Anagrafe della ricerca

CISC - Collaborative Intelligence for Safety Critical systems

Durata:
48 mesi (2025)
Responsabile scientifico:
Tipo di progetto:
Ricerca UE - H2020 - Excellent Science - Marie Curie
Ente finanziatore:
COMMISSIONE EUROPEA
Codice identificativo progetto:
Ruolo PoliTo:
Partner

Abstract

'The European Commission 'The European Commissions guidelines on ethics in artificial intelligence' (AI), published in April 2019, recognised the importance of a 'human-centric' approach to AI that is respectful of European values. Dedicated training schemes to prepare for the integration of human-centric AI into European innovation and industry are now needed. AIs should be able to collaborate with (rather than replace) humans. Safety critical applications of AI technology are human-in-the-loop scenarios, where AI and humans work together, as manufacturing processes, IoT systems, and critical infrastructures. The concept of Collaborative Intelligence is essential in these scenarios. The CISC EID will nurture and train 14 world class-leading Collaborative Intelligence Scientists for safety critical situations and provide a blue-print for postgraduate training in this area. The development of Collaborative Intelligence systems requires an interdisciplinary skill set blending expertise across AI, Human Factors, Neuroergonomics and System Safety Engineering. This inter-disciplinary skill-set is not catered for in traditional training courses at any level. The CISC training programme will develop Collaborative Intelligence Scientists with the expertise and skill set necessary to carry-out the major tasks required to develop a Collaborative Intelligence system: (1) Modelling the dynamics of system behaviours for the production processes, IoT systems, and critical infrastructures (System Safety Engineering); (2) Designing and implementing processes capable of monitoring interactions between automated systems and the humans destined to use them (Human Factors/Neuroergonomics); (3) Using data analytics and AI to create novel human-in-the-loop automation paradigms to support decision making and/or anticipate critical scenarios; and, (4) Managing the Legal and Ethical implications in the use of physiology-recording wearable sensors and human performance data in AI algorithms.'

Strutture coinvolte

Partner

  • Adient Interiors d.o.o.
  • European DIGITAL SME Alliance
  • Fakultet Inzenjerskih Nauka Univerziteta u Kragujevcu
  • Irish Manufacturing Research
  • IVECO Espana sl
  • MATHEMA
  • mBrainTrain
  • PILZ Ireland Industrial Automation
  • POLITECNICO DI TORINO
  • Technological University of Dublin - Coordinatore
  • Università degli Studi di Milano
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Parole chiave

Settori ERC

PE6_12 - Scientific computing, simulation and modelling tools
PE6_9 - Human computer interaction and interface, visualisation and natural language processing
PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE6_7 - Artificial intelligence, intelligent systems, multi agent systems
LS1_1 - Molecular interactions
LS1_10 - Structural biology (NMR)

Obiettivi di Sviluppo Sostenibile (Sustainable Development Goals)

Obiettivo 12. Garantire modelli sostenibili di produzione e di consumo

Budget

Costo totale progetto: € 3.605.667,12
Contributo totale progetto: € 3.605.667,12
Costo totale PoliTo: € 558.801,33
Contributo PoliTo: € 558.801,33

Attività di comunicazione