Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization

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Maximising opportunities and minimising risks associated with artificial intelligence (AI) requires a focus on human-centred trustworthy AI. This can be achieved by collaborations between research excellence centres with a technical focus on combining expertise in theareas of learning, optimisation and reasoning. Currently, this work is carried out by an isolated scientific community where research groups are working individually or in smaller networks. The EU-funded TAILOR project aims to bring these groups together in a single scientific network on the Foundations of Trustworthy AI, thereby reducing the fragmentation and increasing the joint AI research capacity of Europe, helping it to take the lead and advance the state-of-the-art in trustworthy AI. The four main instruments are a strategic roadmap, a basic research programme to address grand challenges, a connectivity fund for active dissemination, and network collaboration activities.

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 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.

The new national PhD program in Artificial Intelligence is on the launchpad! https://phd-ai.it/en/

Premio Internazionale Tecnovisionarie® 2021

Il premio Le Tecnovisionarie 2021 sul tema Intelligenza Artificiale BigData è stato consegnato a Fosca Giannotti dalla Presidente del CNR con la seguente motivazione:

MALOTEC Seminar - Riccardo Guidotti: Evaluating Local Explanation Methods on Ground Truth 09/04/2021

Riccardo is an Assistant Professor at the Department of Computer Science, University of Pisa, and a member of the Knowledge Discovery and Data Mining Laboratory (KDDLab), a joint research group with the Information Science and Technology Institute

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Acronym
TAILOR
Code
952215
Web Site
Start Date
1 September 2020
End Date
31 August 2023
Funded
European Commission H2020
Type
European Project
Area
Affiliation
Department of Computer Science, University of Pisa (DI-UNIPI)
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)