FAIR
Future Artificial Intelligence Research
![logo](https://www.unict.it/sites/default/files/styles/logo_progetti_ricerca/public/logo_progetti_ricerca/logo_fair.png?itok=ztaTw9U-)
Classification:
national research
Programme:
PNRR - Partenariati estesi
Call:
Decreto Direttoriale MUR n. 341 del 15/03/2022 - Avviso pubblico per la presentazione di Proposte di intervento per la creazione di “Partenariati estesi alle università, ai centri di ricerca, alle aziende per il finanziamento di progetti di ricerca di base” – nell’ambito del Piano Nazionale di Ripresa e Resilienza, Missione 4 “Istruzione e ricerca” – Componente 2 “Dalla ricerca all’impresa” – Investimento 1.3, finanziato dall’Unione europea – NextGenerationEU
Main ERC field:
Physical Sciences and Engineering
Unict role:
Partner
Duration (months):
36
Start date:
Sunday, January 1, 2023
End date:
Wednesday, December 31, 2025
Total cost:
€ 122.043.643,00
Unict cost:
€ 5.703.895,26
Coordinator:
Consiglio Nazionale delle Ricerche
Principal investigator in Unict:
Prof. Concetto Spampinato
University department involved:
Department of Mathematics and Computer Science
Department of Law
Department of Electrical, Electronic and Computer Engineering
Department of Economics and Business
Participants:
- Bracco Imaging
- Deloitte Risk Advisory SRLSB
- Expert.ai
- Fondazione Bruno Kessler
- Intesa Sanpaolo
- Istituto Italiano di Tecnologia
- Istituto Nazionale di Fisica Nucleare
- Leonardo
- Lutech
- Politecnico di Milano
- Politecnico di Torino
- Scuola Internazionale Superiore di Studi Avanzati
- Scuola Normale Superiore
- ST-Microelectronics
- Università Campus Bio-Medico di Roma
- Università Commerciale Luigi Bocconi
- Università degli Studi di Bari "Aldo Moro"
- Università degli Studi di Napoli "Federico II"
- Università degli Studi di Roma “La Sapienza”
- Università degli Studi della Calabria
- Università degli Studi di Bologna
- Università degli Studi di Pisa
- Università degli Studi di Trento
Abstract
Well beyond currently available technologies, FAIR aims at devising and developing AI systems capable of interacting and collaborating with humans, of perceiving and acting within evolving contexts, of being aware of their own limitations and able to adapt to new situations, and interact appropriately in complex social settings, of being aware of their perimeters of security and trust, and of being attentive to the environmental and social impact that their implementation and execution may entail.
In short, FAIR aims at building an AI that does not yet exist. To meet this level of ambition, FAIR envisions new forms of AI that are:
- human-centered: co-evolve with the human “in-the-loop”, at individual and collective level
- integrative: bridge across the different AI methods, technologies, disciplines, and competences
- resilient: operate in challenging, noisy, uncertain real-world settings, 4. adaptive: perceive, learn and act in dynamically changing environments
- high-quality: meet quality standards for high-risk, high-accuracy, safety-critical applications
- symbiotic: promote effective human-machine interaction and collaboration
- edge/exascale: operate at the infinitely small on the edge, and at the infinitely big on the cloud
- pervasive: operate ubiquitously in different social settings
- green-aware: consider the environmental dimension “by-design”
- sustainable and bio-cognitive: mimic the principles of biological systems at multiple scales