Regulatory sandboxes
S. Ranchordas; V. Vinci (2024)
Regulatory sandboxes and innovation-friendly regulation: between collaboration and capture
Regulatory sandboxes, controlled regulatory environments for the testing of novel products or processes, have garnered an increasing amount of attention over the last decade. More recently, regulatory sandboxes have been presented as innovation-friendly instruments. This article contends that fostering responsible innovation through regulatory sandboxes presents significant challenges. First, there is no consensus on what the advancement of innovation entails, how to achieve it, and what the role of regulations and regulatory sandboxes should be in it. Second, there is a lack of clarity regarding the definition and functioning of regulatory sandboxes. Third, there is a risk of regulatory capture due to the close collaboration between regulators and regulatees. Drawing on Italy’s initial experiences with general and sector-specific regulatory sandboxes and existing scholarship on experimental regulatory instruments, this article contributes to the ongoing debate on regulation and innovation by critically examining the interplay between regulatory sandboxes and the promotion of responsible innovation. Furthermore, it explores the impact of regulatory sandboxes on the evolving collaborative dimensions of public law and provides policymakers and regulators with actionable insights for navigating this innovative regulatory tool.
Nicoletta Rangone (2023)
Artificial Intelligence Challenging Core State Functions: A Focus on Law-making and Rule-making
The use of AI in the public sector is emerging around the world and its spread affects the core States functions: the administrative, the judiciary, and the legislative. Nevertheless, a comprehensive approach to AI in the life-cycle of rules - from the proposal of a new rule to its implementation, monitoring and review- is currently lacking in the rich panorama of studies from different disciplines. The analysis shows that AI has the power to play a crucial role in the life-cycle of rules, by performing time-consuming tasks, increasing access to knowledge base, and enhancing the ability of institutions to draft effective rules and to declutter the regulatory stock. However, it is not without risks, ranging from discrimination to challenges to democratic representation. In order to play a role in achieving law effectiveness while limiting the risks, a complementarity between human and AI should be reached both at the level of the AI architecture and ex post. Moreover, an incremental and experimental approach is suggested, as well as the elaboration of a general framework, to be tailored by each regulator to the specific features of its tasks, aimed at setting the rationale, the role, and adequate guardrails to AI in the life-cycle of rules. This agile approach would allow the AI revolution to display its benefits while preventing potential harms or side effects.
Impact assessment
Zachary D. Liscow; Cass R. Sunstein (2023)
Efficiency vs. Welfare in Benefit-Cost Analysis: The Case of Government Funding
In Republican and Democratic administrations, regulatory and funding decisions have both been made with close reference to benefit-cost analysis (BCA). With respect to regulation, there has been a great deal of scholarly discussion of BCA and its limits, but almost no attention has been paid to the role of BCA in government funding. That is a serious gap, not least in connection with climate-related risks, such as wildfire, drought, extreme heat, and flooding. In OMB Circular A-94, the Office of Management and Budget has long required applicants for federal funding to demonstrate that the benefits of their projects would exceed the costs. Under Circular A-94, efficiency-based BCA can produce results that fail to maximize welfare and that are also highly inequitable. The 2023 draft revision of Circular A-94, focused on welfare and equity, reflects an effort to incorporate new academic thinking over the past three decades, which is now—not uncontroversially—being brought directly into policy. At the same time, the new draft Circular A-94 raises fresh questions about how best to promote welfare, and to consider equity, in practice. Pressing issues involve the use of distributional weights in funding decisions and also the use of averages across populations, which might be seen as a form of distributional weighting. More broadly, the trajectory of this benefit-cost guidance, which predates the guidance for regulation and originally covered regulation, helps uncover the logic under which BCA has been operating and deeper challenges and tensions within BCA, in the past and going forward.
Artificial Intelligence and new technologies regulation
Luca Megale (2023)
Il Garante della privacy contro ChatGPT: quale ruolo per le autorità pubbliche nel bilanciare sostegno all’innovazione e tutela dei diritti?
[ITA] I recenti provvedimenti del Garante privacy nei confronti di ChatGPT, un sistema di intelligenza artificiale generativa di proprietà di OpenAI, sollevano riflessioni sul ruolo e la capacità delle autorità pubbliche di supportare l’innovazione tutelando al contempo i cittadini. Gli interventi del Garante mettono in luce l’impatto sull’attuazione amministrativa di una regolazione obsoleta - il Regolamento europeo generale sulla protezione dei dati - che contribuisce all’ineffettività dei provvedimenti rispetto agli obiettivi perseguiti. Neppure è risolutiva l’impostazione molto poco flessibile della proposta di Regolamento europeo sull’IA, laddove è invece auspicabile un mutamento del paradigma regolatorio alla base dell’intervento pubblico. -- [ENG] The recent actions taken by the Italian Data Protection Authority against ChatGPT, a generative artificial intelligence system owned by OpenAI, prompt reflections on the role and ability of public authorities to support innovation while simultaneously protecting citizens. The interven- tions by the Privacy Authority shed light on the impact of an outdated regulatory framework, the European General Data Protection Regulation, on the regulatory delivery, thereby impeding the effectiveness of these measures in achieving their intended goals. Furthermore, the proposed European Regulation on Artificial Intelligence, with its rigid approach, fails to provide a definitive solution, as there is a need for ashift in the regulatory paradigm underlying public intervention.