Bias detection and reduction in machine-learning techniques

A system comprising:

• a processing device;
• and
• a memory device in which instructions executable by the processing device are stored for causing the processing device to perform operations comprising:
• determining, using a machine learning model trained using a training process, a risk indicator for a target entity from predictor variables associated with the target entity, wherein the risk indicator indicates a level of risk associated with the target entity, wherein the training process includes operations comprising:
• training the machine learning model using training samples comprising training predictor variables and training outputs corresponding to the training predictor variables,
• obtaining protected attribute data;
• calculating a bias metric using the protected attribute data and model-generated data obtained from the machine learning model, wherein the bias metric comprises a correlation metric based at least in part on a first correlation between values of a training predictor variable and the protected attribute data and a second correlation between the model-generated data and the protected attribute data;
• determining that a bias is detected based on the bias metric;
• modifying the machine learning model based on the detected bias;
• re-training the machine learning model;
• and
• transmitting, to a remote computing device, a responsive message including at least the risk indicator for use in controlling access of the target entity to one or more interactive computing environments.

A non-transitory computer-readable storage medium having program code that is executable by a processor device to cause a computing device to perform operations, the operations comprising:

• determining, using a machine learning model trained using a training process, a risk indicator for a target entity from predictor variables associated with the target entity, wherein the risk indicator indicates a level of risk associated with the target entity, wherein the training process includes operations comprising:
• training the machine learning model using training samples comprising training predictor variables and training outputs corresponding to the training predictor variables,
• obtaining protected attribute data;
• calculating a bias metric using the protected attribute data and model-generated data obtained from the machine learning model, wherein the bias metric comprises a correlation metric based at least in part on a first correlation between values of a training predictor variable and the protected attribute data and a second correlation between the model-generated data and the protected attribute data;
• determining that a bias is detected based on the bias metric;
• modifying the machine learning model based on the detected bias;
• re-training the machine learning model;
• and
• transmitting, to a remote computing device, a responsive message including at least the risk indicator for use in controlling access of the target entity to one or more interactive computing environments.