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大数据带来的伦理挑战。

Ethical Challenges Posed by Big Data.

作者信息

Howe Iii Edmund G, Elenberg Falicia

机构信息

Dr. Howe is a Professor of Psychiatry and Medicine, Director of Medical School Programs in Ethics, and Senior Scientist at Uniformed Services University of the Health Sciences in Bethesda, Maryland.

出版信息

Innov Clin Neurosci. 2020 Oct 1;17(10-12):24-30. eCollection 2020 Oct-Dec.

PMID:33898098
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7819582/
Abstract

Big Data is a term that refers to tremendously large data sets intended for computational analysis that can be used to advance research through revealing trends and associations. Innovative research that leverages Big Data can dramatically advance the fields of medicine and public health but can also raise new ethical challenges. This paper explores these challenges, and how they might be addressed such that individuals are optimally protected. Key ethical concerns raised by Big Data research include respecting patient's autonomy via provision of adequate consent, ensuring equity, and respecting participants' privacy. Examples of actions that could be taken to address these key concerns on a broader regulatory level, as well as on a case specific level, are presented. Big Data research offers enormous potential, but due to its widespread influence, it also introduces the potential for extensive harm. It is imperative to consider and account for the risks associated with this research.

摘要

大数据是一个术语,指的是用于计算分析的极大数据集,这些数据集可通过揭示趋势和关联来推动研究。利用大数据的创新性研究能够极大地推动医学和公共卫生领域的发展,但也会带来新的伦理挑战。本文探讨了这些挑战,以及如何应对这些挑战以实现对个人的最佳保护。大数据研究引发的关键伦理问题包括通过提供充分的知情同意来尊重患者的自主权、确保公平以及尊重参与者的隐私。文中还列举了在更广泛的监管层面以及具体案例层面为应对这些关键问题可采取的行动示例。大数据研究具有巨大潜力,但由于其广泛影响,也带来了造成广泛危害的可能性。必须考虑并权衡与该研究相关的风险。

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本文引用的文献

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Cambridge Analytica controversy must spur researchers to update data ethics.剑桥分析公司争议必须促使研究人员更新数据伦理。
Nature. 2018 Mar;555(7698):559-560. doi: 10.1038/d41586-018-03856-4.
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Science. 2019 Oct 25;366(6464):447-453. doi: 10.1126/science.aax2342.
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Digital Futures Past - The Long Arc of Big Data in Medicine.数字未来的过去——医学大数据的漫长轨迹
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Artificial Intelligence in Health Care: Will the Value Match the Hype?医疗保健中的人工智能:其价值能否与炒作相匹配?
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Gender equality in science, medicine, and global health: where are we at and why does it matter?科学、医学和全球健康领域的性别平等:我们处于什么位置,为什么这很重要?
Lancet. 2019 Feb 9;393(10171):560-569. doi: 10.1016/S0140-6736(18)33135-0.
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Deep Learning in Medicine-Promise, Progress, and Challenges.医学中的深度学习——前景、进展与挑战
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