Data Representativity for Machine Learning and AI Systems. (arXiv:2203.04706v1 [stat.ML])

Data representativity is crucial when drawing inference from data through
machine learning models. Scholars have increased focus on unraveling the bias
and fairness in the models, also in relation to inherent biases in the input
data. However, limited work exists on the representativity of samples
(datasets) for appropriate inference in AI systems. This paper analyzes data
representativity in scientific literature related to AI and sampling, and gives
a brief overview of statistical sampling methodology from disciplines like
sampling of physical …

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