Publications

The Recommendation aims at further strengthening regulatory governance by helping to update and enhance relevant instruments, processes, and institutions. More precisely, it seeks to provide a conceptual framework and relevant guidance for using and adapting regulatory policy and governance in the face of the regulatory challenges and opportunities arising from innovation.

Artificial Intelligence (AI) is a peculiar case of General Purpose Technology that differs from other examples in history because it embeds specific uncertainties or ambiguous character that may lead to a number of risks when used to support transformative solutions in the public sector. AI has extremely powerful and, in many cases, disruptive effects on the internal management, decision-making and service provision processes of public administration. Over the past few years, the European Union and its Member States have designed regulatory policies and initiatives to mitigate the AI risks and make its opportunities a reality for national, regional and local government institutions. ‘AI Watch’ is one of these initiatives which has, among its goals, the monitoring of European Union’s industrial, technological, and research capacity in AI and the development of an analytical framework of the impact potential of AI in the public sector. This report, in particular, follows a previous landscaping study and collection of European cases, which was delivered in 2020. This document first introduces the concept of AI appropriation in government, seen as a sequence of two logically distinct phases, respectively named adoption and implementation of related technologies in public services and processes. Then, it analyses the situation of AI governance in the US and China and contrasts it to an emerging, truly European model, rooted in a systemic vision and with an emphasis on the revitalised role of the member states in the EU integration process, Next, it points out some critical challenges to AI implementation in the EU public sector, including: the generation of a critical mass of public investments, the availability of widely shared and suitable datasets, the improvement of AI literacy and skills in the involved staff, and the threats associated with the legitimacy of decisions taken by AI algorithms alone. Finally, it draws a set of common actions for EU decision-makers willing to undertake the systemic approach to AI governance through a more advanced equilibrium between AI promotion and regulation. The three main recommendations of this work include a more robust integration of AI with data policies, facing the issue of so-called “explainability of AI” (XAI), and broadening the current perspectives of both Pre-Commercial Procurement (PCP) and Public Procurement of Innovation (PPI) at the service of smart AI purchasing by the EU public administration. These recommendations will represent the baseline for a generic implementation roadmap for enhancing the use and impact of AI in the European public sector.

Digital platforms have strengthened their power more and more by collecting and exploiting data processed through algorithms. Economic and social interactions are increasingly shaped by the technology and software. Such a reliance on digital technologies has brought about the tendency of private subjects (but also of public institutions) to replace traditional norms and rules with regulations based on the code (code is law). From this perspective digital giants are no longer market participants. Rather they are market makers and exert regulatory control over the terms which define the positions of commercial and final users. Moreover they aspire to displace more governmental and public roles over time, performing functions and tasks normally vested in public authorities such as judicial bodies and courts. This shift in power towards private actors has led to an expanding privatization in the field of individuals’ rights as well. Algorithms are replacing the traditional functions of law embedding private values and interests in the technology. They represent the key of digital platforms’ power. Therefore regulators should ‘capture’ the algorithm to steer its effects and thanks to the technology be able to introduce regulatory principles into the design of the digital code.

This report looks at how data analysis techniques and information management tools can help make regulatory inspections more efficient through better risk analysis, targeting and co-ordination. It is based mainly on work conducted by the OECD in Italy (funded by EC DG REFORM) to pilot the use of machine learning techniques and data-driven analysis for risk assessment and to improve information systems integration. The pilots, undertaken in the regions of Campania, Lombardy and Trentino,, cover several regulatory domains – food safety, occupational safety, and environment. They show how better use and management of data can improve inspection systems even within a relatively short timeframe. The approach is based on improving the identification and rating of risk factors, so as to focus regulatory efforts on those businesses or establishments with the highest risks. This report was approved by the Regulatory Policy Committee at its 24th Session on 21st April 2021 and prepared for publication by the OECD Secretariat.

Artificial Intelligence has great potential in all areas of our lives, but it also presents risks for fundamental rights and the rule of law. The European Union is trying to create a balanced regulatory framework between the pros and cons of AI. On 21 April 2021 EU published a comprehensive proposal for an AI regulation, which should protect and promote European rights and values, without impeding the technological, industrial, and commercial development of AI. This article aims to give a first analysis of the proposal, focusing on its main positive and negative aspects.

Over the past three decades, cyberspace has gradually become an engine of unsustainable outcomes from an economic, social and environmental perspective. The European Commission has launched several new initiatives, in the attempt to restore public control over cyberspace, remedy the distributional imbalances generated by the rise of large-scale digital platforms, and promote Europe's digital sovereignty. The paper argues that only by embedding rules and values in “code” and preserving openness towards the rest of the world will the EU manage to achieve its desired goals. Current initiatives such as the data strategy, the AI regulation, the Digital Services Act and the European Cloud Federation appear still too sparse and uncoordinated to really deliver on Europe's ambition to lead the world in the sustainable use of technology.