遗传数据并不总是个人的 - - 将遗传数据的识别性和敏感性进行分类
Johanna Rahnasto1,2,3
1Harvard University, Harvard Law School, Cambridge, MA 02138, USA.
Journal of law and the biosciences
|November 29, 2023
概括
欧盟和美国的遗传数据隐私法规需要一个细微的方法. 专注于如何使用遗传数据,而不仅仅是其特殊地位,将更好地保护隐私利益.
科学领域:
- 生物伦理学生物伦理学
- 数据隐私法 数据隐私法
- 基因组学就是基因组学.
背景情况:
- 在欧盟和美国,遗传数据被视为需要加强隐私保护的特殊类别.
- 目前的法规重点关注可识别性和敏感性,这是对遗传数据隐私的主要关注点.
- 这种方法假定所有遗传数据都是固有的可识别和敏感的,可能会忽视细微差别.
研究的目的:
- 争取一种更细致的方法来评估遗传数据对隐私的威胁.
- 建议根据数据使用的具体因素对隐私利益进行分类.
- 通过将重点从数据类别转移到数据应用来建议监管改进.
主要方法:
- 欧盟和美国遗传数据隐私框架的比较法律分析.
- 在大数据环境中检查可识别性和敏感性概念.
- 根据数据使用,数量,独特性和信息内容来分类隐私利益的框架的开发.
主要成果:
- 并非所有遗传数据都可以同样识别或敏感.
- 遗传数据与其他类型的大数据在隐私问题上具有共同的特征.
- 考虑拟议使用,数据量,独特性和内容的细微评估更有效.
结论:
- 欧盟和美国的监管方案可以通过专注于遗传数据的应用而不是其特殊类别的地位来改进.
- 对与遗传数据相关的隐私风险进行上下文依赖的评估至关重要.
- 这种方法可以更精确,更有效地保护个人隐私利益.
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