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Artificial Intelligence in Science

Challenges, Opportunities and the Future of Research

image of Artificial Intelligence in Science

The rapid advances of artificial intelligence (AI) in recent years have led to numerous creative applications in science. Accelerating the productivity of science could be the most economically and socially valuable of all the uses of AI. Utilising AI to accelerate scientific productivity will support the ability of OECD countries to grow, innovate and meet global challenges, from climate change to new contagions.

This publication is aimed at a broad readership, including policy makers, the public, and stakeholders in all areas of science. It is written in non-technical language and gathers the perspectives of prominent researchers and practitioners. The book examines various topics, including the current, emerging, and potential future uses of AI in science, where progress is needed to better serve scientific advancements, and changes in scientific productivity.

Additionally, it explores measures to expedite the integration of AI into research in developing countries.

A distinctive contribution is the book’s examination of policies for AI in science. Policy makers and actors across research systems can do much to deepen AI’s use in science, magnifying its positive effects, while adapting to the fast-changing implications of AI for research governance.

English

What can artificial intelligence do for physics?

In recent years, governments all over the world have launched research initiatives for artificial intelligence (AI). These range from Australia, Canada and the United States to the People’s Republic of China, Denmark, the European Commission, France, Germany and the United Kingdom. Everyone suddenly has a strategy for “AI made in”, whatever happens to be their own part of the planet. In the coming decades, it is likely that tens of billions of public and private dollars, euros and Yuan renminbi will flow into the field. However, ask physicists what they think of AI, and they will probably be surprised. For them, AI was trendy in the 1980s. They prefer to call it “machine learning” and pride themselves on having used that term for decades. This essay summarises different applications for which AI physicists use AI, classifying them roughly into data analysis, modelling and model analysis.

English

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