[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fgcMsO88hfxxXjbioT0X4LkUFuZ_yJ8IeDj2ah3-zquc":3},{"code":4,"msg":5,"data":6},200,"操作成功",{"id":7,"title":8,"content":9,"digest":10,"source":10,"coverPath":11,"thumbsCoverPath":12,"isTop":13,"isShow":14,"baseClick":13,"clickCount":15,"createTime":16,"typeId":17,"isNewest":18,"newsInfoTypeRespVo":19,"voiceUrl":22,"voiceSize":23,"taskId":24,"releaseTime":25,"titleEn":26,"contentEn":27,"voiceUrlEn":28,"taskIdEn":29,"voiceSizeEn":30},1328,"UNESCO发布《AI与教育的未来》","\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F09\u002F79599ee4762445a0994794af9e4b8903\u002F641.webp\" width=\"489\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">2025年9月2日，UNESCO发布《人工智能与教育未来：变革、困境与方向》（AI and the Future of Education: Disruptions, Dilemmas and Directions）论文集，深入探讨了AI对教育领域的颠覆性影响所引发的哲学思辨、伦理困境与教学变革。通过汇聚全球思想家、教育领袖与变革者的多元视角，该文集旨在挑战固有认知、揭示深层矛盾、激发学术争鸣，并为实现人机协同创造的公平愿景提供大胆构想。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">该文集开篇指出，AI在教育领域的崛起并非单一叙事，而是一场跨越学科、地域、语言和世界观的多维度对话。这些讨论聚焦于智力本质、教育目标以及人类与AI交织下共同构建的未来图景——无论这种构建是否出于自觉。相关探讨涉及计算机科学、哲学、心理学和认知科学等多元学科领域，不同立场的主体塑造着截然不同的话语：既有将AI视为教育变革良方的主流强势声音，也有警示其加剧社会不公、侵蚀教育本质的批判观点。从教师团体联名抵制生成式AI，到学者探索机器学习霸权之外的替代方案，这一领域始终充满张力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">该文集收录的21篇思想文章涵盖了从废除过时的评估体系到培养关爱伦理等7个主题，具体如下：\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">1.教育中的AI未来：哲学叩问\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">文集开篇的哲学探讨引领人们超越AI当下的利弊之争，直指更本质的命题——在AI增强的世界中，人类如何学习、存在与发展。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Báyò Akómoláfé在对话中提出：AI不仅是工具，更是动摇教育本体论与认识论根基的力量。借鉴后人类主义与关系性视角，他追问当教育日益被\"超人类\"系统塑造时，学习、教学与治理意味着什么？他呼吁教育者拥抱迷失与断裂，将其视为新感知方式和共存关系的契机，而非亟待解决的问题。这种思考敦促我们超越控制、掌控与规模化的语言，驻足于主流范式失灵之处。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Bing Song则从和谐哲学与心性修养传统出发，对比强调自主性、预测与效率的AI模型，主张将智慧教育置于课程改革核心。其目标不仅是技能获取，更强调伦理判断、自省与平衡的培育——这些品质在充满不确定性与机器逻辑的时代愈发珍贵。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Mary Rice与Joaquín T. Argüello de Jesús以\"水\"为隐喻，通过多维度\"检测\"，将水的历史政治经济学、生态学与AI进行类比，揭示权力与知识流动的深层关联。他们的思考提供了一种时间敏感性的探索：如何从维系生命的水系统治理中，汲取构建生成式AI未来的智慧。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">2.AI的潜力与风险之争\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">生成式AI的每周突破不断助长\"机器即将超越人类认知\"的论断。从通用人工智能（AGI）到超级人工智能（ASI）的设想，不仅重塑学习方式，更挑战对智力本质的认知。这些设想迫使教育界重新思考：在一个机器深度介入的世界，教育的核心使命是什么？人之为人的意义何在？\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Andreas Horn从产业视角指出，AI教育应用正呼唤decisive leadership。他提出务实路线图：教学法优先、投资教师队伍建设、选择性应用AI、强制AI素养教育、设置防护栏，以及培养学生主导AI时代的能力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Emily M. Bender则尖锐批判主流AI叙事，称其为可能贬低教育者价值、误导公共投资的 speculative myths。她强调：大语言模型（LLMs）不具备理解、推理或关怀能力，仅是生成统计合理文本的装置。真正的颠覆不在于技术本身，而在于少数商业巨头对教育系统的日益掌控。她的论述揭示了公共教育正被私有化逻辑重构的危机。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">这些分歧折射出深层张力：一方视AI为教育改革的加速器，另一方则主张对其进行民主监督与伦理约束。Markus Deimann和Robert Farrow探讨了如何重建以包容、正义、可持续与关怀为价值基石的教育图景。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">3.AI教学法、评估体系与未来教育新图景\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">在教育学领域，AI对人类认知方式、超个性化学习、课程体系、评估机制以及教师角色演变的影响正引发深度探讨。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Abeba Birhane借鉴保罗·弗莱雷的批判教育学理论、Hanna de Jaegher的具身认知科学研究及最新实证数据，提出教育本质上是具有关系性、动态性、伦理性和政治性的社会实践。她驳斥了将学习简化为概率模型的假设，警示基于历史数据训练的AI系统可能抹杀人类思维的丰富性，并加剧系统性不平等。其行动倡议强调：在建立独立监管体系、完善保障机制、确保教师-学习者-社区三方实质性参与之前，教育界应审慎对待AI的全盘应用。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Carla Aerts与Paul Prinsloo指出，虽然AI的差异化教学能力颇具潜力，但算法驱动的个性化学习可能导致学习者孤立化、自主权萎缩、不平等加剧以及教师角色边缘化。他们主张采用\"以人为中心\"的路径，让AI作为集体社会智能中的辅助性\"第三存在\"，促进共情能力培养、协作学习、文化多样性包容及学生主体性发展。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">当AI系统能够独立生成高质量课业时，教育者面临核心拷问：传统评估方式既已失效，该如何重构？该文集呈现两种互补观点。Mike Perkins和Jasper Roe认为生成式AI暴露出传统评估体系的固有缺陷，同时加剧全球教育不平等——AI工具、基础设施及培训资源的获取差异可能使评估体系沦为新的排斥机制。他们提出分级框架，帮助教师判别AI使用何时促进\u002F损害学习诚信。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Bill Cope、Mary Kalantzis与Akash Kumar Saini则持审慎乐观立场。