The increasing use of artificial intelligence (AI) is revolutionising the creation of value from (measurement) data. It opens up entirely new business areas and changes practically all areas of life and the economy. In smart homes and smart cities, smart meters and controllers enable demand-centred control and efficient billing of energy and water supply as well as optimisation of network utilisation. “Predictive maintenance” using AI significantly reduces production downtimes and maintenance costs in Industry 4.0. In the healthcare sector, AI-supported diagnosis and therapy planning improve the treatment of patients and thus significantly reduce absences from work and avoidable burdens on the healthcare system. The combination of widely used measurement technology and artificial intelligence methods therefore creates enormous benefits to both the economy and society. This advance of the key technology 

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With the increasing availabildity of large volumes of data in all areas of life and the enormous technological advances in measurement technology during digitalisation, the use of artificial intelligence (AI) methods is also steadily increasing. The key technology AI is fundamentally revolutionising the understanding of products and services [1, 2] and thus acts as a catalyst for digital innovations. It is not only in Industry 4.0 where significant resources can be saved through the predictive maintenance of machines and systems using AI. New fields of application for AI are also constantly opening up in the intelligent control of supply systems in smart homes and smart cities, in self-learning diagnostic tools for personalised medicine, and in autonomous vehicles. Due to their versatility and inherent adaptability to problems of all kinds, AI systems offer outstanding economic potential as a component of products or as stand-alone items, which - if recognised and harnessed at an early stage - can decisively strengthen Germany’s position on the global market and mean significant competitive advantages across the board, from start-ups to SMEs to large corporations. 

The disruptive key technology AI has long since left the niche stage in research and is pushing onto the market in the form of a wide variety of products and services and thus into all areas of life and the economy. In order to set corresponding guidelines for this dynamic, progressing development, the EU Commission published a White Paper on artificial intelligence in February 2020. This paper builds on the European AI strategy of 2018 and places innovative, but - in contrast to the developments in the USA and China - strongly human-centred AI in the focus of further actions. This mission statement means that AI should benefit people and society while strengthening self-determined action and is often referred to as “European-style AI”. The German government has also given the issue of AI high priority and embedded it in its strategic action with the AI Strategy of 2018 and its update 2020 as well 

Human resources

PTB aims to complement its high level of metrological domain knowledge with essential AI skills in order to create and secure long-term trust in AI and act as a strong and competent authority in cooperation with partners.

Research questions

PTB sets itself the goal of developing suitable metrics for the evaluation of AI and data in its metrological research mission, adapting existing measurement and testing processes to the use of AI and, at the same time, testing and expanding the safe application of AI for metrological research and services.

Infrastructure & Data

PTB aims to establish well-organised and harmonised machine-usable data and AI methods as trust anchors for future technologies in metrology, to develop and provide digital standards (e. g., reference data sets) for metrology and to set up the necessary infrastructures.

Regulatory framework

PTB aims to proactively shape its role as an important pillar of the quality infrastructure within a regulatory framework for AI, to revise processes based on the new requirements and capabilities, and to actively contribute its metrological expertise to the standardisation as well as the assessment and certification of AI.

The objectives outlined in the previous chapters will provide a basis for comprehensive strategic considerations regarding the practical implementation. As a starting point, the development of PTB activities in relation to AI will certainly require activity in the following focus areas: