The evidence behind the guides

Sources

Find a study, check what it supports, and follow it back to a concern.

TopicCollection

2 sources

Guide citations are still under editorial review.

Suresh and Guttag · EAAMO 2021 Research framework

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle (original source, new tab)

Framework distinguishes historical, representation, measurement, aggregation, learning, evaluation, and deployment bias. These categories can overlap.

Gebru and colleagues · Communications of the ACM Research proposal

Datasheets for Datasets (original source, new tab)

Documentation questions cover composition, collection, time, uses, permissions, and maintenance. This is a documentation method, not proof of a particular dataset's defects.

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