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In this article, I break down what algorithmic bias is, how it presents itself in machine learning systems, and how it can be mitigated. I’ll get into the finer details of the different types of bias and the negative business impacts of bias.

Machines aren’t human and, in theory, should not be guided by human prejudices and biases – how then can a machine exhibit algorithmic bias (or simply bias)?

Developers of machine learning systems should flag ethical issues and recognize the moral and ethical responsibilities they have when developing machine learning systems.

As machine learning moves from the research lab to the enterprise, algorithmic bias is a huge impediment to fully realizing the benefits of machine learning.

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