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Big data ethics, also known simply as data ethics, refers to systemizing, defending, and recommending concepts of right and wrong conduct in relation to data, in particular personal data. [1] Since the dawn of the Internet the sheer quantity and quality of data has dramatically increased and is continuing to do so exponentially.
The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. [22] [23] Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.
The datasphere is a multidisciplinary concept that first appeared in the 1980s. While many terms have been adopted to describe the digital world – terms such as the Internet, cyberspace, metaverse – the various concepts of the datasphere seem to address the growing dependency of human activities on data, as well as approach the digital world in a holistic manner.
The human-driven data economy is a fair and functioning data economy in which data is controlled and used fairly and ethically in a human-oriented manner. [8] [9] The human-driven data economy is linked to the MyData Movement and is a human-centered approach to personal data management. [10]
A team of data analysts reproduced the AI technology developed by Cambridge Analytica around Facebook's data and was able to define the following rules: 10 likes enables a machine to know a person like a coworker, 70 likes like a friend would, 150 likes like a parent would, 300 likes like a lover would, and beyond it may be possible to know a ...
The Australian Library Journal states proponents for censorship in libraries, the practice of librarians deciphering which books/ resources to keep in their libraries, argue the act of censorship is an ethical way to provide information to the public that is considered morally sound, allowing positive ethics instead of negative ethics to be ...
Also, most commercial data analysis tools are used by organizations for extracting, transforming and loading ETL for data warehouses in a manner that ensures no element is left out during the process (Turban et al., 2008). Thus the data analysis tools are used for supporting the 3 Vs in Big Data: volume, variety and velocity. Factor velocity ...
Dynamic consent is an approach to informed consent that enables on-going engagement and communication between individuals and the users and custodians of their data. It is designed to address the many issues that are raised by the use of digital technologies in research and clinical care that enable the wide-scale use, linkage, analysis and integration of diverse datasets and the use of AI and ...