在批判高风险标准化测评的过时性基础上，他们构想AI作为合作伙伴，助力构建持续性、形成性、人性化的评估体系。其\"网络社交学习\"理论将AI定位为教学中介：基于教师设计的评估量规，增强学习反馈效能，深化关系性教学实践。这两组关于教育评估的论述构成辩证对话，从不同视角既发出预警，又指明前路。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">4.重新定义教师的核心价值\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">随着人工智能逐步融入各类教学场景，一个关键问题浮出水面：如何重塑教师的角色？AI是否终将取代人类教师？本专题的讨论聚焦于在AI增强的教学环境中，如何通过策略重构教师的核心价值。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Ching Sing Chai, Jiun-Yu Wu与Thomas K.F. Chiu基于马丁·布伯和格特·比斯塔的理论框架，从关系性、目的性、认知性、心理性和教育性五个维度，系统分析了AI对人类发展的影响。他们强调，教育的本质绝非知识灌输，而是培养具有自主性、批判思维并能参与社会建构的完整人格。研究特别指出，过度依赖AI可能侵蚀学生好奇心和情感健康这些支撑自主发展的基石，因此必须维护师生关系中的人文内核。作者呼吁教师应主动引领AI整合，成为学习生态的\"意向性设计者\"，始终捍卫学习者的主体性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">基于这一伦理框架，Arafeh Karimi提出了七项实践转型方案，将关怀伦理、公平性原则和关系问责制注入AI系统的开发与治理中。其建议涵盖师生参与式协同设计、可信度与福祉评估、公平导向的可解释性机制，以及教师主导的数据管理模式。如果说前三位学者构建了理论基石，Arafeh Karimi则展示了如何通过政策工具与采购机制落实这些原则。她将AI重新定位为教育生态的协作进化者而非颠覆者，在这个持续发展的系统中，包容性、归属感与教学尊严将通过制度设计得到系统性培育。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">5.教育领域AI发展的伦理与治理要义\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">当AI系统深度融入教育肌理——从内容生成、学习者画像到政策自动化——治理问题变得愈发紧迫且复杂。谁来决定教育AI的设计准则、部署规范与监管机制？\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kaśka Porayska-Pomsta和Isak Nti Asare提出\"设计即关怀\"的伦理框架，强调教育本质上是关乎人类成长、脆弱性与相互依存的深层过程。他们主张伦理准则不应在AI系统部署后被动修补，而应通过优先考虑师生真实需求的参与式包容性设计，从源头嵌入系统架构。这一研究呼应了全球范围内日益强烈的共识：必须将人权、包容性与尊严确立为教育AI治理的基石。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kalervo N. Gulson和 Sam Sellar则通过分析\"合成治理\"的兴起深化了讨论——这种新型决策模式正日益受算法系统与机器逻辑塑造。其提出的\"合成政治\"概念驳斥了\"AI在教育政策中保持中立\"的假设，呼吁建立以价值导向、民主参与和权力审视为核心的批判性应对机制。随着教育系统愈发依赖数据驱动平台与预测模型，两位学者追问：这些技术正在塑造何种政治主体性与治理真相？我们又如何通过抵制、重构或转化这些机制，以捍卫教育作为公共利益的公平属性？\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">6.直面教育中的算法不平等\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">该文集中有四篇论述为追求公平包容的AI教育未来提供了全新社会构想，这些构想旨在应对新型的算法不平等现象。每篇论述都聚焦于人的主体性、文化语言多样性以及全球南方边缘化学习者（包括年轻女性和听障群体）的真实生存境遇。它们共同提出了立足实践、追求正义的参与式路径，将AI重新定位为促进教育共创、包容与关系变革的社会技术系统。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Vukosi Marivate、Nombuyiselo Caroline Zondi与Baphumelele Masikisiki提出了一个植根于公平理念、文化多元主义及师生日常实践的非洲高等教育AI融合方案。他们主张采用由本地主导的参与式方法，强调人的主体地位、教育关怀与情境化知识。基于基层实践、田野调查和多语言课堂经验，他们呼吁开发不仅能翻译更要能转型的AI系统——这些系统应当能识别多样化的交流模式，支持弱势语言，并体现当地社区的社会想象。从伦理数据治理到离线AI工具，再到教师主导的模型校准，他们提供了构建智能学习系统的具体策略，这些系统以建立师生信任关系、共创价值为核心。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kiran Bhatia与Payal Arora则大胆重构了AI、教育与全球南方年轻女性三者间的关系。他们批判将年轻女性视为\"风险管控对象\"的保护主义范式，反对基于道德恐慌与监控的叙事框架，转而提出以快乐、创造力与变革能动性为核心的AI教育愿景。在这个愿景中，身处边缘地带的年轻女性将成为数字未来的共同缔造者，打破性别、阶级、地域与网络接入的不平等结构。这需要从象征性咨询转向实质共创，从机械合规转向创新表达，从控制转向关怀。本文不仅止步于批判，更颂扬年轻女性的智慧与韧性，倡导将AI教育重塑为充满自由、意义与人际尊严的空间。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Yuchen Wang聚焦全纳教育，呼吁厘清\"包容\"的伦理内涵，强调关系性、归属感与集体学习优于狭隘的个性化概念。她邀请政策制定者、教育工作者与开发者基于学习者真实经历，借鉴全纳教育研究成果，以改造而非修补教育系统的道德决心，共同设计AI教育系统。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Marloes Williams van Elswijk则关注听障学习者（DHH）面临的复杂挑战：语言剥夺、数据贫困与性别边缘化等多重结构性障碍。她主张与听障社群共同设计多模态AI教育系统，并保留人工支持层级——因为真正的公平永远无法仅靠自动化实现。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">7.重塑教育政策中的AI：证据与地缘政治现实\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">该文集以两篇思想性文章作结，探讨政策方向与循证决策的作用。George Siemens对生成式AI给教育体系带来的变革与混乱进行了冷静而前瞻的思考。他指出，对于中美等大力投资AI前沿研究、基础设施和网络安全的国家而言，人工智能正日益成为治国方略的工具——这些国家投入的战略远见与意图，堪比对待军事和经济实力的重视。在他看来，这场地缘政治竞赛凸显了构建教育系统的紧迫性：既要释放AI潜力，又要守护人类福祉，这要求教育部长们将政策制定视为系统变革与集体学习的过程。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Ilkka Tuomi则借鉴批判现实主义、\"政策即学习\"理念及杜威的实用主义，主张将教育政策重构为集体意义建构与发展性实验，而非线性执行。他批判了生成式AI导致的知识商品化现象，强调应将人的能动性、社会目标与能力发展作为核心教育宗旨。他呼吁的不是扩大证据规模，而是重新思考何为有效证据，并设计能服务于教育决策的智能学习型证据体系。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">该文集最后结论概括了教育与AI的三个关键领域：\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">1.作为伦理、公平且以人为本的AI教育守护者\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI在教育中的未来发展亟需优先关注权力、机会与资源分配中的结构性不平等如何被重塑。这些系统的演进可能加剧现有的性别、阶级、语言、地域及数字接入鸿沟。此刻需要超越技术修补的魄力，从根本上重新构想AI在教育中的角色。