Construct · 1 fields · 1 citations

historical bias: a standalone construct

One name. One construct. A landmark on the map.

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historicalbias1 CONSTRUCTHistorical biasSURESH · ALGORITHMIC FAIRNESS

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Algorithmic fairness

harm arising in a machine learning system because the world the data reflect already contains inequities, even when data are measured and sampled perfectly.

In algorithmic fairness, historical bias refers to harm arising in a machine learning system because the world the data reflect already contains inequities, even when data are measured and sampled perfectly. This meaning comes from Suresh (2021) in Equity and Access in Algorithms, Mechanisms, and Optimization.[1]

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Nearby constructs

aggregation bias1 fields · 1 citationsanchor · a standalone constructrepresentation bias1 fields · 1 citationsanchor · a standalone constructbias6 fields · 8 citationsjingle · one name, six constructs

References

  1. Suresh, H., & Guttag, J. (2021). A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle. Equity and Access in Algorithms, Mechanisms, and Optimization. https://doi.org/10.1145/3465416.3483305

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