Department of Psychology, Stanford University, Stanford, California, USA.
Hum Brain Mapp. 2022 Jun 1;43(8):2707-2721. doi: 10.1002/hbm.25803. Epub 2022 Feb 10.
Sharing data is a scientific imperative that accelerates scientific discoveries, reinforces open science inquiry, and allows for efficient use of public investment and research resources. Considering these benefits, data sharing has been widely promoted in diverse fields and neuroscience has been no exception to this movement. For all its promise, however, the sharing of human neuroimaging data raises critical ethical and legal issues, such as data privacy. Recently, the heightened risks to data privacy posed by the rapid advances in artificial intelligence and machine learning techniques have made data sharing more challenging; the regulatory landscape around data sharing has also been evolving rapidly. Here we present an in-depth ethical and regulatory analysis that examines how neuroimaging data are currently shared against the backdrop of the relevant regulations and policies in the United States and how advanced software tools and algorithms might undermine subjects' privacy in neuroimaging data sharing. The implications of these novel technological threats to privacy in neuroimaging data sharing practices and policies will also be discussed. We then conclude with a proposal for a legal prohibition against malicious use of neuroscience data as a regulatory mechanism to address privacy risks associated with the data while maximizing the benefits of data sharing and open science practice in the field of neuroscience.
数据共享是加速科学发现、强化开放科学探究以及实现公共投资和研究资源高效利用的科学要务。鉴于这些益处,数据共享已在不同领域得到广泛推广,神经科学也不例外。然而,尽管数据共享前景广阔,但它也引发了一些关键的伦理和法律问题,例如数据隐私问题。最近,人工智能和机器学习技术的快速发展给数据隐私带来了更高的风险,使得数据共享更加具有挑战性;数据共享的监管环境也在迅速演变。在这里,我们进行了深入的伦理和法规分析,研究了在美国相关法规和政策背景下,神经影像学数据目前是如何被共享的,以及先进的软件工具和算法可能如何破坏神经影像学数据共享中受试者的隐私。我们还讨论了这些新型技术对神经影像学数据共享实践和政策中隐私的威胁所产生的影响。最后,我们提出了一项禁止恶意使用神经科学数据的法律建议,将其作为一种监管机制,以解决与数据相关的隐私风险,同时在神经科学领域最大限度地提高数据共享和开放科学实践的益处。