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">2.作为课程与教学重构的思想引领者\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI已在重塑课程设置、教学方法、评估体系与知识生产。这凸显了引领新兴课程与教学变革的必要性，需探索以批判性思维、元认知能力、关怀教育学与伦理推理为核心的策略，从而挑战机械记忆学习、标准化评估、认知外包及拟人化AI陪伴背后的简化逻辑及其复杂风险。在此背景下，关注网络社交学习中包容性新教学法的可能性变得至关重要。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">3.作为多元争议对话的催化平台\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">教育AI的哲学张力意味着需建立审议式论坛，让不同社群、学科与文化背景的参与者不仅探讨AI的实施，更深入辩论其教育目的、持续演化的影响及后果。此类论坛必须放大边缘化群体——包括原住民、性别少数、全球南方与残障人士——的声音与视角。前行之路需要的不仅是谨慎调适，更要求在全球日益增长的不确定性与动荡中，彻底重新思考如何设计、治理并整合人机协同的教育系统。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cem style=\"color: rgb(165, 165, 165);\">资料来源：\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cem style=\"color: rgb(165, 165, 165);\">UNESCO. AI and the future of education Disruptions, dilemmas and directions. https:\u002F\u002Funesdoc.unesco.org\u002Fark:\u002F48223\u002Fpf0000395236\u003C\u002Fem>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">【新闻来源】教育国际前沿 \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20250902A08KQ300\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20250902A08KQ300\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（本网转发此文章，旨在为读者提供更多的信息资讯，所涉内容不构成投资、消费建议。文章事实如有疑问，请与有关方核实，文章观点非本网观点，仅供读者参考。）\u003C\u002Fspan>\u003C\u002Fp>","","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F09\u002F1292948e1daa4f00bed0a8b5b876d11b\u002F教育生态.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F09\u002Fthumbs\u002F1292948e1daa4f00bed0a8b5b876d11b\u002F教育生态.jpg",0,1,50,"2025-09-04 18:46",2,false,{"id":17,"name":20,"enName":21},"芯位视野","Xinwei Vision","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A41f781ea-5dca-4287-a231-a515919b42ab%3A0.wav?Expires=1756986788&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=Dkx1%2BE3pgW%2F4CbY%2FSSPxmSrRe8s%3D",27090538,"41f781ea-5dca-4287-a231-a515919b42ab","2025-09-04 18:41","UNESCO released \"The Future of Education and AI\"","\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F09\u002F79599ee4762445a0994794af9e4b8903\u002F641.webp\" width=\"489\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">On September 2, 2025, UNESCO published the collection of papers \"Artificial Intelligence and the Future of Education: Disruptions, Dilemmas and Directions,\" which delves into the philosophical reflections, ethical dilemmas, and pedagogical transformations triggered by the disruptive impact of AI on the education sector. By gathering diverse perspectives from global thinkers, educational leaders, and change-makers, this collection aims to challenge existing perceptions, reveal deep-seated contradictions, stimulate academic debates, and provide bold visions for achieving a fair future created through human-machine collaboration.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The collection opens with the assertion that the rise of AI in education is not a single narrative, but a multidimensional dialogue spanning disciplines, regions, languages, and worldviews. These discussions focus on the essence of intelligence, the goals of education, and the future scenarios co-created by humans and AI—whether or not such creation is conscious. The related discussions involve multiple fields including computer science, philosophy, psychology, and cognitive science. Different positions shape entirely different discourses: there are mainstream voices that see AI as a solution to educational transformation, as well as critical perspectives that warn about its potential to exacerbate social inequality and erode the essence of education. From teacher groups resisting generative AI together, to scholars exploring alternatives beyond machine learning hegemony, this field has always been full of tension.