April 4, 2024, 4:42 a.m. | Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang

cs.LG updates on arXiv.org arxiv.org

arXiv:2307.05862v2 Announce Type: replace
Abstract: Machine learning is traditionally studied at the model level: researchers measure and improve the accuracy, robustness, bias, efficiency, and other dimensions of specific models. In practice, the societal impact of machine learning is determined by the surrounding context of machine learning deployments. To capture this, we introduce ecosystem-level analysis: rather than analyzing a single model, we consider the collection of models that are deployed in a given context. For example, ecosystem-level analysis in hiring recognizes …

abstract accuracy analysis arxiv bias context cs.ai cs.cy cs.lg deployments dimensions ecosystem efficiency impact machine machine learning practice researchers robustness type

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