Large Scale pilots on trustworthy AI data and robotics addressing key societal challenges (AI Data and Robotics Partnership) (IA)

AI is key to maintain European sovereignty in major industrial sectors strategic for Europe. Human-centric approaches are key to acceptance and to ensure safety, security and protection of fundamental rights. To assure safety and human acceptance trust is mandatory. AI based solutions and tools can boost societal wellbeing and economic growth. To promote their deployment and uptake, there is a need to test and improve their robustness, performance and reliability in real-world scenarios and on concrete use cases to identify and overcome barriers to their deployment. Large scale pilots involving industry and end users can demonstrate how AI, Data and Robotics enabled solutions can benefit, both industry as well as a society, demonstrating robustness and “trustworthiness” (in all its dimension). Pilots should target technological advances with large scale potential impact ion strategically important sectors with large societal impacts such as healthcare, improved working and/or living conditions, etc.

Multidisciplinary research and innovation activities should address all of the following:

• Proposals should involve appropriate expertise in all the relevant disciplines, such as engineering, computer sciences, mathematics, Social Sciences and Humanities (SSH), biology, gender etc. and involve the relevant expertise to address the selected application sector.
• 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.
• Involvement of end-users in the requirement and validation of the pilots to ensure human-centric approach and maximise acceptance.
• Proposals should include a clear business case and exploitation strategy.
• Build on existing standards or contribute to standardisation. Interoperability for data sharing should be addressed, notably through the implementation of the FAIR data principles and adopting standardised and discipline-oriented metadata schemas and ontologies.
• Projects should build on or seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms.

All proposals should demonstrate the assessment criteria upon which the proposed sectors/use-cases have been selected (e.g. in terms of socioeconomic factors, etc.).

All proposals are furthermore expected to embed mechanisms to assess and demonstrate progress (with qualitative and quantitative KPIs, benchmarking and progress monitoring, as well as illustrative application use-cases demonstrating concrete potential added value), 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 through the sharing of results and best practice.

This topic implements the co-programmed European Partnership on AI, data and robotics.