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Artificial intelligence and machine learning systems, for example, often rely on data-mining algorithms to construct models with little or no human guidance. However, a plethora of patterns are inevitable in large data sets, and computer algorithms have no effective way of assessing whether the patterns they unearth are truly useful or meaningless coincidences. While data mining sometimes discovers useful relationships, the data deluge has caused the number of possible patterns that can be discovered relative to the number that are genuinely useful to grow exponentially\u2014which makes it increasingly likely that what data mining unearths is likely to be fool\u2019s gold.<\/jats:p>","DOI":"10.1177\/0268396220915600","type":"journal-article","created":{"date-parts":[[2020,5,11]],"date-time":"2020-05-11T04:49:37Z","timestamp":1589172577000},"page":"182-194","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":37,"title":["Data mining fool\u2019s gold"],"prefix":"10.1177","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5173-2741","authenticated-orcid":false,"given":"Gary","family":"Smith","sequence":"first","affiliation":[{"name":"Pomona College, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2020,5,11]]},"reference":[{"key":"bibr1-0268396220915600","unstructured":"Alloway T (2019) JPMorgan creates \u201cVolfefe\u201d index to track Trump tweet impact. 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