Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm emphasizing that the systematic design and engineering of data is essential for building effective and efficient AI-based systems. The objective of this article is to introduce practitioners and researchers from the field of Information Systems (IS) to data-centric AI. We define relevant terms, provide key characteristics to contrast the data-centric paradigm to the model-centric one, and introduce a framework for data-centric AI. We distinguish data-centric AI from related concepts and discuss its longer-term implications for the IS community.

翻译：数据为中心的人工智能（data-centric AI）代表一种新兴范式，强调数据的系统化设计与工程化对于构建高效 AI 系统至关重要。本文旨在向信息系统（IS）领域的研究者与实践者介绍这一范式。我们将定义相关术语，提供区分数据为中心范式与模型为中心范式的主要特征，并引入数据为中心 AI 的框架。同时，我们辨析数据为中心 AI 与相关概念的差异，并探讨其对 IS 领域的长期影响。