Big Data Ethics

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 or personally identifying information (PII). Big data describes large amounts 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. At closer inspection, datasets often reveal details that are not superficially visible, as in this case where corneal reflections on the eye of the photographed person provide information about bystanders, including the photographer. Data ethics considers the implications. 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. In contrast, big data ethics concerns 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. 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. ______________________________________________________________________________________________________________________________

0:07 Data ethics is concerned with the following principles: 

Ownership – Individuals own their personal data.

Transaction transparency – If an individual's personal data is used, they should have transparent access to the algorithm design used to generate aggregate data sets. 

Consent – If an individual or legal entity would like to use personal data, one needs informed and explicitly expressed consent of what personal data moves to whom, when, and for what purpose from the owner of the data.

Privacy – If data transactions occur all reasonable effort needs to be made to preserve privacy.

Currency – Individuals should be aware of financial transactions resulting from the use of their personal data and the scale of these transactions.

Openness – Aggregate data sets should be freely available.