In her 2020 State of the Union Address,a President of the European Commission von der Leyen called for Europe to lead the way on digital in the areas of data and artificial intelligence (AI). Artificial intelligence, data and robotics (ADR) present an opportunity and a challenge for Europe, a chance to improve the competitiveness of the European public and private sectors, and a challenge to translate Europe’s core AI, data, and robotics strengths into a global market advantage (see Figure 1).
Figure 1. Challenges for adoption of AI, data, and robotics in Europe.
Working together, the Big Data Value Association (BDVA), the Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE), the European Laboratory for Learning and Intelligent Systems (ELLIS), the European Association for Artificial Intelligence (EurAI), and the European Robotics Association (euRobotics) have founded the AI, Data and Robotics Association (Adra) in order to establish an effective European Partnership on AI, Data and Robotics with the European Commission. The objective is to strengthen European competitiveness, societal well-being, and environmental sustainability. The vision is to lead the world in researching, developing, and deploying value-driven trustworthy AI, data, and robotics based on fundamental European rights, principles, and values.
The partnership is unique in bringing together AI, data, and robotics disciplines within a single initiative with a budget of €2.6 billion (US $3 billion). Adra represents the private side of the partnership and developed the Strategic Research, Innovation and Deployment Agenda (SRIDA)4 to guide the partnership’s work.
To achieve this vision, a better-integrated ecosystem must evolve. Figure 2 depicts the context for the partnership by clustering the primary areas of importance for AI, data, and robotics research, innovation, and deployment into three overarching areas of interest.
Figure 2. European AI, data, and robotics framework and enablers.
The European AI, Data and Robotics Framework shows the legal and societal context of ADR’s impact on stakeholders and users of ADR-enabled products and services. Products and services based on AI, data, and robotics must be based on values compatible with principles for European rights and values.2,3 Users will only accept AI, data, and robotics products and technologies when they both trust them and see their value.
The AI, Data and Robotics Innovation Ecosystem Enablers represent activities in the ecosystem that underlie innovation across sectors and from research to deployment. To meet the goal, a substantial development in skills and knowledge is needed in European industry. For AI, data, and robotics to develop further, large volumes of cross-sectorial, unbiased, high-quality, and trustworthy data must become available. Data spaces, platforms, and marketplaces are enablers, the key to unleashing the potential of such data.1 Experimentation and sandboxes are critical for ADR-based innovation because of the need to deploy in complex physical and digital environments.
Cross-Sectorial AI, Data and Robotics Technology Enablers represent the core technical competencies essential for developing successful AI, data, and robotics systems, services, and products. The sensing and perception, and knowledge and learning technology enablers create the data and knowledge on which decisions are made. These are used by the reasoning and decision-making technologies to deliver; edge and cloud-based decision making, planning, search and optimization in systems, and the multilayered decision-making necessary for AI, data and robotics systems operating in complex environments. Action and interaction covers the challenges of human interaction, machine-to-machine inter-operation, and machine interaction with the human environment, which can be even physical in the case of robotics applications. Finally, systems, methodologies, hardware, and tools provide methods that enable the construction and configuration of systems by integrating technologies into systems and ensuring core systems properties, such as safety, robustness, dependability, and trustworthiness, are met. Each technical enabler overlaps with the other, and there are no clear boundaries. Indeed, exciting advances are most often made in the intersections between these five areas and the system-level synergies that emerge from their interconnections.
Conclusion
The partnership on AI, data, and robotics will mobilize the ADR ecosystem in Europe to provide strong leadership in these areas, both in science, innovation, and deployment. It will create dialogues that address fundamental issues around deployment and citizen trust in AI. It will enable a rich AI, data, and robotics innovation ecosystem built on Europe’s many strong components, from its strong academic excellence, strong skills pipeline, and global companies to its innovation-driving regulation and standards coupled to best practice.
This work is licensed under a Creative Commons Attribution 4.0 International License. 
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