多学科方法
计算机科学
功能(生物学)
透视图(图形)
领域(数学)
甲骨文公司
数据科学
人工智能
管理科学
工程类
数学
社会学
社会科学
软件工程
进化生物学
纯数学
生物
作者
Mario Krenn,Robert Pollice,Si Yue Guo,Matteo Aldeghi,Alba Cervera-Lierta,Pascal Friederich,Gabriel dos Passos Gomes,Florian Häse,Adrián Jinich,AkshatKumar Nigam,Zhenpeng Yao,Alán Aspuru‐Guzik
标识
DOI:10.1038/s42254-022-00518-3
摘要
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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