Aufsatz(elektronisch)1. Dezember 2020

Personalized Unfair Terms Control: EU Law Meets Innovative US Doctrines

In: European Review of Private Law, Band 28, Heft 6, S. 1249-1272

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Abstract

According to part of the US scholarship, the use of big data and prediction algorithms could entail a paradigmatic change in contract law: No longer would one have general and abstract legal norms, but rather granular and personalized ones, customized on the needs and features of the contracting parties. This shift to a law tailored to specific individuals could affect both default and mandatory rules and provide for a more efficient and just legal system. The argument goes that such a flexible and technology-driven regulation is also capable of addressing the issue of unfair personalized pricing schemes applied by businesses in online transactions. The present contribution adopts a futuristic approach and investigates whether these doctrinal proposals could possibly pave the way for an amendment of the Directive 93/13 on unfair terms in consumer contracts. In doing so, the main elements of the unfair terms control are highlighted, together with their link with national default rules, which serve both as a benchmark for the assessment of the unfair character of the clause and as gap-fillers. Based on a comparison with the findings of US scholars, it then explores how the unfair terms control may change in order to reduce cross-subsidies to a minimum and tackle discriminatory pricing schemes. Finally, this article elaborates further on how the modifications could be implemented within a new enforcement mechanism, using a technology that would also cover so-called smart contracts.
personalization, unfair terms control, big data, consumer contracts. Motsclés: Personnalisation, Contrôle de clauses abusives, Grandes bases de données, Contrats conclus avec les consommateurs Schlüsselwörter: Personalisierung, Kontrolle missbräuchlicher Klauseln, Big Data, Verbraucherverträge

Sprachen

Englisch

Verlag

Kluwer Law International BV

ISSN: 0928-9801

DOI

10.54648/erpl2020075

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