Where are human subjects in Big Data research? The emerging ethics divide
Where are human subjects in Big Data research? The emerging ethics divide
复制标题
DOI：
10.1177/2053951716650211
复制
发表时间：
2016-06-01
影响因子：
8.5
通讯作者：
Crawford, Kate
中科院分区：
文献类型：
--
作者：
Metcalf, Jacob;Crawford, Kate
数据科学的研究实践与研究伦理监管的既定工具之间存在越来越多的不连续性。现有研究伦理法规的一些核心承诺，例如研究与实践之间的区别，无法从生物医学研究干净地导出到数据科学研究。这种不连续性导致一些数据科学从业者和研究人员直接拒绝道德法规。这些转变发生在对共同规则进行重大修订的同时，该共同规则是美国人类受试者研究的主要法规，几十年来首次被考虑。我们将这些修订置于长期以来对社会科学研究监管的抱怨中，并认为数据科学应该被理解为与社会科学在这方面的连续性。拟议的法规对非生物医学研究方法更具灵活性和可扩展性，但在很大程度上将数据科学方法排除在人类受试者监管之外，特别是使用公共数据集。大数据研究的伦理框架存在很大争议，并且不断变化，数据科学研究的潜在危害是不可预测的。我们研究了数据科学中几个有争议的研究危害案例，包括2014年Facebook情绪传染研究和2016年使用地理数据技术识别匿名艺术家Banksy。为了解决关于人类主体研究伦理在数据科学中的应用的争议，关键数据研究应该提供一个历史上细致入微的“数据主体性”理论，以回应数据科学和商业的认识方法，危害和好处。
There are growing discontinuities between the research practices of data science and established tools of research ethics regulation. Some of the core commitments of existing research ethics regulations, such as the distinction between research and practice, cannot be cleanly exported from biomedical research to data science research. Such discontinuities have led some data science practitioners and researchers to move toward rejecting ethics regulations outright. These shifts occur at the same time as a proposal for major revisions to the Common Rule-the primary regulation governing human-subjects research in the USA-is under consideration for the first time in decades. We contextualize these revisions in long-running complaints about regulation of social science research and argue data science should be understood as continuous with social sciences in this regard. The proposed regulations are more flexible and scalable to the methods of non-biomedical research, yet problematically largely exclude data science methods from human-subjects regulation, particularly uses of public datasets. The ethical frameworks for Big Data research are highly contested and in flux, and the potential harms of data science research are unpredictable. We examine several contentious cases of research harms in data science, including the 2014 Facebook emotional contagion study and the 2016 use of geographical data techniques to identify the pseudonymous artist Banksy. To address disputes about application of human-subjects research ethics in data science, critical data studies should offer a historically nuanced theory of "data subjectivity'' responsive to the epistemic methods, harms and benefits of data science and commerce.