AI for Scientific Discovery  book cover
1st Edition

AI for Scientific Discovery




  • Available for pre-order on May 16, 2023. Item will ship after June 6, 2023
ISBN 9781032124841
June 6, 2023 Forthcoming by CRC Press
112 Pages 5 B/W Illustrations

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USD $29.95

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Book Description

AI for Scientific Discovery provides an accessible introduction to the wide-ranging applications of artificial intelligence technologies in scientific research and discovery across the full breadth of scientific disciplines. Artificial intelligence technologies support discovery science in multiple different ways. They support literature management and synthesis, allowing the wealth of what has already been discovered and reported on to be integrated and easily accessed. They play a central role in data analysis and interpretation – in the context of what is called ‘data science’. AI is also helping to combat the reproducibility crisis in scientific research, by underpinning the discovery process with AI-enabled standards and pipelines, support the management of large-scale data and knowledge resources so that they can be shared, integrated and serve as a background ‘knowledge ecosystem’ into which new discoveries can be embedded. However, there are limitations to what AI can achieve and its outputs can be biased and confounded thus should not be blindly trusted. The latest generation of hybrid and ‘human-in-the-loop’ AI technologies have as their objective a balance between human inputs and insights and the power of the number-crunching and statistical inference at massive scale that AI technologies are best at.

Table of Contents

1. Introduction: AI and the digital revolution in science. 2. AI for managing scientific literature and evidence. 3. AI for data interpretation. 4. AI for reproducible research. 5. Limitations of AI and strategies for combating bias. 6. Conclusion: AI and the future of scientific discovery.

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Author(s)

Biography

Janna Hastings is a computer scientist with more than a decade of experience in knowledge representation and reasoning across the life, behavioural and social sciences. She is also a data scientist with a PhD in computational biology and extensive experience in bioinformatics, cheminformatics and psychoinformatics. She is currently Assistant Professor of Medical Knowledge and Decision Support at the University of Zurich and Vice-Director of the School of Medicine at the University of St. Gallen. Her current research focuses on bridging the gaps between knowledge and learning to bring AI technologies in medicine closer to the needs and workflows of clinicians and to support truly interdisciplinary and integrative knowledge discovery.

Reviews

“An excellent summary of the state of the art of AI for Scientific Discovery. A concise and informative book covering the main areas of the topic. It is clear the material is very well researched and referenced. AI is placed in context and difficulties such as ethical problems and bias are addressed as well as the exciting new science produced. The writing style is excellent, the abstracts for each chapter are useful, and the text is easy to read.”

--Jeremy Frey, Professor of Physical Chemistry, University of Southampton, UK.

 

"This book is brilliant and contains loads of gems that will be invaluable to scientists and people working in AI."

--Robert West, Professor Emeritus of Health Psychology, University College London.