Data-Centric Artificial Intelligence
Data-centric artificial intelligence (AI) emphasizes the systematic enhancement of data to improve AI systems. This paradigm complements the existing model-centric approach, which focuses on refining models with a fixed dataset. The article aims to introduce this concept to practitioners and researchers in Business and Information Systems Engineering, highlighting its implications and tools available for implementation.
- ▪Data-centric AI focuses on improving the quality and quantity of data used in AI systems.
- ▪This new paradigm is intended to complement model-centric AI, which has traditionally dominated AI research.
- ▪The article provides a framework for understanding data-centric AI and its relevance to the Business and Information Systems Engineering community.
Opening excerpt (first ~120 words) tap to expand
Home Business & Information Systems Engineering Article Data-Centric Artificial Intelligence Catchword Open access Published: 05 March 2024 Volume 66, pages 507–515 (2024) Cite this article You have full access to this open access article Download PDF Save article View saved research Business & Information Systems Engineering Aims and scope Submit manuscript Data-Centric Artificial Intelligence Download PDF Johannes Jakubik1, Michael Vössing1, Niklas Kühl2, Jannis Walk1 & …Gerhard Satzger1 Show authors 13k Accesses 92 Citations 14 Altmetric 2 Mentions Explore all metrics AbstractData-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…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Springer.
