BMWi: Deutsch-Französische Projekte zu Künstlicher Intelligenz

Auszug aus dem englischen Call Text:

This joint call is directed towards applied Franco-German research and innovation projects on artificial intelligence technologies for risk prevention, crisis management and resilience. The call aims to explore how AI could help to create solutions that would detect and anticipate crises in the near future and minimise their impact by providing support with decision-making and automation. A new initiative for modelling and prediction tools and for automation in order to create a more resilient society is needed to help us tackle the challenges of crisis management. The main focus will be on economically and politically important areas of application such as health, commerce and sustainability. The knowledge gained from this collaboration and the resulting solutions should be transferable to different types of crisis. The call focuses on accelerating the transfer of technology from research to SMEs and into business models and products. The objective is to bring about new cooperation projects, especially new projects involving cooperation between research and industry. The joint projects will aim at developing precompetitive products and services and will select subjects which entail technological barriers but offer great economic potential in both countries. Scientific findings should be transferable into the development of marketable high-tech technologies with a high degree of potential for practical applications.

Fields of application

The selected fields of application, such as health, commerce and sustainability, are some of the areas most affected by the crisis. However, the results of the projects could also be relevant for other types of crisis, and further synergies with fields of application which have already been able to make successful use of AI could be of interest. Use cases for AI have to be developed.

1. Health issues

Major health issues include early detection of epidemics, care of the population and crisis management. Some questions are:  How can AI methods be used for the early detection of epidemics?  What possibilities does AI offer to effectively support health organisations like clinics, doctors‘ practices or health authorities during an epidemic?  How can AI help, for example, with the swifter evaluation of scientific findings regarding medical procedures, or with the swifter development of necessary products like rapid tests, drugs or vaccines?  What might be the impact of using AI in diagnostics and in the monitoring of patients at risk? The following innovation topics in health applications are given as examples: – Interoperability of different medical domains within a digital data production network, e.g. on the basis of biological data because they are well structured and intellectual property rights are clarified – Supporting health organisations (management of services to organise healthcare in a hospital) – Tracking the virus (following the epidemic within a structure) – Virtual trials – Simulating lockdown and unlocking strategies (transversal subject to socioeconomics) – Designing the best physical distancing – Digital models of patients – Operating clinical trials using real-life data more speedily – Building relevant and real-time indicators on health, commerce or social life, and organising the data – Using standardised data, e.g. SNOMED CT, EHR or biological data as an opening strategy for connectivity to the European Union and the international level.

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The project proposal must be submitted by a binational consortium including at least one eligible partner for each of the two participating agencies (Bpifrance for France, DLR for Germany). The consortium must be composed of at least one company and one research actor carrying out an activity in the general interest and without a project partner representing more than 70% of the project expenditure.