Supreme food system digitalization envisioned in 2100
Community-based federated generative AI with real-time forecasting and interventions to dynamically optimize food system parameters
Real-time dynamically updated strategies
Both local and sector-level information will be continuously updated in real-time, ensuring a highly dynamic resource. The decision support system will then formulate tailor-made optimal intervention strategies for the individuals in the food system based on the latest sectoral and local data.
Advanced natural language models and visual content generation
The decision support system will utilize the capabilities of advanced natural language models and visual content generation techniques to create highly user-friendly interfaces
More ethical and responsible data sourcing and usage
The community-based federated data & AI system will prioritize ethical data sourcing and usage (all data in the network are authorized by the data owners), adhering to responsible practices (based on the agreements or protocols with the data owners). This entails safeguarding privacy, obtaining consent, and employing data in a manner that upholds the rights and well-being of individuals and communities
If there are possible societal issues related to the digital twin, it is possible to add a new set of cards in MIRO, which present societal issues that digital twins might raise. In this round participants are asked to choose the issue that they want to debate by means of inserting their likes. The issue that receives most likes is discussed further in Teams. This phase invites participants to reflect as citizens on the future with the digital twin.
Local solutions with the help of sectoral information
In the future, stakeholders within the food system, such as individual farmers, will have the capacity to enhance their operations by integrating the sector-level insights with their specific local circumstances.