{"title":"全民人工智能扫盲:可调整的跨学科社会技术课程","authors":"Sri Yash Tadimalla, Mary Lou Maher","doi":"arxiv-2409.10552","DOIUrl":null,"url":null,"abstract":"This paper presents a curriculum, \"AI Literacy for All,\" to promote an\ninterdisciplinary understanding of AI, its socio-technical implications, and\nits practical applications for all levels of education. With the rapid\nevolution of artificial intelligence (AI), there is a need for AI literacy that\ngoes beyond the traditional AI education curriculum. AI literacy has been\nconceptualized in various ways, including public literacy, competency building\nfor designers, conceptual understanding of AI concepts, and domain-specific\nupskilling. Most of these conceptualizations were established before the public\nrelease of Generative AI (Gen-AI) tools like ChatGPT. AI education has focused\non the principles and applications of AI through a technical lens that\nemphasizes the mastery of AI principles, the mathematical foundations\nunderlying these technologies, and the programming and mathematical skills\nnecessary to implement AI solutions. In AI Literacy for All, we emphasize a\nbalanced curriculum that includes technical and non-technical learning outcomes\nto enable a conceptual understanding and critical evaluation of AI technologies\nin an interdisciplinary socio-technical context. The paper presents four\npillars of AI literacy: understanding the scope and technical dimensions of AI,\nlearning how to interact with Gen-AI in an informed and responsible way, the\nsocio-technical issues of ethical and responsible AI, and the social and future\nimplications of AI. While it is important to include all learning outcomes for\nAI education in a Computer Science major, the learning outcomes can be adjusted\nfor other learning contexts, including, non-CS majors, high school summer\ncamps, the adult workforce, and the public. This paper advocates for a shift in\nAI literacy education to offer a more interdisciplinary socio-technical\napproach as a pathway to broaden participation in AI.","PeriodicalId":501112,"journal":{"name":"arXiv - CS - Computers and Society","volume":"12 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI Literacy for All: Adjustable Interdisciplinary Socio-technical Curriculum\",\"authors\":\"Sri Yash Tadimalla, Mary Lou Maher\",\"doi\":\"arxiv-2409.10552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a curriculum, \\\"AI Literacy for All,\\\" to promote an\\ninterdisciplinary understanding of AI, its socio-technical implications, and\\nits practical applications for all levels of education. With the rapid\\nevolution of artificial intelligence (AI), there is a need for AI literacy that\\ngoes beyond the traditional AI education curriculum. AI literacy has been\\nconceptualized in various ways, including public literacy, competency building\\nfor designers, conceptual understanding of AI concepts, and domain-specific\\nupskilling. Most of these conceptualizations were established before the public\\nrelease of Generative AI (Gen-AI) tools like ChatGPT. AI education has focused\\non the principles and applications of AI through a technical lens that\\nemphasizes the mastery of AI principles, the mathematical foundations\\nunderlying these technologies, and the programming and mathematical skills\\nnecessary to implement AI solutions. In AI Literacy for All, we emphasize a\\nbalanced curriculum that includes technical and non-technical learning outcomes\\nto enable a conceptual understanding and critical evaluation of AI technologies\\nin an interdisciplinary socio-technical context. The paper presents four\\npillars of AI literacy: understanding the scope and technical dimensions of AI,\\nlearning how to interact with Gen-AI in an informed and responsible way, the\\nsocio-technical issues of ethical and responsible AI, and the social and future\\nimplications of AI. While it is important to include all learning outcomes for\\nAI education in a Computer Science major, the learning outcomes can be adjusted\\nfor other learning contexts, including, non-CS majors, high school summer\\ncamps, the adult workforce, and the public. This paper advocates for a shift in\\nAI literacy education to offer a more interdisciplinary socio-technical\\napproach as a pathway to broaden participation in AI.\",\"PeriodicalId\":501112,\"journal\":{\"name\":\"arXiv - CS - Computers and Society\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Computers and Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10552\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computers and Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10552","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AI Literacy for All: Adjustable Interdisciplinary Socio-technical Curriculum
This paper presents a curriculum, "AI Literacy for All," to promote an
interdisciplinary understanding of AI, its socio-technical implications, and
its practical applications for all levels of education. With the rapid
evolution of artificial intelligence (AI), there is a need for AI literacy that
goes beyond the traditional AI education curriculum. AI literacy has been
conceptualized in various ways, including public literacy, competency building
for designers, conceptual understanding of AI concepts, and domain-specific
upskilling. Most of these conceptualizations were established before the public
release of Generative AI (Gen-AI) tools like ChatGPT. AI education has focused
on the principles and applications of AI through a technical lens that
emphasizes the mastery of AI principles, the mathematical foundations
underlying these technologies, and the programming and mathematical skills
necessary to implement AI solutions. In AI Literacy for All, we emphasize a
balanced curriculum that includes technical and non-technical learning outcomes
to enable a conceptual understanding and critical evaluation of AI technologies
in an interdisciplinary socio-technical context. The paper presents four
pillars of AI literacy: understanding the scope and technical dimensions of AI,
learning how to interact with Gen-AI in an informed and responsible way, the
socio-technical issues of ethical and responsible AI, and the social and future
implications of AI. While it is important to include all learning outcomes for
AI education in a Computer Science major, the learning outcomes can be adjusted
for other learning contexts, including, non-CS majors, high school summer
camps, the adult workforce, and the public. This paper advocates for a shift in
AI literacy education to offer a more interdisciplinary socio-technical
approach as a pathway to broaden participation in AI.