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The collection includes 21 thought-provoking articles covering seven themes, specifically as follows:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">1. The Future of AI in Education: Philosophical Inquiry\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The philosophical exploration at the beginning of the collection goes beyond the current pros and cons of AI, addressing more fundamental questions—how humans learn, exist, and develop in an AI-enhanced world.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Báyò Akómoláfé proposes that AI is not only a tool, but also a force that challenges the ontological and epistemological foundations of education. Drawing on posthumanist and relational perspectives, he questions what learning, teaching, and governance mean when education is increasingly shaped by \"superhuman\" systems. He calls on educators to embrace disorientation and rupture, viewing them as opportunities for new modes of perception and coexistence rather than problems to be solved immediately. This thinking urges us to move beyond language of control, mastery, and scalability, and to dwell where mainstream paradigms fail.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Bing Song, starting from the traditions of harmonious philosophy and mind cultivation, contrasts AI models emphasizing autonomy, prediction, and efficiency, advocating placing wise education at the core of curriculum reform. Its goal is not only skill acquisition, but also the cultivation of ethical judgment, self-reflection, and balance—qualities that become increasingly precious in an era of uncertainty and machine logic.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Mary Rice and Joaquín T. Argüello de Jesús use \"water\" as a metaphor, drawing comparisons between the historical political economy and ecology of water and AI through multi-dimensional \"detections,\" revealing deep connections between power and knowledge flows. Their thoughts offer a time-sensitive exploration: how can we draw wisdom from the governance of life-sustaining water systems to build the future of generative AI?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">2. The Debate on AI's Potential and Risks\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Weekly breakthroughs in generative AI continue to fuel the claim that \"machines are about to surpass human cognition.\" From General Artificial Intelligence (AGI) to Super Artificial Intelligence (ASI), these ideas not only reshape learning methods but also challenge conceptions of the nature of intelligence. These ideas force the education sector to reconsider: What is the core mission of education in a world deeply involved by machines? What does it mean to be human?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Andreas Horn, from an industrial perspective, points out that AI applications in education call for decisive leadership. He proposes a pragmatic roadmap: prioritizing pedagogy, investing in teacher development, selectively applying AI, enforcing AI literacy education, setting up safeguards, and cultivating students' abilities to lead in the AI era.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Emily M. Bender sharply criticizes the mainstream AI narrative, calling it speculative myths that may devalue the value of educators and mislead public investment. She emphasizes that large language models (LLMs) lack the ability to understand, reason, or care—they are just devices that generate statistically plausible texts. The real disruption lies not in the technology itself, but in the increasing control of educational systems by a few commercial giants. Her arguments reveal the crisis of public education being restructured by privatization logic.