Building legal datasets
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...
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2021
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| Online Access: | https://ink.library.smu.edu.sg/sol_research/3442 https://ink.library.smu.edu.sg/context/sol_research/article/5400/viewcontent/BuildingDatasets_2021_wp.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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