (GenAI), such as foundation models, is a powerful and groundbreaking type of AI that can learn from data and create new content.  However, GenAI has significant limitations that can lead to misuse or hinder its widespread use and positive impact on society and economy. These limitations stem from its lack of robustness in three key areas: technical, operational, and user robustness.

ROBUSTIFAI aims to radically change the way GenAI systems are developed by creating and promoting a rigorous method for designing and deploying robust GenAI systems. The methodology is based on the following three innovative approaches: techniques to understand and incorporate human needs into the neural model, systematic methods for combining neural models and symbolic techniques, and enabling GenAI systems to adapt to changes in their environment and user variations. 

The methodology will be tested and supported by three real-world industrial use cases from three different application domains: the automotive industry, service robots, and cybersecurity.

AIXPERT         

An agentic, multi-layer, GenAI-powered backbone to make an AI system explainable, accountable, and transparent

The AIXPERT project puts forward a new approach to developing AI systems that are explainable, accountable, and transparent AI systems. The project is centred on an adaptable, situation-aware AI-agentic platform capable of encapsulating various AI models, regardless of their underlying architecture. This approach significantly enhances the trustworthiness of AI systems by providing a consistent framework for explainability and accountability across different model types. The project tackles challenges in making AI systems explainable, transparent, accountable, autonomous, and robust by integrating multi-agent systems with foundation models that use multiple forms of data and real-time human feedback. This combination enhances AI system trustworthiness and user-friendliness while allowing for flexibility in the choice of underlying AI models. 

The project’s results will be applied in five specific areas: healthcare, recruitment, manufacturing, education, and the creative industries.

TRUMAN

Trustworthy human-centric artificial intelligence

The TRUMAN project aims to develop generic technologies and methods to improve the resilience of AI systems against security, privacy, and fairness threats, and to increase user trust in these systems. This will be done by considering all stages of the AI life cycle, from data collection to training and deployment.

TRUMAN will develop customized solutions to protect against existing and new types of attacks, including those that target privacy, fairness, and system security.  

Additionally, TRUMAN will examine the impact of these solutions on people and develop ways to explain the underlying technologies and risks to them, as well as involve them in improving these models. The project will also work to establish comprehensive guidelines and recommendations for building trustworthy and robust AI systems.

The project’s technologies will be tested on four real-world scenarios from different sectors: marketing, IT security, finance, and healthcare, to evaluate their effectiveness.

Background

You can find out more about policy priorities, challenges and opportunities and the role  of research and innovation in addressing them, in the Horizon Europe Strategic Plan .

Interested in funding? Check out Horizon Europe Work Programme 2025 and the HaDEA Call for proposals page to discover new opportunities!