{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:34:34Z","timestamp":1760146474660,"version":"build-2065373602"},"reference-count":18,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T00:00:00Z","timestamp":1731283200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>This paper considers the question of what kind of knowledge is produced by deep learning. Ryle\u2019s concept of knowledge how is examined and is contrasted with knowledge with a rationale. It is then argued that deep neural networks do produce knowledge how, but, because of their opacity, they do not in general, though there may be some special cases to the contrary, produce knowledge with a rationale. It is concluded that the distinction between knowledge how and knowledge with a rationale is a useful one for judging whether a particular application of deep learning AI is appropriate.<\/jats:p>","DOI":"10.3390\/info15110720","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T06:28:32Z","timestamp":1731392912000},"page":"720","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning and Knowledge"],"prefix":"10.3390","volume":"15","author":[{"given":"Donald","family":"Gillies","sequence":"first","affiliation":[{"name":"Department of Science and Technology Studies, University College London, London WC1E 6BT, UK"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sejnowski, T.J. (2018). The Deep Learning Revolution, The MIT Press.","DOI":"10.7551\/mitpress\/11474.001.0001"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Otsuka, J. (2023). Thinking About Statistics. The Philosophical Foundations, Routledge.","DOI":"10.4324\/9781003319061"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/aristotelian\/46.1.1","article-title":"Knowing How and Knowing That","volume":"46","author":"Ryle","year":"1945\u20131946","journal-title":"Proc. Aristot. Soc."},{"key":"ref_4","unstructured":"Ryle, G. (1960). The Concept of Mind, Hutchinson."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Gillies, D. (1996). Artificial Intelligence and Scientific Method 2018, Oxford University Press.","DOI":"10.1093\/oso\/9780198751588.001.0001"},{"key":"ref_6","unstructured":"Leibniz, G.W. (1961). New Essays on the Human Understanding, Dent. English Translation by Mary Morris of Selections in Leibniz: Philosophical Writings."},{"key":"ref_7","unstructured":"Leibniz, G.W. (1961). The Monadology, Dent. English Translation by Mary Morris in Leibniz: Philosophical Writings 1714."},{"key":"ref_8","unstructured":"Popper, K.R. (1972). Objective Knowledge. An Evolutionary Approach, Oxford University Press."},{"key":"ref_9","unstructured":"Anderson, C. (2008). The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. Wired Mag., 16."},{"key":"ref_10","first-page":"45","article-title":"Is there a Science of Healthy Eating?","volume":"7","author":"Gillies","year":"2023","journal-title":"MEFISTO. J. Med. Philos. Hist."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"226","DOI":"10.5840\/monist198568225","article-title":"Knowledge and Intellectual Virtue","volume":"68","author":"Sosa","year":"1985","journal-title":"Monist"},{"key":"ref_12","first-page":"1","article-title":"ImageNet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ribeiro, M.T., Singh, S., and Guestrin, C. (2016, January 13\u201317). \u201cWhy should I trust you?\u201d Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939778"},{"key":"ref_14","unstructured":"Chollet, F. (2017). Deep Learning with Python, Manning."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Metz, C. (2021). Genius Makers: The Mavericks Who Brought AI to Google, Facebook and the World, Penguin. Penguin Edition.","DOI":"10.56315\/PSCF9-22Metz"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1086\/714960","article-title":"Black Boxes or Unflattering Mirrors? Comparative Bias in the Science of Machine Behaviour","volume":"74","author":"Buckner","year":"2023","journal-title":"Br. J. Philos. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/srep26094","article-title":"Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records","volume":"6","author":"Miotto","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1093\/bjps\/axz035","article-title":"Understanding from Machine Learning Models","volume":"73","author":"Sullivan","year":"2022","journal-title":"Br. J. Philos. Sci."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/11\/720\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:29:51Z","timestamp":1760113791000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/15\/11\/720"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,11]]},"references-count":18,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["info15110720"],"URL":"https:\/\/doi.org\/10.3390\/info15110720","relation":{},"ISSN":["2078-2489"],"issn-type":[{"type":"electronic","value":"2078-2489"}],"subject":[],"published":{"date-parts":[[2024,11,11]]}}}