{"title":"了解深度学习的重要性。","authors":"Tim Räz, Claus Beisbart","doi":"10.1007/s10670-022-00605-y","DOIUrl":null,"url":null,"abstract":"<p><p>Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, <i>contra</i> Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan's claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.</p>","PeriodicalId":47741,"journal":{"name":"ERKENNTNIS","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11090801/pdf/","citationCount":"0","resultStr":"{\"title\":\"The Importance of Understanding Deep Learning.\",\"authors\":\"Tim Räz, Claus Beisbart\",\"doi\":\"10.1007/s10670-022-00605-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, <i>contra</i> Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan's claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.</p>\",\"PeriodicalId\":47741,\"journal\":{\"name\":\"ERKENNTNIS\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11090801/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERKENNTNIS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s10670-022-00605-y\",\"RegionNum\":2,\"RegionCategory\":\"哲学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/8/7 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"0\",\"JCRName\":\"PHILOSOPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERKENNTNIS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10670-022-00605-y","RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/8/7 0:00:00","PubModel":"Epub","JCR":"0","JCRName":"PHILOSOPHY","Score":null,"Total":0}
Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, contra Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan's claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.
期刊介绍：
Erkenntnis is a philosophical journal publishing papers committed in one way or another to the philosophical attitude which is signified by the label ''scientific philosophy''. It concentrates on those philosophical fields which are particularly inspired by this attitude, although other topics are welcome as well. These fields are:- Epistemology - Philosophy of science, foundations and methodology of science in general and of natural and human sciences such as physics, biology, psychology, economics, social sciences in particular - Philosophy of mathematics - Logic, philosophy of logic, and all kinds of philosophical logics - Philosophy of language - Ontology, metaphysics, theory of modality - Philosophical psychology, philosophy of mind, neurophilosophy - Practical philosophy, i.e. ethics, philosophy of action, philosophy of law, etc. One of the objectives of Erkenntnis is the provision of a suitable platform for the discussion of controversial issues; another is the provision of timely, competent reviews of important publications in an ever-growing field of research.In recent years, philosophers standing quite outside the pale of analytic philosophy have also paid careful, and indeed most welcome, attention to precision of concept and language, to arguments, and to well-grounded foundations. Erkenntnis provides for them, and for philosophers of all persuasions, a place of meeting, of discussion, and of disputation.Erkenntnis was originally founded in 1930 by Rudolf Carnap and Hans Reichenbach, it was revived in 1975 by Carl G. Hempel, Wolfang Stegmüller, and Wilhelm K. Essler. You can find more information about this in the article “Hempel: The old and the new ‘Erkenntnis’” accessible in the tabs to the right.Today, Erkenntnis is one of the leading journals in philosophy worldwide and attracts first-class authors at all stages of career; from young philosophers at the PhD level up to established academic philosophers and highly renowned senior scholars. We pride ourselves on supplying our authors with substantial referee reports, subject to a turnaround time of about three months until the first decision. The acceptance rate for publications in the journal is presently slightly below 10%.
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