Tailor: Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization
Artificial Intelligence (AI) and all the key digital technologies that are subsumed by the term AI today are an essential part of the answers to many of the daunting challenges that we are facing. AI will impact the everyday lives of citizens as well as all business sectors. To maximize the opportunities and minimize the risks, Europe focuses on human-centered Trustworthy AI, and is taking important steps towards becoming the worldwide centre for Trustworthy AI. Trustworthiness however still requires significant basic research, and it is clear that the only way to achieve this is through the integration of learning, optimisation and reasoning, as neither approach will be sufficient on its own.
The purpose of TAILOR (No. 952215)is to build a strong academic-public-industrial research network with the capacity of providing the scientific basis for Trustworthy AI leveraging and combining learning, optimization and reasoning for realizing AI systems that incorporate the safeguards that make them in the reliable, safe, transparent and respectful of human agency and expectations. Not only the mechanisms to maximize benefits, but also those for minimizing harm. The network will be based on a number of innovative state-of-the-art mechanisms. A multi-stakeholder strategic research and innovation research roadmap coordinates and guides the research in the five basic research programs. Each program forming virtual research environments with many of the best AI researchers in Europe addressing the major scientific challenges identified in the roadmap. A collection of mechanisms supporting innovation, commercialization and knowledge transfer to industry. To support network collaboration TAILOR provides mechanisms such as AI-Powered Collaboration Tools, a PhD program, and training programs. A connectivity fund to support active dissemination across Europe through for example allowing the network to grow and to support the scientific stepping up of more research groups.