DCAI: Data-centric Artificial Intelligence

Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee

Abstract: The emergence of Data-centric AI (DCAI) represents a pivotal shift in AI development, redirecting focus from model refinement to prioritizing data quality. This paradigmatic transition emphasizes the critical role of data in AI. While past approaches centered on refining models, they often overlooked potential data imperfections, raising questions about the true potential of enhanced model performance. DCAI advocates the systematic engineering of data, complementing existing efforts and playing a vital role in driving AI success. This transition has spurred innovation in various machine learning and data mining algorithms and their applications on the Web. Therefore, we propose the DCAI Workshop at WWW'24, which offers a platform for academic researchers and industry practitioners to showcase the latest advancements in DCAI research and their practical applications in the real world.