Literature Study on Bias and Fairness in Machine Learning Systems

In this work, we investigated research identifying different sources causing biases impacting artificial intelligence and machine learning applications. This work evaluated other areas causing unfairness in artificial intelligence and machine learning-based applications. This work identifies that many avenues still need to be explored. Some future directions and solutions can be taken to mitigate the problem of bias in artificial intelligence and machine learning-based systems. There are still many future directions and solutions that can be taken to mitigate the problem of bias in AI systems. This survey will likely motivate researchers to tackle these issues shortly by observing existing work in their respective fields.