Data-Centric Artificial Intelligence

Fuente: arXiv
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Autores principales: Jakubik, Johannes, Vössing, Michael, Kühl, Niklas, Walk, Jannis, Satzger, Gerhard
Formato: Preprint
Publicado: 2022
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author Jakubik, Johannes
Vössing, Michael
Kühl, Niklas
Walk, Jannis
Satzger, Gerhard
author_facet Jakubik, Johannes
Vössing, Michael
Kühl, Niklas
Walk, Jannis
Satzger, Gerhard
contents Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm emphasizing that the systematic design and engineering of data is essential for building effective and efficient AI-based systems. The objective of this article is to introduce practitioners and researchers from the field of Information Systems (IS) to data-centric AI. We define relevant terms, provide key characteristics to contrast the data-centric paradigm to the model-centric one, and introduce a framework for data-centric AI. We distinguish data-centric AI from related concepts and discuss its longer-term implications for the IS community.
format Preprint
id arxiv_https___arxiv_org_abs_2212_11854
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Data-Centric Artificial Intelligence
Jakubik, Johannes
Vössing, Michael
Kühl, Niklas
Walk, Jannis
Satzger, Gerhard
Artificial Intelligence
Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm emphasizing that the systematic design and engineering of data is essential for building effective and efficient AI-based systems. The objective of this article is to introduce practitioners and researchers from the field of Information Systems (IS) to data-centric AI. We define relevant terms, provide key characteristics to contrast the data-centric paradigm to the model-centric one, and introduce a framework for data-centric AI. We distinguish data-centric AI from related concepts and discuss its longer-term implications for the IS community.
title Data-Centric Artificial Intelligence
topic Artificial Intelligence
url https://arxiv.org/abs/2212.11854