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Data Science
Using Python to Mitigate Bias and Discrimination in Machine Learning Models
Machine learning models can be used in critical applications, such as hiring processes, the judicial system, credit scoring, or facial recognition systems. In these cases, it is essential to ensure that the algorithms used do not discriminate against those they are assessing.There have been a number of high-profile, real-world instances of AI systems displaying bias and materially impacting particular groups. A 2018 study, for example, found that three popular facial recognition systems appeared to be biased, and incorrectly classified up to 34.7% of Black women compared to a 0.8% error rate for white men.