  Data-centric AI calls for better, not just bigger, datasets. As data
protection laws with extra-territorial reach proliferate worldwide, ensuring
datasets are legal is an increasingly crucial yet overlooked component of
``better''. To help dataset builders become more willing and able to navigate
this complex legal space, this paper reviews key legal obligations surrounding
ML datasets, examines the practical impact of data laws on ML pipelines, and
offers a framework for building legal datasets.
