{"title":"机器是彻底的语境主义者吗?","authors":"Ryan M. Nefdt","doi":"10.1111/mila.12429","DOIUrl":null,"url":null,"abstract":"In this article, I describe a novel position on the semantics of artificial intelligence. I present a problem for the current artificial neural networks used in machine learning, specifically with relation to natural language tasks. I then propose that from a metasemantic level, meaning in machines can best be interpreted as radically contextualist. Finally, I consider what this might mean for human-level semantic competence from a comparative perspective.","PeriodicalId":51472,"journal":{"name":"Mind & Language","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Are machines radically contextualist?\",\"authors\":\"Ryan M. Nefdt\",\"doi\":\"10.1111/mila.12429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, I describe a novel position on the semantics of artificial intelligence. I present a problem for the current artificial neural networks used in machine learning, specifically with relation to natural language tasks. I then propose that from a metasemantic level, meaning in machines can best be interpreted as radically contextualist. Finally, I consider what this might mean for human-level semantic competence from a comparative perspective.\",\"PeriodicalId\":51472,\"journal\":{\"name\":\"Mind & Language\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2022-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mind & Language\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1111/mila.12429\",\"RegionNum\":3,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mind & Language","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1111/mila.12429","RegionNum":3,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"LINGUISTICS","Score":null,"Total":0}
In this article, I describe a novel position on the semantics of artificial intelligence. I present a problem for the current artificial neural networks used in machine learning, specifically with relation to natural language tasks. I then propose that from a metasemantic level, meaning in machines can best be interpreted as radically contextualist. Finally, I consider what this might mean for human-level semantic competence from a comparative perspective.
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