Data-Centric Artificial Intelligence

Johannes Jakubik (), Michael Vössing, Niklas Kühl, Jannis Walk and Gerhard Satzger
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Johannes Jakubik: Karlsruhe Institute of Technology
Michael Vössing: Karlsruhe Institute of Technology
Niklas Kühl: University of Bayreuth
Jannis Walk: Karlsruhe Institute of Technology
Gerhard Satzger: Karlsruhe Institute of Technology

Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, 2024, vol. 66, issue 4, No 6, 507-515

Abstract: Abstract Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm that emphasizes the importance of enhancing data systematically and at scale to build effective and efficient AI-based systems. The novel paradigm complements recent model-centric AI, which focuses on improving the performance of AI-based systems based on changes in the model using a fixed set of data. The objective of this article is to introduce practitioners and researchers from the field of Business and Information Systems Engineering (BISE) to data-centric AI. The paper defines relevant terms, provides key characteristics to contrast the paradigm of data-centric AI with the model-centric one, and introduces a framework to illustrate the different dimensions of data-centric AI. In addition, an overview of available tools for data-centric AI is presented and this novel paradigm is differenciated from related concepts. Finally, the paper discusses the longer-term implications of data-centric AI for the BISE community.

Keywords: Data-centric artificial intelligence; Data quality; Data work (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12599-024-00857-8

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