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On scientific understanding with artificial intelligence

An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend...

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Autores principales: Krenn, Mario, Pollice, Robert, Guo, Si Yue, Aldeghi, Matteo, Cervera-Lierta, Alba, Friederich, Pascal, dos Passos Gomes, Gabriel, Häse, Florian, Jinich, Adrian, Nigam, AkshatKumar, Yao, Zhenpeng, Aspuru-Guzik, Alán
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552145/
https://www.ncbi.nlm.nih.gov/pubmed/36247217
http://dx.doi.org/10.1038/s42254-022-00518-3
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author Krenn, Mario
Pollice, Robert
Guo, Si Yue
Aldeghi, Matteo
Cervera-Lierta, Alba
Friederich, Pascal
dos Passos Gomes, Gabriel
Häse, Florian
Jinich, Adrian
Nigam, AkshatKumar
Yao, Zhenpeng
Aspuru-Guzik, Alán
author_facet Krenn, Mario
Pollice, Robert
Guo, Si Yue
Aldeghi, Matteo
Cervera-Lierta, Alba
Friederich, Pascal
dos Passos Gomes, Gabriel
Häse, Florian
Jinich, Adrian
Nigam, AkshatKumar
Yao, Zhenpeng
Aspuru-Guzik, Alán
author_sort Krenn, Mario
collection PubMed
description An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions. This is scientific understanding, one of the main aims of science. With the increase in the available computational power and advances in artificial intelligence, a natural question arises: how can advanced computational systems, and specifically artificial intelligence, contribute to new scientific understanding or gain it autonomously? Trying to answer this question, we adopted a definition of ‘scientific understanding’ from the philosophy of science that enabled us to overview the scattered literature on the topic and, combined with dozens of anecdotes from scientists, map out three dimensions of computer-assisted scientific understanding. For each dimension, we review the existing state of the art and discuss future developments. We hope that this Perspective will inspire and focus research directions in this multidisciplinary emerging field.
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spelling pubmed-95521452022-10-11 On scientific understanding with artificial intelligence Krenn, Mario Pollice, Robert Guo, Si Yue Aldeghi, Matteo Cervera-Lierta, Alba Friederich, Pascal dos Passos Gomes, Gabriel Häse, Florian Jinich, Adrian Nigam, AkshatKumar Yao, Zhenpeng Aspuru-Guzik, Alán Nat Rev Phys Perspective An oracle that correctly predicts the outcome of every particle physics experiment, the products of every possible chemical reaction or the function of every protein would revolutionize science and technology. However, scientists would not be entirely satisfied because they would want to comprehend how the oracle made these predictions. This is scientific understanding, one of the main aims of science. With the increase in the available computational power and advances in artificial intelligence, a natural question arises: how can advanced computational systems, and specifically artificial intelligence, contribute to new scientific understanding or gain it autonomously? Trying to answer this question, we adopted a definition of ‘scientific understanding’ from the philosophy of science that enabled us to overview the scattered literature on the topic and, combined with dozens of anecdotes from scientists, map out three dimensions of computer-assisted scientific understanding. For each dimension, we review the existing state of the art and discuss future developments. We hope that this Perspective will inspire and focus research directions in this multidisciplinary emerging field. Nature Publishing Group UK 2022-10-11 2022 /pmc/articles/PMC9552145/ /pubmed/36247217 http://dx.doi.org/10.1038/s42254-022-00518-3 Text en © Springer Nature Limited 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Perspective
Krenn, Mario
Pollice, Robert
Guo, Si Yue
Aldeghi, Matteo
Cervera-Lierta, Alba
Friederich, Pascal
dos Passos Gomes, Gabriel
Häse, Florian
Jinich, Adrian
Nigam, AkshatKumar
Yao, Zhenpeng
Aspuru-Guzik, Alán
On scientific understanding with artificial intelligence
title On scientific understanding with artificial intelligence
title_full On scientific understanding with artificial intelligence
title_fullStr On scientific understanding with artificial intelligence
title_full_unstemmed On scientific understanding with artificial intelligence
title_short On scientific understanding with artificial intelligence
title_sort on scientific understanding with artificial intelligence
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9552145/
https://www.ncbi.nlm.nih.gov/pubmed/36247217
http://dx.doi.org/10.1038/s42254-022-00518-3
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