Collectively resolving information asymmetries through data sharing clubs: agritech case study

There is a symbiotic relationship between the developers of AI services and the communities seeking to harness the benefits of AI. Some form of ecosystem governance is required if such relationships are to become mutually beneficial rather than parasitic, with one side deriving benefits at the expense of the other. This paper examines how a data trust framework can provide data sharing ecosystem governance to facilitate data flows and resolve information asymmetries between competitive entities. The EU Horizon-funded SPADE project case is discussed as an application scenario featuring agricultural drones, digital twins, and other data sharing challenges to explore this concept. We also examine how a club theory approach can help implement a sound business model with a data trust framework as a governance model.