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H2020Doctoral network2021–2025

CISC · Collaborative Intelligence for Safety Critical systems

Horizon 2020 — Marie Skłodowska-Curie Actions

Duration
2021-01-01 → 2025-06-30
EU contribution
€3,605,548
Participants
13
Scheme
MSCA-ITN

Lines connect the coordinator with its partners. CORDIS does not always give exact coordinates for projects before 2014. These points are placed at city or country level.

Results in brief

Collaborative Intelligence for Safety Critical systems

Collaborative Intelligence for Safety Critical systems is core to the European declared 'human-centric' approach to AI that requires a human capital able to prepare for the socio-economic changes brought about by AI. While the ease of collecting and using field data with AI is increasing, few understand the importance of fully considering how to interface AIs with the humans that are supposed to use them in order to realise the anticipated benefits, and even fewer know how to address these new types of human-machine collaboration and their legal and ethical aspects, In Collaborative Intelligent systems, for instance, humans need to perform three crucial roles. They must train machines to perform certain tasks; explain the outcomes of those tasks, especially when the results are counterintuitive or controversial; and they must sustain the responsible use of machines (by, for example, preventing robots from harming humans). On the other side AI can amplify our cognitive strengths such as filter data to provide us with information about the status of a safety critical plant (e.g. distillation column) & suggest possible procedures to cope with plant status upsets. Furthermore AI systems in collaborative robotics (cobotics) can embody human skills to extend our physical capabilities. In these collaborations the end users should not to be subject to a decision based solely on automated processing and there should always be human oversight. The development of Collaborative Intelligence systems requires an interdisciplinary skillset blending expertise in AI with expertise in Human Factors, Neuroergonomics and System Safety Engineering. The CISC training programme developed Collaborative Intelligence Scientists (1) Using data analytics and AI to create novel human-in-the-loop automation paradigms to support decision making and or anticipate critical scenarios; (2) Designing and implementing processes capable of monitoring interactions between automated systems and the humans destined to use them; (3) Modelling the dynamics of system behaviours for the manufacturing process considering System Safety Engineering; (4) Managing the Legal and Ethical implications of AI algorithms, and the use of physiology recording wearable sensors and human performance data in them.

Data: CORDIS, © European Union

Project objective

The European Commission ""The European Commission’s 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.""

Original text from CORDIS.

Participants

  • TECHNOLOGICAL UNIVERSITY DUBLIN · DublinCoordinatorIreland
  • ADIENT INTERIORS D.O.O. KRAGUJEVAC · KragujevacCity levelSerbia
  • EUROPEAN DIGITAL SME ALLIANCE · Bruxelles / BrusselBelgium
  • FAKULTET INZENJERSKIH NAUKA UNIVERZITETA U KRAGUJEVCU · KragujevacSerbia
  • HUGIN EXPERT AS · AalborgDenmark
  • IRISH MANUFACTURING RESEARCH COMPANY LIMITED BY GUARANTEE · RathcooleIreland
  • IVECO ESPANA SL · MadridSpain
  • MATHEMA SRL · FirenzeItaly
  • MBRAINTRAIN DOO BEOGRAD-SAVSKI VENAC · BEOGRADSerbia
  • PILZ IRELAND INDUSTRIAL AUTOMATION DISTRIBUTION · CorkIreland
  • POLITECNICO DI TORINO · TorinoItaly
  • SOFTWARE COMPETENCE CENTER HAGENBERG GMBH · HAGENBERGAustria
  • UNIVERSITA DEGLI STUDI DI MILANO · MilanoItaly

Links

Data: CORDIS, © European Union