{"title":"深度ASI读写能力:与人工超级智能系统对齐的教育","authors":"Nicolas J. Tanchuk","doi":"10.1111/edth.70030","DOIUrl":null,"url":null,"abstract":"<p>Artificial intelligence companies and researchers are currently working to create Artificial Superintelligence (ASI): AI systems that significantly exceed human problem-solving speed, power, and precision across the full range of human solvable problems. Some have claimed that achieving ASI — for better or worse — would be the most significant event in human history and the last problem humanity would need to solve. In this essay Nicolas Tanchuk argues that current AI literacy frameworks and educational practices are inadequate for equipping the democratic public to deliberate about ASI design and to assess the existential risks of such technologies. He proposes that a systematic educational effort toward what he calls “Deep ASI Literacy” is needed to democratically evaluate possible ASI futures. Deep ASI Literacy integrates traditional AI literacy approaches with a deeper analysis of the axiological, epistemic, and ontological questions that are endemic to defining and risk-assessing pathways to ASI. Tanchuk concludes by recommending research aimed at identifying the assets and needs of educators across educational systems to advance Deep ASI Literacy.</p>","PeriodicalId":47134,"journal":{"name":"EDUCATIONAL THEORY","volume":"75 4","pages":"739-764"},"PeriodicalIF":0.9000,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/edth.70030","citationCount":"0","resultStr":"{\"title\":\"Deep ASI Literacy: Educating for Alignment with Artificial Super Intelligent Systems\",\"authors\":\"Nicolas J. Tanchuk\",\"doi\":\"10.1111/edth.70030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Artificial intelligence companies and researchers are currently working to create Artificial Superintelligence (ASI): AI systems that significantly exceed human problem-solving speed, power, and precision across the full range of human solvable problems. Some have claimed that achieving ASI — for better or worse — would be the most significant event in human history and the last problem humanity would need to solve. In this essay Nicolas Tanchuk argues that current AI literacy frameworks and educational practices are inadequate for equipping the democratic public to deliberate about ASI design and to assess the existential risks of such technologies. He proposes that a systematic educational effort toward what he calls “Deep ASI Literacy” is needed to democratically evaluate possible ASI futures. Deep ASI Literacy integrates traditional AI literacy approaches with a deeper analysis of the axiological, epistemic, and ontological questions that are endemic to defining and risk-assessing pathways to ASI. Tanchuk concludes by recommending research aimed at identifying the assets and needs of educators across educational systems to advance Deep ASI Literacy.</p>\",\"PeriodicalId\":47134,\"journal\":{\"name\":\"EDUCATIONAL THEORY\",\"volume\":\"75 4\",\"pages\":\"739-764\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/edth.70030\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EDUCATIONAL THEORY\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/edth.70030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EDUCATIONAL THEORY","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/edth.70030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Deep ASI Literacy: Educating for Alignment with Artificial Super Intelligent Systems
Artificial intelligence companies and researchers are currently working to create Artificial Superintelligence (ASI): AI systems that significantly exceed human problem-solving speed, power, and precision across the full range of human solvable problems. Some have claimed that achieving ASI — for better or worse — would be the most significant event in human history and the last problem humanity would need to solve. In this essay Nicolas Tanchuk argues that current AI literacy frameworks and educational practices are inadequate for equipping the democratic public to deliberate about ASI design and to assess the existential risks of such technologies. He proposes that a systematic educational effort toward what he calls “Deep ASI Literacy” is needed to democratically evaluate possible ASI futures. Deep ASI Literacy integrates traditional AI literacy approaches with a deeper analysis of the axiological, epistemic, and ontological questions that are endemic to defining and risk-assessing pathways to ASI. Tanchuk concludes by recommending research aimed at identifying the assets and needs of educators across educational systems to advance Deep ASI Literacy.
期刊介绍:
The general purposes of Educational Theory are to foster the continuing development of educational theory and to encourage wide and effective discussion of theoretical problems within the educational profession. In order to achieve these purposes, the journal is devoted to publishing scholarly articles and studies in the foundations of education, and in related disciplines outside the field of education, which contribute to the advancement of educational theory. It is the policy of the sponsoring organizations to maintain the journal as an open channel of communication and as an open forum for discussion.