Web: http://arxiv.org/abs/2206.11673

June 24, 2022, 1:11 a.m. | Moritz Hardt, Michael P. Kim

stat.ML updates on arXiv.org arxiv.org

When does a machine learning model predict the future of individuals and when
does it recite patterns that predate the individuals? In this work, we propose
a distinction between these two pathways of prediction, supported by
theoretical, empirical, and normative arguments. At the center of our proposal
is a family of simple and efficient statistical tests, called backward
baselines, that demonstrate if, and to which extent, a model recounts the past.
Our statistical theory provides guidance for interpreting backward baselines, …

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