AI for Scientific Discovery

Janna Hastings (University College London, London, UK)

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English

CRC Press
06 June 2023

Robotics; Algorithms & data structures; Artificial intelligence

Series: AI for Everything

AI for Scientific Discovery provides an accessible introduction to the wide-ranging applications of artificial intelligence (AI) technologies in scientific research and discovery across the full breadth of scientific disciplines. AI technologies support discovery science in multiple 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 and supporting the management of large-scale data and knowledge resources so that they can be shared and 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 and 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 number-crunching and statistical inference at a massive scale that AI technologies are best at.

By: Janna Hastings (University College London London UK)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 198mm, Width: 129mm,
Weight: 520g
ISBN: 9781032124841
ISBN 10: 1032124849
Series: AI for Everything
Pages: 120
Publication Date: 06 June 2023
Audience: College/higher education , Professional and scholarly , Professional and scholarly , Primary , Undergraduate
Format: Paperback
Publisher's Status: Active

Janna Hastings is a computer scientist with more than a decade of experience 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 for AI for Scientific Discovery

"“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."