Rarely a week passes without announcements that artificial intelligence (AI) has achieved new capabilities. Since the arrival of generative AI, ChatGPT and subsequent large language models – after many of the contributions to this book were written - discussion of AI’s proliferating uses and their implications is increasingly visible in mainstream media. The economic, business, labour market and societal ramifications of AI now occupy the attention of firms, professional bodies, governmental and non-governmental organisations. Indeed, most governments in OECD countries have national AI strategies.

In late 2019 the OECD concluded an agreement with the Fondation IPSEN, which would provide financial support to work on artificial intelligence (AI) and the productivity of science. The context was one in which some scholars had argued that the productivity of science may be stagnating, or even in decline. One aim of the project was to update and significantly expand previous work on AI in science conducted under the aegis of the Committee on Scientific and Technological Policy (CSTP). This prior work included a chapter in the 2018 edition of the OECD Science, Technology and Innovation Outlook, titled “Artificial intelligence and machine learning in science”. A session on the growing importance of AI in science was also organised on 23 February 2022 the second OECD AI WIPS Conference.

Accelerating the productivity of research could be the most economically and socially valuable of all the uses of artificial intelligence (AI). While AI is penetrating all domains and stages of science, its full potential is far from realised. Policy makers and actors across research systems can do much to accelerate and deepen the uptake of AI in science, magnifying its positive contributions to research. This will support the ability of OECD countries to grow, innovate and address global challenges, from climate change to new contagions.

This book addresses the current and emerging roles of artificial intelligence (AI) in science. Accelerating the productivity of research could be the most economically and socially valuable of all AI’s uses. AI and its various subdisciplines are pervading every field and stage of the scientific process. Advances in AI have led to an outpouring of creative uses in research. However, AI’s potential contribution to science is far from realised, and the impact of some widely hailed achievements may be less than is generally thought. AI, for instance, contributed little to research and treatment during the COVID-19 pandemic. Moreover, policy makers and other actors in research systems can do much to speed and broaden the uptake of AI in science, and to magnify its positive contributions to science and society.