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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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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. |
format | Online Article Text |
id | pubmed-9552145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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