An authentic self : Big Data and passive digital footprints

Williams, Lynne and Pennington, Diane (2018) An authentic self : Big Data and passive digital footprints. In: International Symposium on Human Aspects of Information Security & Assurance (HAISA 2018), 2018-08-29 - 2018-08-31.

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    Abstract

    The ability to allow users to create online communities of interest and to share a variety of personal information, collectively referred to as social media, is gradually being built into an expanding range of applications. Some of these applications, such as computer operating systems, were not originally intended to collect information from the user. Thus, users may not be aware that their digital information is being collected. Devices such as smart televisions, smart cars, and even smart grids, are now collecting massive quantities of user data without the user’s knowledge. Users of social media, and the internet in general, leave fragments of their activities and intentions behind them across an increasing range of technologies. These fragments collectively and passively create a hidden identity built up from metadata of which the user is mostly unaware. Given that the user builds this hidden identity during the normal course of their day, without editing elements that the user may not wish to share with others, might the passive digital footprint more accurately reveal the individual's genuine or authentic self than the individual realises? We propose that an aggregated, passively collected digital portrait of a user's unconscious but connected activities may reveal a more genuine view of that person's self than would be deduced from sources over which the user has conscious control. This more accurate and potentially revealing portrait of the individual requires a review of how privacy has been classically defined in both legal as well as ethical constructs.