Publications & Documents

This paper discusses five innovation policy imperatives critical to achieving green and digital transitions: coordinated government, stakeholder engagement, policy agility and experimentation, directionality and support for breakthrough innovation. The paper provides policy examples from Germany, based on the OECD Review of Innovation Policy: Germany , and other countries to illustrate in what ways countries have addressed these imperatives. Overall, the quality and scale of these policy responses need to increase if transitions are to succeed. Open questions for future policy research are also highlighted.

People with disability face persisting difficulties in the labour market. There are concerns that AI, if managed poorly, could further exacerbate these challenges. Yet, AI also has the potential to create more inclusive and accommodating environments and might help remove some of the barriers faced by people with disability in the labour market. Building on interviews with more than 70 stakeholders, this report explores the potential of AI to foster employment for people with disability, accounting for both the transformative possibilities of AI-powered solutions and the risks attached to the increased use of AI for people with disability. It also identifies obstacles hindering the use of AI and discusses what governments could do to avoid the risks and seize the opportunities of using AI to support people with disability in the labour market.

This document provides an integrated view on income-based tax incentives for R&D and innovation. It brings together the latest evidence on the adoption, design, generosity, cost and take-up of income-based tax incentives, and gives new insights into both the long-term and short-term trends in the take-up of income-based tax incentives by business and their cost to governments, including role of policy design changes. Furthermore, the report explores the scope for developing indicators that provide a more complete picture of the value of expenditure- and income-based tax relief for R&D and innovation in the OECD area and beyond.

This paper resents a measurement framework aiming to support the collection of comprehensive and internationally comparable quantitative and qualitative information on governmental innovation support programmes and instruments. It proposes a taxonomic system with definitions, classifications and reporting conventions aligned with OECD and other international standards. The framework is intended to support future OECD measurement efforts in this area and the analysis of innovation support portfolios within and across countries.

This paper examines the experiences of self-employed online freelancers working on digital labour platforms during the COVID-19 pandemic. It is based on interviews with freelancers and platform managers and experts in Belgium, France, Italy, the Netherlands and Poland. Their experiences during COVID-19 reveal issues of asymmetric power vis-à-vis platforms. Notably, they reported lack of transparency and certainty in their contracts with platforms, lack of power in negotiating with clients, and limited ability to engage with clients on other platforms. In addition, they often experienced difficulties in accessing government temporary supports for businesses during the pandemic. The paper puts forward policy recommendations to address these issues.

This report outlines a new methodology and provides a first exploratory analysis of technologies and applications that are at the core of recent advances in AI. Using AI-related keywords and technology classes, the study identifies AI-related patents protected in the United States in 2000-18. Among those, 'core' AI patents are selected based on their counts of AI-related forward citations. The analysis finds that, compared to other (AI and non-AI) patents, they are more original and general, and tend to be broader in technological scope. Technologies related to general AI, robotics, computer/image vision and recognition/detection are consistently listed among core AI patents, with autonomous driving and deep learning having recently become more prominent. Finally, core AI patents tend to spur innovation across AI-related domains, although some technologies – likely AI applications, such as autonomous driving or robotics – appear to increasingly contribute to developments in their own field.

This paper examines the nature and evolution of data localisation measures and their impact on business activity. It highlights that data localisation measures are growing and increasingly restrictive. By early 2023, 100 such measures were in place across 40 countries, with more than two-thirds combining local storage requirements with flow prohibition, the most restrictive form of data localisation. Insights gained from businesses operating in the e-payments, cloud computing, and air travel sectors suggest that data localisation can have unintended consequences. It not only increases operating costs, with implications for downstream users, but can also lead to increased vulnerabilities to fraud and cybersecurity risks, and reduced resilience to unexpected shocks. While international regulatory efforts have largely taken place through regional trade agreements (RTAs), this paper calls for continued monitoring of the regulatory environment with a view to informing efforts to agree on global rules that take into account legitimate public policy objectives while avoiding excessive fragmentation, especially through discussion at the WTO under the Joint Initiative on e-commerce.

The OECD AI Principles call for AI actors to be accountable for the proper functioning of their AI systems in accordance with their role, context, and ability to act. Likewise, the OECD Guidelines for Multinational Enterprises aim to minimise adverse impacts that may be associated with an enterprise’s operations, products and services. To develop ‘trustworthy’ and ‘responsible’ AI systems, there is a need to identify and manage AI risks. As calls for the development of accountability mechanisms and risk management frameworks continue to grow, interoperability would enhance efficiency and reduce enforcement and compliance costs. This report provides an analysis of the commonalities of AI risk management frameworks. It demonstrates that, while some elements may sometimes differ, all the risk management frameworks analysed follow a similar and sometimes functionally equivalent risk management process.