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dc.contributor.authorHACKER, Philipp
dc.date.accessioned2018-11-28T13:13:40Z
dc.date.available2018-11-28T13:13:40Z
dc.date.issued2017
dc.identifier.citationInternational data privacy law, 2017, Vol. 7, No. 4, pp. 266-286
dc.identifier.issn2044-3994
dc.identifier.issn2044-4001EN
dc.identifier.urihttp://hdl.handle.net/1814/59685
dc.descriptionPublished: 01 September 2017
dc.description.abstractPersonal data harvested in the Internet of Things not only promises to be particularly valuable, but also particularly privacy-sensitive.Analysed with the power of specialized Artificial Intelligence, such data allows for potentially beneficial personalization of goods and services; however, it also facilitates data-driven exploitative contracting.For example, data collected by autonomous and connected vehicles enables innovative driving and safety features in a personalized version of autonomous driving; but it also invites exploitative contracts tailored to profit from the vulner-abilities of drivers and passengers.Current EU data protection, contract, and tort law arguably fail to rein in data-driven exploitative contracts.Three novel interventions aiming to infuse greater fairness into the code of the digital economy are discussed: (i) mandatory 'data safe' alternatives; (ii) personalized data protection; and (iii) procedural rules on algorithmic fairness.
dc.publisherOxford University Pressen
dc.relation.ispartofInternational data privacy law
dc.titlePersonal data, exploitative contracts, and algorithmic fairness : autonomous vehicles meet the internet of things
dc.typeArticle
dc.identifier.doi10.1093/idpl/ipx014
dc.identifier.volume7
dc.identifier.startpage266
dc.identifier.endpage286
eui.subscribe.skiptrue
dc.identifier.issue4


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