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">These differences reflect deeper tensions: one sees AI as an accelerator for educational reform, while the other advocates for democratic supervision and ethical constraints. Markus Deimann and Robert Farrow explore how to rebuild an educational vision grounded in values of inclusivity, justice, sustainability, and care.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">3. AI Pedagogy, Assessment Systems, and New Educational Scenarios\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">In the field of pedagogy, the impact of AI on human cognitive patterns, hyper-personalized learning, curricula, assessment mechanisms, and the evolution of the teacher role is triggering in-depth discussions.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Abeba Birhane draws on Paulo Freire's critical pedagogy theory, Hanna de Jaegher's embodied cognition research, and the latest empirical data, proposing that education is essentially a socially situated, dynamic, ethical, and political practice. She refutes the assumption that learning can be simplified into probabilistic models, warning that AI systems trained on historical data may erase the richness of human thinking and exacerbate systemic inequalities. Her action initiatives emphasize that before fully adopting AI, the education sector should exercise caution, establish independent regulatory systems, improve safeguard mechanisms, and ensure substantive participation from teachers, learners, and communities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Carla Aerts and Paul Prinsloo point out that although the differentiated teaching capabilities of AI are promising, algorithm-driven personalized learning may lead to learner isolation, loss of autonomy, increased inequality, and marginalization of the teacher role. They advocate for a \"human-centered\" approach, allowing AI to act as a \"third entity\" within collective social intelligence, promoting empathy, collaborative learning, cultural diversity, and student agency.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">When AI systems can independently generate high-quality assignments, educators face a core question: if traditional assessment methods have already failed, how should they be reconstructed? This collection presents two complementary views. Mike Perkins and Jasper Roe argue that generative AI exposes the inherent flaws of traditional assessment systems and exacerbates global educational inequality—differences in access to AI tools, infrastructure, and training resources may make assessment systems become new mechanisms of exclusion. They propose a tiered framework to help teachers determine when AI use promotes or harms academic integrity.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Bill Cope, Mary Kalantzis, and Akash Kumar Saini take a cautious optimistic stance. Based on a critique of the outdatedness of high-risk standardized assessments, they envision AI as a partner to help build continuous, formative, and humane assessment systems. Their \"networked social learning\" theory positions AI as a teaching mediator: based on assessment rubrics designed by teachers, it enhances the effectiveness of learning feedback and deepens relational teaching practices. These two sets of discussions on educational assessment form a dialectical dialogue, issuing warnings from different perspectives while pointing the way forward.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">4. Redefining the Core Value of Teachers\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">As artificial intelligence gradually integrates into various teaching scenarios, a key question emerges: How to reshape the role of teachers? Will AI eventually replace human teachers? This section focuses on how to redefine the core value of teachers in an AI-enhanced teaching environment.