Personal data, exploitative contracts, and algorithmic fairness : autonomous vehicles meet the internet of things
International data privacy law, 2017, Vol. 7, No. 4, pp. 266-286
HACKER, Philipp, Personal data, exploitative contracts, and algorithmic fairness : autonomous vehicles meet the internet of things, International data privacy law, 2017, Vol. 7, No. 4, pp. 266-286 - https://hdl.handle.net/1814/59685
Retrieved from Cadmus, EUI Research Repository
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.
Published: 01 September 2017
Cadmus permanent link: https://hdl.handle.net/1814/59685
Full-text via DOI: 10.1093/idpl/ipx014
ISSN: 2044-3994; 2044-4001
Publisher: Oxford University Press
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