dc.contributor.author | HACKER, Philipp | |
dc.date.accessioned | 2018-11-28T13:13:40Z | |
dc.date.available | 2018-11-28T13:13:40Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | International data privacy law, 2017, Vol. 7, No. 4, pp. 266-286 | |
dc.identifier.issn | 2044-3994 | |
dc.identifier.issn | 2044-4001 | EN |
dc.identifier.uri | https://hdl.handle.net/1814/59685 | |
dc.description | Published: 01 September 2017 | |
dc.description.abstract | Personal 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.publisher | Oxford University Press | en |
dc.relation.ispartof | International data privacy law | |
dc.title | Personal data, exploitative contracts, and algorithmic fairness : autonomous vehicles meet the internet of things | |
dc.type | Article | |
dc.identifier.doi | 10.1093/idpl/ipx014 | |
dc.identifier.volume | 7 | |
dc.identifier.startpage | 266 | |
dc.identifier.endpage | 286 | |
eui.subscribe.skip | true | |
dc.identifier.issue | 4 | |