The Myth Of The Impartial Machine by University of Washington
Wide-ranging applications of data science bring utopian proposals of a world free from bias, but in reality, machine learning models reproduce the inequalities that shape the data they’re fed. Can programmers free their models from prejudice?
This article walks readers through the ways in which bias can infiltrate machine learning models through animations and interactive data visualizations.
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CreditsFred Hohman - editor; Victoria Uren - editor; Matthew Conlen - design, development; Created by Alice Feng & Shuyan Wu
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