Publications & Documents

The rapid pace of technological change, coupled with a pressing need for solutions to address grand societal challenges and global crises, heightens the challenge for policy makers to develop science, technology and innovation policies at speed, in situations of high uncertainty and, in some cases, around potentially controversial technology fields. Technology assessment (TA) has a long history of providing decision-makers with timely strategic intelligence on emerging technologies. Current demands are pushing TA to evolve in order to fulfil diverse functions: to illuminate the societal, economic, environmental and other consequences of new technologies; to inform public opinion; and to guide research and development. Drawing on nine case studies, this report analyses the response of TA practices to these changing drivers and demands to support policies for new and emerging technologies. It also identifies a set of principles to guide good contemporary TA practice.

Despite the increasing adoption of income-based tax incentives for R&D and innovation in the OECD area and beyond, evidence on the availability, design, generosity and actual cost of these incentives remains scarce. This report helps fill this gap by documenting government efforts to provide preferential tax treatment of economic outputs of innovation activities. Drawing on the responses of national contact points to the OECD KNOWINTAX surveys carried out in 2020 and 2021, it presents new evidence on the cost (foregone tax revenues) and uptake of income-based-tax incentives by businesses in 2019, and tracks their distribution by firm size and industry and their evolution over the 2000-2019 period.

This report analyses the use of artificial intelligence (AI) in firms across 11 countries. Based on harmonised statistical code (AI diffuse) applied to official firm-level surveys, it finds that the use of AI is prevalent in ICT and Professional Services and more widespread across large – and to some extent across young – firms. AI users tend to be more productive, especially the largest ones. Complementary assets, including ICT skills, high-speed digital infrastructure, and the use of other digital technologies, which are significantly related to the use of AI, appear to play a critical role in the productivity advantages of AI users.

Sociotechnical systems in areas like energy, agrifood and mobility need to transform rapidly to become more sustainable and resilient. Science, technology and innovation (STI) have essential roles in these transformations, but governments must be more ambitious and act with greater urgency in their STI policies to meet these challenges. They should design policy portfolios that enable transformative innovation and new markets to emerge, challenge existing fossil-based systems, and create windows of opportunity for low-carbon technologies to break through. This calls for larger investments but also greater directionality in research and innovation, for example, through mission-oriented policies, to help direct and compress the innovation cycle for low-carbon technologies. International co-operation will be essential, but rising geopolitical tensions, including strategic competition in key emerging technologies, could make this difficult. OECD Science, Technology and Innovation Outlook 2023 explores these and other key issues and trends that present STI with a new operating environment to which it must adapt.

The provision of key health technologies and products such as vaccines and antibiotics is insufficient in purely competitive and volume-based markets, requiring new revenue streams for sustainability. Recent developments in health innovation suggest that innovative collaborative mechanisms can be effective in addressing this issue. In the domains of vaccines and antibiotics, these approaches should incorporate shared research investment, long-term access planning, the provision of manufacturing infrastructure, supply chains, and financial returns. Collaborative approaches such as subscription models could be piloted at the regional level, while other models could be developed to delink innovation, manufacturing, and access from sales volume and revenue. Finally, blended finance instruments from the development field could encourage greater collaboration among established and emerging stakeholders in health innovation. These stakeholders should work together to create, test, access, and implement more collaborative approaches to health innovation to share upfront investments, mitigate risks of failure, and accelerate market access.

The transition to climate neutrality requires cost reductions in existing clean technologies to enable rapid deployment on a large scale, as well as the development of emerging technologies such as green hydrogen. This policy paper argues that science, technology, innovation, and industrial (STI&I) policies focusing on developing and deploying low-carbon technologies are crucial to achieving carbon neutrality. It notes however that the current level of innovation is insufficient to meet the net-zero challenge due to a policy emphasis on deployment rather than research and development (R&D) support. The paper explores the rationale for more ambitious STI&I policies targeted at R&D for climate neutrality and provides policy recommendations for an effective innovation policy for net-zero, including its interaction with the broader climate policy package.

Artificial intelligence (AI) is transforming economies and promising new opportunities for productivity, growth, and resilience. Countries are responding with national AI strategies to capitalise on these transformations. However, no country today has data on, or a targeted plan for, national AI compute capacity. This policy blind-spot may jeopardise domestic economic goals. This report provides the first blueprint for policy makers to help assess and plan for the national AI compute capacity needed to enable productivity gains and capture AI’s full economic potential. It provides guidance for policy makers on how to develop a national AI compute plan along three dimensions: capacity (availability and use), effectiveness (people, policy, innovation, access), and resilience (security, sovereignty, sustainability). The report also defines AI compute, takes stock of indicators, datasets, and proxies for measuring national AI compute capacity, and identifies obstacles to measuring and benchmarking national AI compute capacity across countries.