What is data ethics?
What is data ethics?
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DOI：
10.1098/rsta.2016.0360
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发表时间：
2016-12-28
期刊：
影响因子：
5
通讯作者：
Taddeo, Mariarosaria
中科院分区：
文献类型：
--
作者：
Floridi, Luciano;Taddeo, Mariarosaria
本期主题刊的创立目标是将数据伦理学作为一个新的伦理学分支，研究和评估与数据（包括生成、记录、管理、处理、传播、共享和使用）、算法（包括人工智能、人工代理、机器学习和机器人）和相应的实践（包括负责任的创新、编程、黑客和专业代码）相关的道德问题。为了制定和支持道德上好的解决方案（例如，正确的行为或正确的价值观）。数据伦理学建立在计算机和信息伦理学提供的基础之上，但与此同时，它通过将伦理调查的抽象层次从以信息为中心转移到以数据为中心，从而改进了迄今为止在该研究领域所认可的方法。这种转变使人们关注到各种数据的不同道德层面，甚至是那些从未直接转化为信息但可以用来支持行动或产生行为的数据。它强调了伦理分析需要关注计算操作的内容和本质——硬件、软件和数据之间的相互作用，而不是各种数字技术使它们成为可能。它还强调了数据科学带来的伦理挑战的复杂性。由于这种复杂性，数据伦理学应该从一开始就作为一个宏观伦理学来发展，也就是说，作为一个整体框架，避免狭隘的、特别的方法，并在一个一致的、整体的和包容的框架内解决数据科学及其应用的伦理影响和影响。只有作为一种宏观伦理学，数据伦理学才能提供解决方案，为我们的社会、我们所有人和我们的环境最大化数据科学的价值。本文是“数据科学的伦理影响”主题的一部分。
This theme issue has the founding ambition of landscaping data ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data ethics builds on the foundation provided by computer and information ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the level of abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations-the interactions among hardware, software and data-rather than on the variety of digital technologies that enable them. And it emphasizes the complexity of the ethical challenges posed by data science. Because of such complexity, data ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of data science and its applications within a consistent, holistic and inclusive framework. Only as a macroethics will data ethics provide solutions that can maximize the value of data science for our societies, for all of us and for our environments.This article is part of the themed issue 'The ethical impact of data science'.