Algorithmic Disclosure Rules

Artificial intelligence and Law (2022)

44 Pages Posted: 7 Oct 2020 Last revised: 20 Oct 2021

See all articles by Fabiana Di Porto

Fabiana Di Porto

University of Salento ; Luiss Guido Carli University; Law Faculty, Hebrew University

Date Written: September 19, 2021

Abstract

During the past decade, a small but rapidly growing number of Law&Tech scholars have been applying algorithmic methods in their legal research. This Article does it too, for the sake of saving disclosure regulation failure: a normative strategy that has long been considered dead by legal scholars, but conspicuously abused by rule-makers.
Existing proposals to revive disclosure duties, however, either focus on the industry policies (e.g. seeking to reduce consumers' costs of reading) or on rulemaking (e.g. by simplifying linguistic intricacies). But failure may well depend on both. Therefore, this Article develops a `comprehensive approach', suggesting to use computational tools to cope with linguistic and behavioral failures at both the enactment and implementation phases of disclosure duties, thus filling a void in the Law&Tech scholarship. Specifically, it outlines how algorithmic tools can be used in a holistic manner to address the many failures of disclosures from the rulemaking in parliament to consumer screens.
It suggests a multi-layered design where lawmakers deploy three tools in order to produce optimal disclosure rules: machine learning (ML), natural language processing (NLP), and behavioral experimentation through regulatory sandboxes. To clarify how and why these tasks should be performed, disclosures in the contexts of online contract terms and privacy online are taken as examples.
Because algorithmic rulemaking is frequently met with well-justified skepticism, problems of its compatibility with legitimacy, efficacy and proportionality are also discussed.

Keywords: Disclosure Regulation, Regulatory Failure, Consumers, Law And Technology, Information Duties, Machine learning, Algorithms, Natural Language Processing, Regulatory Sandboxes, Knowledge Graph, Due Process, Self-Implementation I

JEL Classification: K10, K20

Suggested Citation

Di Porto, Fabiana, Algorithmic Disclosure Rules (September 19, 2021). Artificial intelligence and Law (2022), Available at SSRN: https://ssrn.com/abstract=3705967 or http://dx.doi.org/10.2139/ssrn.3705967

Fabiana Di Porto (Contact Author)

University of Salento ( email )

Via per Monteroni
Lecce, Lecce 73100
Italy

Luiss Guido Carli University

Viale Romania
Rome, Roma 00100
Italy

Law Faculty, Hebrew University ( email )

Mount Scopus
Mount Scopus, IL 91905
Israel

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