Publications

The document is a comprehensive framework created by the Central Digital and Data Office for the UK Government, providing guidelines for the adoption and responsible use of generative AI within government and public sector organizations. The framework is organized around ten guiding principles.

The Guidelines offer a comprehensive toolkit for policy- and lawmakers on how to improve their legislative process to tackle contemporary lawmaking challenges head-on and to promote more openness, transparency, accountability, inclusiveness and participation at all stages of the legislative cycle. The Guidelines are an effective instrument to ensure that lawmaking processes and adopted legislation are human rights-compliant, accessible, non-discriminatory, gender-responsive and sensitive to the needs of diverse social groups. The Guidelines also emphasize the fundamental role that non-governmental organizations play throughout the lawmaking process and can serve as an advocacy tool for civil society to ensure that the people affected by legislation are informed about, and have a say in shaping its contents. It is our hope that these Guidelines will be a useful source of information and will provide users with practical, hands-on advice on how to reform their legislative rules and practices in compliance with international human rights and rule of law standards and OSCE commitments, leading to better-quality laws. Their ultimate goal is to empower decision makers to develop legislation that truly serves the people.

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.

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Rather than proposing any single model for AI governance at this stage, the foregoing preliminary recommendations focus on the principles and functions to which any such regime must aspire. Over the coming months, we will consult — individually and in groups — with diverse stakeholders around the world. This includes participation at events tasked with discussing the issues in this report as well as engagement with governments, the private sector, civil society, and research and technical communities. We will also pursue our research, including on risk assessment methodologies and governance interoperability. Case studies will be developed to help think about landing issues identified in the report in specific contexts. We also intend to dive deep into a few areas, including OpenSource, AI and the financial sector, standard setting, intellectual property, human rights, and the future of work by leveraging existing efforts and institutions.

Grand challenges are shaping twenty-first-century politics. Threats connected to health, climate, demographics and welfare are increasingly intruding on the lives of citizens. Still, governments are often found off-guard, and policymakers need strategies grounded in longer-term perspectives. Strategic foresight (SF) helps us to design and shape policies to prepare to withstand shocks, anticipating and adapting to changes. However, as governments work towards embedding SF into their policymaking processes, the empirical evidence suggests that applications are still piecemeal and predominantly limited to the agenda-settings and policy formulation stages. In this article, we argue that to drive anticipatory governance, foresight needs to be applied at all stages of the policy cycle, including in evaluating policies to draw lessons for future interventions. We maintain that considering SF systemically throughout the policymaking cycle, from agenda setting to evaluation, strengthens anticipatory governance.

The Stanford Emerging Technology Review (SETR) is the first product of a major new Stanford technology education initiative for policymakers. The goal is to help both the public and private sectors better understand the technologies poised to transform our world so that the United States can seize opportunities, mitigate risks, and ensure that the American innovation ecosystem continues to thrive.

Il numero di ottobre della Rassegna trimestrale dell'Osservatorio AIR propone analisi sullo sviluppo di diversi strumenti della qualità della regolazione, sia relativamente alla metodologia, sia relativamente alla loro attuazione. Nei primi tre contributi si commentano altrettante recenti analisi OCSE su tre rilevanti strumenti: il test PMI, le consultazioni e le sandboxes. Nei restanti due commenti ci si concentra sull'aspetto attuativo, con un contributo di analisi sullo stato dell'arte dell'AIR e della VIR a livello nazionale (con un commento alla Relazione annuale del DAGL al Parlamento sull'applicazione di AIR e VIR) e sulla sperimentazione che il Friuli-Venezia Giulia ha effettuato in tema di enforcement, relativamente ai controlli nel settore lattiero-caseario.

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.

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.