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.

The DIGITbrain project is deeply rooted in the innovation ecosystem of the I4MS project CloudiFacturing and the industrial platforms FIWARE and IDS, and it will build on these results, by means of extending the CloudiFacturing solution with an augmented digital-twin concept called “Digital Product Brain” (DPB) and a smart business model called “Manufacturing as a Service” (MaaS). By having access to on-demand data, models, algorithms, and resources for industrial products (i.e. mechatronic systems supporting the production of other products), the DBP will enable their customisation and adaptation according to individual conditions. The availability of industrial-product capacity will facilitate the implementation of MaaS, which will allow manufacturing SMEs to access advanced manufacturing facilities within their regions or to distribute their orders across different ones. The DIGITbrain project will address four principles that will foster the uptake of advanced digital and manufacturing technologies. A) Technology: leverage edge-, cloud- and HPC-based modelling, simulation, optimisation, analytics, and machine learning tools and augment the concept of digital twin with a memorizing capacity that records the provenance of the industrial product over its full lifecycle. B) Feasibility: support more than 20 highly innovative cross-border experiments, bringing together technology providers and manufacturing end users, and facilitating cost-effective distributed and localised production, based on on-demand manufacturing machine capacity. C) Sustainability: coach and empower DIHs to implement the smart business model MaaS and contribute to their long-term sustainability, by increasing their portfolio with services tailored to the industrial needs of their regions. D) Network of DIHs: engage DIHs across Europe that implement MaaS, enable manufacturing SMEs to co-create and experiment with digital innovations before investing, and attract national and regional funding.

VISION: By 2023, Europe will set the reference for the Industry 4.0 market: European CPS/IOT Open Digital Platforms providers will be able to flexibly and dynamically connect the Real World with digital Enterprise Systems through common open standards; European ICT SMEs will be growing fast through leadership in data-driven smart Industry 4.0 services; European Manufacturing SMEs will successfully compete globally with innovative products and services, digitised Industry 4.0 processes and innovative business models, involving their workforce at all levels in this Digital Transformation innovations. MISSION. The MIDIH 4.0 project aims at implementing the fast, dynamic, borderless, disruptive side of the I4MS innovation coin: technological services (interactive try-on demos, webinars, challenges, hackathons and awards) will be driven by young and dynamic ICT talents virtually meeting older and experienced manufacturing engineers in a one-stop-shop global marketplace; business services (ideas incubation, business acceleration, demand-offer matchmaking and brokerage, access to finance) will support SMEs, startups, web entrepreneurs as well as corporates in the delivery of innovative products and services, in accessing new markets, in fund-raising; skills building services (serious and role games, participative lessons and webinars, virtual experiments in physical teaching factories, professional courses for existing technicians as well as for executives) will not only help SMEs and corporates understand the new technologies, but also take full advantage of them, providing an operational framework that will stimulate trust, confidence and investments. The MIDIH project is an inclusive Innovation Action of 21 beneficiaries coming from 12 EU Countries, including, Competence Centers, Digital Innovation Hubs, CPS/IOT Technology Providers as well as Lighthouse Manufacturing Industries. A two-iteration Open Call will help achieve a critical mass of cross-border experiments.

Action on circularity is not taken when information and evidence is not available across the life cycle chain. The CircThread project's main objective is to unlock access to data now in silo’s, and enhancing it as decision information for actors across and outside the extended product life cycle. To do this CircThread will deliver a Circular Digital Thread methodology, a framework for facilitating information flow exchanges across the extended life cycle chain of Products, Components, their Materials and Chemicals data, and related Circularity, Environmental, Social and Economic Information. The core is to create data linkages between product chain, value chain, asset chain and life cycle chains based on a Product information Catalogue, and enable information exchanges via data contracts governed by secure and reliable management standards. The project will implement the system in Cloud Platforms in 3 demonstration clusters in Italy, Slovenia and Spain rolled-out across the entire extended life cycle chain of home appliances (incl. washing machines and dish washers) and home energy systems (incl. boilers, solar-PV systems and batteries) to test 7 circularity use cases and associated business models. The expected impact for the work programme is to enable improved decision taking accelerating Circularity and Carbon emissions reductions including: i) Enhanced life extensions of products by better understanding of in use failures and maintenance needs, ii) improved understanding of the quality of end-of-life products for spare parts buy-backs to support right to repair, iii) improved assessment of circularity routes by waste management and recycling companies by delivering enhanced product composition data, iv) improved materials and chemicals tracing of products and components for safer products and identifying Critical Raw Materials cycles, v) Empowering decisions by citizens and citizen organisations by providing direct access to product performance information.

Cognitive robots are augmenting their autonomy, enabling them to deployments in increasingly open-ended environments. This offers enormous possibilities for improvements in human economy and wellbeing. However, it also poses strong risks that are difficult to assess and control by humans. The trend towards increased autonomy conveys augmented problems concerning reliability, resilience, and trust for autonomous robots in open worlds. The essence of the problem can be traced to robots suffering from a lack of understanding of what is going on and a lack of awareness of their role in it. This is a problem that artificial intelligence approaches based on machine learning are not addressing well. Autonomous robots do not fully understand their open environments, their complex missions, their intricate realizations, and the unexpected events that affect their performance. An improvement in the capability to understand of autonomous robots is needed. This project tries to provide a solution to this need in the form of 1) a theory of understanding, 2) a theory of awareness, 3) reusable software assets to apply these theories in real robots, and 4) three demonstrations of its capability to a) augment resilience of drone teams, b) augment flexibility of manufacturing robots, and c) augment human alignment of social robots. In summary, we will develop a cognitive architecture for autonomous robots based on a formal concept of understanding, supporting value-oriented situation understanding and self-awareness to improve robot flexibility, resilience and explainability.