Privatized machine learning using generative adversarial networks

A data processing system comprising:

• a memory device to store instructions;
• one or more processors to execute the instructions stored on the memory device, the instructions to cause the data processing system to perform operations comprising:
• sending a set of labeled data to a set of multiple mobile electronic devices, each of the mobile electronic devices including a first machine learning model;
• sending a unit of data to the set of multiple mobile electronic devices, the set of multiple mobile electronic devices to generate a set of proposed labels for the unit of data;
• receiving a set of proposed labels for the unit of data from the set of multiple mobile electronic devices, the set of proposed labels encoded to mask individual contributors of each proposed label in the set of proposed labels;
• processing the set of proposed labels to determine a label to assign to the unit of data;
• and
• adding the unit of data and the label to a training set for use in training a second machine learning model.