Abstract: A method and a system are disclosed for generating synthetically anonymized data, the method comprising providing first data to be anonymized; providing a data embedding comprising data features, wherein data features enable a representation of corresponding data, and wherein the data is representative of the first data; providing an identifier embedding comprising identifiable features, wherein the identifiable features enable an identification of the data and the first data; providing a task-specific embedding comprising task-specific features, wherein said task-specific features enables a disentanglement of different classes relevant to the given task; generating synthetically anonymized data, the generating comprising a generative process using samples comprising a first sampling from the data embedding which ensures that a corresponding first sample originates away from a projection of the data and the first data in the identifier embedding and a second sampling from the task-specific embedding which ens