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Ching Sing Chai, Jiun-Yu Wu, and Thomas K.F. Chiu, based on the theoretical frameworks of Martin Buber and Gert Biesta, systematically analyze the impact of AI on human development from five dimensions: relational, purposeful, cognitive, psychological, and educational. They emphasize that the essence of education is not merely the transmission of knowledge, but the cultivation of complete personalities with autonomy, critical thinking, and the ability to participate in social construction. The study particularly points out that over-reliance on AI may erode the foundational elements of students' curiosity and emotional health that support autonomous development, so the humanistic core in teacher-student relationships must be maintained. The authors call on teachers to actively lead the integration of AI, becoming \"intentional designers\" of the learning ecosystem, always defending the subjectivity of learners.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Based on this ethical framework, Arafeh Karimi proposed seven practical transformation strategies, integrating caring ethics, principles of fairness, and relational accountability into the development and governance of AI systems. Her suggestions include participatory co-design by teachers and students, trustworthiness and well-being assessments, fairness-oriented explainability mechanisms, and teacher-led data management models. If the first three scholars built the theoretical foundation, Arafeh Karimi showed how to implement these principles through policy tools and procurement mechanisms. She repositions AI as a collaborative evolutionary force in the educational ecosystem rather than a disruptor. In this continuously evolving system, inclusiveness, a sense of belonging, and teaching dignity will be systematically nurtured through institutional design.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">5. Ethical and Governance Essentials in AI Development in the Education Sector\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">As AI systems are deeply integrated into the fabric of education—from content generation, learner profiles to policy automation—the issue of governance becomes increasingly urgent and complex. Who decides the design criteria, deployment standards, and regulatory mechanisms for educational AI?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kaśka Porayska-Pomsta and Isak Nti Asare propose an \"ethics of design as care\" framework, emphasizing that education is fundamentally a deep process involving human growth, vulnerability, and interdependence. They argue that ethical guidelines should not be passively added after AI systems are deployed, but should be embedded in the system architecture from the outset through participatory inclusive design that prioritizes the real needs of teachers and students. This research echoes a growing global consensus: human rights, inclusion, and dignity must be established as the cornerstone of educational AI governance.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kalervo N. Gulson and Sam Sellar further deepen the discussion by analyzing the rise of \"synthetic governance\"—a new decision-making model increasingly shaped by algorithmic systems and machine logic. Their concept of \"synthetic politics\" refutes the assumption that \"AI remains neutral in educational policy,\" and calls for a critical response mechanism centered on value orientation, democratic participation, and power scrutiny. As educational systems become increasingly reliant on data-driven platforms and predictive models, the two scholars ask: what kind of political subjectivity and governance truth are these technologies shaping? How can we resist, restructure, or transform these mechanisms to safeguard the fairness of education as a public good?