How to Remove Bias in Machine Learning Training Data

Much has changed in the AI/ML world but the concept of'garbage in; garbage out' remains stoic. Any algorithm is only as good as its training data. And, no training data is without bias, not even the ones generated through automation. In the past, many machine learning algorithms have been unfair to certain religions, races, genders, ethnicities, and economical statuses, among others. The Watson supercomputer from IBM that gave suggestions to doctors using a dataset of medical research papers was found to favor reputable studies only. Amazon's recruiting algorithm was found to favor men over women.