Artificial Intelligence in Science
Challenges, Opportunities and the Future of Research
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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.
Advancing the productivity of science with citizen science and artificial intelligence
Citizen science is a form of scientific inquiry where members of the public engage in scientific investigations, often in collaboration with, or under the direction of, professional scientists and scientific institutions. It supports scientific research and applied sciences through a wide range of activities and across diverse topics. Thanks to advances in communication and computing technologies, the public can collaboratively participate in new ways in citizen science projects. For example, participants submit observations and samples about the environment via eBird, iNaturalist or the EchidnaCSI project, among other platforms. They also engage on line by transcribing historical documents or classifying photographs, audio and video via platforms such as DigiVol or Zooniverse. In other cases, participants collaboratively solve mathematical problems via the Polymath Project, or play online games via Foldit, to inform medical research. The public disseminates project outcomes as well.
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