Data-centric AI: Perspectives and Challenges
Abstract
The role of data in building AI systems has recently been significantly magnified by the emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model advancements to ensuring data quality and reliability. Although our community has continuously invested efforts into enhancing data in different aspects, they are often isolated initiatives on specific tasks. To facilitate the collective initiative in our community and push forward DCAI, we draw a big picture and bring together three general missions: training data development, inference data development, and data maintenance. We provide a top-level discussion on representative DCAI tasks and share perspectives. Finally, we list open challenges. More resources are summarized at https://github.com/daochenzha/data-centric-AI
Cite
@article{arxiv.2301.04819,
title = {Data-centric AI: Perspectives and Challenges},
author = {Daochen Zha and Zaid Pervaiz Bhat and Kwei-Herng Lai and Fan Yang and Xia Hu},
journal= {arXiv preprint arXiv:2301.04819},
year = {2023}
}
Comments
Accepted by SDM 2023 Blue Sky Track. More resources are summarized at https://github.com/daochenzha/data-centric-AI