解决神经科学数据中的隐私风险:从数据保护到危害预防。

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2022-09-04 eCollection Date: 2022-07-01 DOI:10.1093/jlb/lsac025
Anita S Jwa, Russell A Poldrack
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引用次数: 5

摘要

最近在研究和临床环境内外的神经科学数据的数量和可用性的增加将增强神经科学研究的可重复性,从而导致健康和疾病状态下大脑功能机制的新发现。然而,神经科学数据的独特敏感性引发了对数据隐私的关键担忧。针对这些问题,人们提出了各种政策和监管方法来控制神经科学数据的获取和披露,但过度的限制可能会阻碍该领域的开放科学实践。本文认为,现在可能是时候将监管话语的范围扩大到保护神经科学数据之外,并开始考虑如何预防潜在的危害。从法律上禁止有害使用神经科学数据可以为防范隐私风险提供最终保障,并将帮助我们找到一条保护数据主体的道路,同时又不会过度限制开放科学实践的好处。本文以美国《遗传信息不歧视法》(GINA)为参考,从GINA的立法过程中吸取教训,分析其保护的优缺点,探讨其核心监管问题的答案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Addressing privacy risk in neuroscience data: from data protection to harm prevention.

A recent increase in the amount and availability of neuroscience data within and outside of research and clinical contexts will enhance reproducibility of neuroscience research leading to new discoveries on the mechanisms of brain function in healthy and disease states. However, the uniquely sensitive nature of neuroscience data raises critical concerns regarding data privacy. In response to these concerns, various policy and regulatory approaches have been proposed to control access to and disclosure of neuroscience data, but excessive restriction may hamper open science practice in the field. This article argues that it may now be time to expand the scope of regulatory discourse beyond protection of neuroscience data and to begin contemplating how to prevent potential harm. Legal prohibition of harmful use of neuroscience data could provide an ultimate safeguard against privacy risks and would help us chart a path toward protecting data subjects without unduly limiting the benefits of open science practice. Here we take the Genetic Information Non-Discrimination Act (GINA) as a reference for this new legislation and search for answers to the core regulatory questions based on what we have learned from the enactment of the GINA and the merits and weaknesses of the protection it provides.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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