.png){kind=icon}
Return
Data-Centric Artificial Intelligence
.png){kind=icon}
OA
AI
DOI：10.1007/s12599-024-00857-8.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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
Journal
IF:
10.4
Papers:
862
Citations:
4.0K
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSave
ShareSaveShareSaveArtificial Bee Colony Algorithm for Economic Load Dispatch Problem with Non-smooth Cost Functions
PREAI
ShareSave
View more