Privacy Discrimination: What it is and why it matters

dc.contributor.authorHillebrand, Luis
dc.contributor.authorHermes, Sebastian
dc.contributor.authorBöhm, Markus
dc.date.accessioned2021-12-24T18:04:35Z
dc.date.available2021-12-24T18:04:35Z
dc.date.issued2022-01-04
dc.description.abstractWe argue that online companies are able to exploit users’ varying levels of privacy needs. We show that by employing data analytics methods on a comparatively small amount of data it is possible to predict how high information privacy concerns of specific users are. We argue that online companies might be able to introduce “privacy discrimination”, in the sense that they might apply varying levels of privacy protection to users, based on their privacy concerns. Users indifferent about privacy could be presented with limited privacy options, adjusted terms and conditions or might be driven to disclose more personal information.
dc.format.extent10 pages
dc.identifier.doihttps://doi.org/10.24251/HICSS.2022.606
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79943
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectThe Dark Sides of AI
dc.subjectartificial intelligence
dc.subjectprivacy
dc.subjectprivacy concerns
dc.subjectprivacy discrimination
dc.titlePrivacy Discrimination: What it is and why it matters
dc.type.dcmitext

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