arXiv · 2211.14611
The Principles of Data-Centric AI (DCAI)
Abstract
Data is a crucial infrastructure to how artificial intelligence (AI) systems learn. However, these systems to date have been largely model-centric, putting a premium on the model at the expense of the data quality. Data quality issues beset the performance of AI systems, particularly in downstream deployments and in real-world applications. Data-centric AI (DCAI) as an emerging concept brings data, its quality and its dynamism to the forefront in considerations of AI systems through an iterative and systematic approach. As one of the first overviews, this article brings together data-centric perspectives and concepts to outline the foundations of DCAI. It specifically formulates six guiding principles for researchers and practitioners and gives direction for future advancement of DCAI.
Explore related subjects
Keep this discovery
Mohammad Hossein Jarrahi, Ali Memariani, Shion Guha. 2022-11-26. The Principles of Data-Centric AI (DCAI). https://doi.org/10.1145/3571724
Cite the original work for its findings. Save a collection to share your selection of sources.