Big data ethics

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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. Big data describes this large amount of data that is so voluminous and complex that traditional data processing application software is inadequate to deal with them. Recent innovations in medical research and healthcare, such as high-throughput genome sequencing, high-resolution imaging, electronic medical patient records and a plethora of internet-connected health devices have triggered a data deluge that will reach the exabyte range in the near future. Data ethics is of increasing relevance as the quantity of data increases because of the scale of the impact.

Big data ethics are different from information ethics because the focus of information ethics is more concerned with issues of intellectual property and concerns relating to librarians, archivists, and information professionals, while big data ethics is more concerned with collectors and disseminators of structured or unstructured data such as data brokers, governments, and large corporations. However, since artificial intelligence or machine learning systems are regularly built using big data sets, the discussions surrounding data ethics are often intertwined with those in the ethics of artificial intelligence.^[2] More recently, issues of big data ethics have also been researched in relation with other areas of technology and science ethics, including ethics in mathematics and engineering ethics, as many areas of applied mathematics and engineering use increasingly large data sets.