为实现敏感数据研究的民主化，我们应该让合成数据更容易获取

IF 6.7 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Patterns Pub Date : 2024-09-13 DOI:10.1016/j.patter.2024.101049

Erik-Jan van Kesteren

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摘要

30 多年来，合成数据一直被视为使敏感数据集可访问的解决方案。然而，尽管开展了大量研究工作，但合成数据作为敏感数据研究工具的应用还很欠缺。本文认为，要在这方面取得进展，数据科学界应集中精力提高现有隐私友好合成技术的可访问性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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To democratize research with sensitive data, we should make synthetic data more accessible

For over 30 years, synthetic data have been heralded as a solution to make sensitive datasets accessible. However, despite much research effort, its adoption as a tool for research with sensitive data is lacking. This article argues that to make progress in this regard, the data science community should focus on improving the accessibility of existing privacy-friendly synthesis techniques.

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