\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">6. Confronting Algorithmic Inequality in Education\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Four articles in this collection provide new social constructs for a fair and inclusive AI education future, aiming to address new forms of algorithmic inequality. Each article focuses on the subjectivity of people, cultural and linguistic diversity, and the real living conditions of marginalized learners in the Global South, including young women and deaf and hard-of-hearing individuals. They collectively propose participatory approaches rooted in practice and pursuing justice, repositioning AI as a socio-technical system that promotes educational co-creation, inclusion, and relational change.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Vukosi Marivate, Nombuyiselo Caroline Zondi, and Baphumelele Masikisiki propose an African higher education AI integration plan rooted in fairness, cultural pluralism, and the daily practices of teachers and students. They advocate for locally led participatory approaches, emphasizing the centrality of human beings, educational care, and contextualized knowledge. Based on grassroots practices, fieldwork, and multilingual classroom experiences, they call for the development of AI systems that not only translate but also transform—these systems should be able to recognize diverse communication patterns, support underrepresented languages, and reflect the social imagination of local communities. From ethical data governance to offline AI tools, and teacher-led model calibration, they provide specific strategies for building intelligent learning systems, which center on establishing trust relationships between teachers and students and co-creating value.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Kiran Bhatia and Payal Arora boldly reconfigure the relationship among AI, education, and young women in the Global South. They criticize the protective paradigm that views young women as \"risk management subjects\" and oppose the narrative framework based on moral panic and surveillance, instead proposing an AI education vision centered on joy, creativity, and transformative agency. In this vision, young women on the margins become co-creators of the digital future, breaking down unequal structures of gender, class, geography, and internet access. This requires moving from symbolic consultation to substantive co-creation, from mechanical compliance to innovative expression, and from control to care. This article not only stops at criticism but also celebrates the wisdom and resilience of young women, advocating for the reshaping of AI education into a space filled with freedom, meaning, and human dignity.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Yuchen Wang focuses on inclusive education, calling for clarifying the ethical connotation of \"inclusiveness,\" emphasizing relationality, belonging, and collective learning over narrow concepts of personalization. She invites policymakers, educators, and developers to jointly design AI education systems based on the real experiences of learners, using the moral determination to transform rather than fix the education system, drawing on inclusive education research findings.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Marloes Williams van Elswijk focuses on the complex challenges faced by deaf and hard-of-hearing learners (DHH): language deprivation, data poverty, and gender marginalization. She advocates for designing multimodal AI education systems in collaboration with the deaf community and retaining human support levels—because true fairness can never be achieved solely through automation.