Identifying and overcoming bias in machine learning

Data scientists build models using data. Real-life data captures real-life injustice and stereotypes. Are data scientists observers whose job is to describe the world, no matter how unjust it is? Charles Earl, an excellent data scientist, and my teammate says that the answer to this question is a firm “NO.” Read the latest post to learn Charles’ arguments and best practices.

Charles Earl on identifying and overcoming bias in machine learning.

via Data Speaker Series: Charles Earl on Discriminatory Artificial Intelligence — Data for Breakfast

By Boris Gorelik

Machine learning, data science and visualization

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