Call 2 - Explainable and Robust AI

Call 2- Explainable and Robust AI (AI Data and Robotics Partnership) (RIA) HORIZON-CL4-2024-HUMAN-03-02

Expected Outcome:

Projects are expected to contribute to one of the following outcomes:

• Enhanced robustness, performance and reliability of AI systems, including generative AI models, with awareness of the limits of operational robustness of the system.

• Improved explainability and accountability, transparency and autonomy of AI systems, including generative AI models, along with an awareness of the working conditions of the system.

Scope 

Trustworthy AI solutions, need to be robust, safe and reliable when operating in real-world conditions, and need to be able to provide adequate, meaningful and complete explanations when relevant, or insights into causality, account for concerns about fairness, be robust when dealing with such issues in real world conditions, while aligned with rights and obligations around the use of AI systems in Europe. Advances across these areas can help create human-centric AI[1], which reflects the needs and values of European citizens and contribute to an effective governance of AI technologies.

The need for transparent and robust AI systems has become more pressing with the rapid growth and commercialisation of generative AI systems based on foundation models. Despite their impressive capabilities, trustworthiness remains an unresolved, fundamental scientific challenge. Due to the intricate nature of generative AI systems, understanding or explaining the rationale behind their outputs is normally not possible with current explainable AI methods. Moreover, these models occasionally tend to 'hallucinate', generating non-factual or inaccurate information, further compromising their reliability.

Read more on the scope of projects:

Multidisciplinary research activities should address all of the following:

Proposals should involve appropriate expertise in all the relevant sector specific use cases and disciplines, and where appropriate Social Sciences and Humanities (SSH), including gender and intersectional knowledge to address concerns around gender, racial or other biases, etc.

Proposals are expected to dedicate tasks and resources to collaborate with and provide input to the open innovation challenge under HORIZON-CL4-2023-HUMAN-01-04 addressing explainability and robustness. 

Research teams involved in the proposals are expected to participate in the respective Innovation Challenges.

Contribute to making AI and robotics solutions meet the requirements of Trustworthy AI, based on the respect of the ethical principles, the fundamental rights including critical aspects such as robustness, safety, reliability, in line with the European Approach to AI. Ethics principles needs to be adopted from early stages of development and design.

All proposals are expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring), and share communicable results with the European R&D community, through the AI-on-demand platform or Digital Industrial Platform for Robotics, public community resources, to maximise re-use of results, either by developers, or for uptake, and optimise efficiency of funding; enhancing the European AI, Data and Robotics ecosystem and possible sector-specific forums through the sharing of results and best practice.

In order to achieve the expected outcomes, international cooperation is encouraged, in particular with Canada and India.

For more details on the full scope of the project visit the Horizon Europe website: