Publications | Jean Monnet Chair on Better Regulation

SubCategory

Year

Digital markets

Luca Megale (2021)

Il report dei Dem del Congresso degli U.S.A. sulle Big Tech: una pietra miliare per la riforma del mercato digitale?

Rassegna trimestrale dell’Osservatorio AIR, n. XII-1, Gennaio 2021

Artificial Intelligence and new technologies regulation

Luca Megale (2021)

Regolare l’Intelligenza Artificiale: il differente approccio nel mondo sino alla proposta UE

in Studi Parlamentari e di Politica Costituzionale, anno 54, n. 209, 1 semestre 2021, pp. 137 – 156

International regulatory co-operation

Luca Megale (2021)

Cooperazione regolatoria internazionale: i costi superano i benefici?

Rassegna trimestrale dell’Osservatorio AIR, n. XII-4, Ottobre 2021

Artificial Intelligence and new technologies regulation

Edoardo Chiti,Barbara Marchetti,Nicoletta Rangone (2021)

Rapporto 2/2021 –L’impiego dell’IA nell’attività di Banca d’Italia | BioLaw Journal n. 4/2021

Artificial Intelligence and new technologies regulation

Edoardo Chiti,Barbara Marchetti,Nicoletta Rangone (2021)

Rapporto 1/2021 –L’impiego dell’IA nell’attività di CONSOB, AGCOM e ARERA | BioLaw Journal n. 4/2021

Artificial Intelligence and new technologies regulation

A. Guerra; F. Parisi; D. Pi (2021)

Liability for robots II: an economic analysis

This is the second of two companion papers that discuss accidents caused by robots. In the first paper (Guerra et al., 2021), we presented the novel problems posed by robot accidents, and assessed the related legal approaches and institutional opportunities. In this paper, we build on the previous analysis to consider a novel liability regime, which we refer to as ‘manufacturer residual liability’ rule. This makes operators and victims liable for accidents due to their negligence – hence, incentivizing them to act diligently; and makes manufacturers residually liable for non-negligent accidents – hence, incentivizing them to make optimal investments in R&D for robots' safety. In turn, this rule will bring down the price of safer robots, driving unsafe technology out of the market. Thanks to the percolation effect of residual liability, operators will also be incentivized to adopt optimal activity levels in robots' usage.

Artificial Intelligence and new technologies regulation

A. Guerra; F. Parisi; D. Pi (2021)

Liability for robots I: legal challenges

In robot torts, robots carry out activities that are partially controlled by a human operator. Several legal and economic scholars across the world have argued for the need to rethink legal remedies as we apply them to robot torts. Yet, to date, there exists no general formulation of liability in case of robot accidents, and the proposed solutions differ across jurisdictions. We proceed in our research with a set of two com-panion papers. In this paper, we present the novel problems posed by robot accidents, and assess the legal challenges and institutional prospects that policymakers face in the regulation of robot torts. In the companion paper, we build on the present analysis and use an economic model to propose a new liability regime that blends negligence-based rules and strict manufacturer liability rules to create optimal incentives for robot torts.

Corruption prevention

M. De Benedetto (2021)

Corruption from a Regulatory Perspective

This book seeks to enrich and, in some cases, reverse current ideas on corruption and its prevention. It is a long held belief that sanctions are the best guard against corrupt practise. This innovative work argues that in some cases sanctions paradoxically increase corruption and that controls provide opportunities for corrupt transactions. Instead it suggests that better regulation and responsive enforcement, not sanctions, offer the most effective response to corruption. Taking both a theoretical and applied approach, it examines the question from a global perspective, drawing on in particular a regulatory perspective, to provide a model for tackling corrupt practises.

Artificial Intelligence and new technologies regulation

Fabiana Di Porto (2021)

Algorithmic disclosure rules

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, natural language processing, 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.

Digital markets

F. Di Porto; T. Grote; G. Volpi (2021)

'I See Something You Don't See'. A Computational Analysis of the Digital Services Act and the Digital Markets Act

In its latest proposals, the Digital Markets Act (DMA) and Digital Services Act (DSA), the European Commission puts forward several new obligations for online intermediaries, especially large online platforms and “gatekeepers.” Both are expected to serve as a blueprint for regulation in the United States, where lawmakers have also been investigating competition on digital platforms and new antitrust laws passed the House Judiciary Committee as of June 11, 2021. This Article investigates whether all stakeholder groups share the same understanding and use of the relevant terms and concepts of the DSA and DMA. Leveraging the power of computational text analysis, we find significant differences in the employment of terms like “gatekeepers,” “self-preferencing,” “collusion,” and others in the position papers of the consultation process that informed the drafting of the two latest Commission proposals. Added to that, sentiment analysis shows that in some cases these differences also come with dissimilar attitudes. While this may not be surprising for new concepts such as gatekeepers or self-preferencing, the same is not true for other terms, like “self-regulatory,” which not only is used differently by stakeholders but is also viewed more favorably by medium and big companies and organizations than by small ones. We conclude by sketching out how different computational text analysis tools, could be combined to provide many helpful insights for both rulemakers and legal scholars.

Artificial Intelligence and new technologies regulation

Cary Coglianese (2021)

Regulating New Tech: Problems, Pathways, and People

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. This means that regulatory organizations need to strengthen their own technological capacities; however, they need most of all to build their human capital. Successful regulation of technological innovation rests with top quality people who possess the background and skills needed to understand new technologies and their problems.

Digital markets

Pınar Akman (2021)

Regulating Competition in Digital Platform Markets: A Critical Assessment of the Framework and Approach of the EU Digital Markets Act

The European Union’s Digital Markets Act (DMA) initiative, which is set to introduce ex ante regulatory rules for “gatekeepers” in online platform markets, is one of the most important pieces of legislation to emanate from Brussels in recent decades. It not only has the potential to influence jurisdictions around the world in regulating digital markets, it also has the potential to change the business models of the wealthiest corporations on the planet and how they offer their products and services to their customers. Against that backdrop, this article provides an analysis of the aims of and principles underlying the DMA, the essential components of the DMA, and the core substantive framework, including the scope and structure of the main obligations and the implementation mechanisms envisaged by the DMA. Following this analysis, the article offers a critique of the central components of the DMA, such as its objectives, positioning in comparison to competition law rules, and substantive obligations. The article then provides recommendations and proposes ways in which the DMA – and other legislative initiatives around the world, which may take the DMA as an example – can be significantly improved by, inter alia, adopting a platform-driven substantive framework built upon self-executing, prescriptive obligations.

Artificial Intelligence and new technologies regulation

C. Coglianese; A. Lai (2021)

Antitrust by Algorithm

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful implementation of antitrust by algorithm.

Artificial Intelligence and new technologies regulation

Fabiana Di Porto (2021)

'Algorithmic Disclosure Rules'

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, natural language processing, 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.

Experimental approach to law and regulation

Sofia Ranchordas (2021)

Experimental Regulations and Regulatory Sandboxes: Law without Order?

This article argues that the poor design and implementation of experimental regulations and regulatory sandboxes can have both methodological and legal implications. First, the internal validity of experimental legal regimes is limited because it is unclear whether the verified positive or negative results are the direct result of the experimental intervention or other circumstances. The limited external validity of experimental legal regimes impedes the generalization of the experiment and thus the ability to draw broader conclusions for the regulatory process. Second, experimental legal regimes that are not scientifically sound make a limited contribution to the advancement of evidence-based lawmaking and the rationalization of regulation. Third, methodological deficiencies may result in the violation of legal principles (e.g., legality, legal certainty, equal treatment, proportionality) which require that experimental regulations follow objective, transparent, and predictable standards. This article contributes to existing comparative public law and law and methods literature with an interdisciplinary framework which can help improve the design of experimental regulations and regulatory sandboxes. This article starts with an analysis of the central features, functions, and legal framework of these experimental legal regimes. It does so by focusing on legal scholarship, policy reports, and case law on experimental regulations and regulatory sandboxes from France, United Kingdom, and The Netherlands. While this article is not strictly comparative in its methodology, the three selected jurisdictions illustrate well the different facets of experimental legal regimes. This article draws on social science literature on the methods of field experiments to offer novel methodological insights for a more transparent and objective design of experimental regulations and regulatory sandboxes.