Abstract: Systems and methods for generating machine learning model output from an input data set is provided. The system includes a processor and a memory coupled to the processor. The memory may store processor-executable instructions that, when executed, configure the processor to: obtain a qualitative data set; determine a regularization threshold value based on the qualitative data set for regularizing the machine learning output; determine a quantitative feedback score for the input data set, wherein the quantitative feedback score includes a bias-detection indication value; determine an adjustment parameter based on the quantitative feedback score and the regularization threshold value; and update the machine learning model based on the determined adjustment parameter.