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">7. Reimagining AI in Educational Policy: Evidence and Geopolitical Realities\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The collection concludes with two thought-provoking articles discussing the role of policy direction and evidence-based decision-making. George Siemens provides a calm and forward-looking reflection on the changes and chaos brought by generative AI to the education system. He points out that for countries like China and the United States, which heavily invest in AI frontier research, infrastructure, and cybersecurity, artificial intelligence is increasingly becoming a tool for statecraft—these countries' strategic foresight and intentions are comparable to their emphasis on military and economic strength. In his view, this geopolitical competition highlights the urgency of building an educational system: not only to unleash the potential of AI but also to protect human well-being, requiring education ministers to view policy-making as a process of systemic change and collective learning.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">Ilkka Tuomi draws on critical realism, the idea of \"policy as learning,\" and Dewey's pragmatism, arguing that educational policy should be restructured as collective meaning-making and developmental experimentation, rather than linear execution. He critiques the commodification of knowledge caused by generative AI, emphasizing that human agency, social objectives, and capacity development should be the core educational goals. He calls not for expanding the scale of evidence, but for rethinking what constitutes effective evidence and designing intelligent learning evidence systems that serve educational decision-making.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The collection concludes with a summary of three key areas for the future of education and AI:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">1. As an ethical, fair, and human-centered guardian of AI in education\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The future development of AI in education urgently needs to prioritize how structural inequalities in power, opportunity, and resource distribution are being reshaped. The evolution of these systems may exacerbate existing gender, class, language, regional, and digital access gaps. At this moment, it is necessary to go beyond technical fixes and fundamentally rethink the role of AI in education.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">2. As a thought leader in the restructuring of curriculum and teaching\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">AI is already reshaping curriculum design, teaching methods, assessment systems, and knowledge production. This highlights the need to lead emerging curriculum and teaching changes, exploring strategies centered on critical thinking, metacognitive skills, caring pedagogy, and ethical reasoning, thus challenging the simplified logic and complex risks behind rote memorization, standardized assessments, cognitive outsourcing, and anthropomorphic AI companions. In this context, it is crucial to pay attention to the possibilities of inclusive new teaching methods in networked social learning.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\" class=\"ql-lineHeight-1-75\">3. As a catalyst platform for diverse controversial dialogues\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\" class=\"ql-lineHeight-1-75\">The philosophical tensions surrounding educational AI mean the need to establish deliberative forums where participants from different communities, disciplines, and cultural backgrounds not only discuss the implementation of AI, but also engage in in-depth debates about its educational purposes, ongoing impacts, and consequences. Such forums must amplify the voices and perspectives of marginalized groups—including indigenous peoples, gender minorities, the Global South, and people with disabilities. The path forward requires not only cautious adjustments but also a thorough rethinking of how to design, govern, and integrate human-machine collaborative education systems amid growing global uncertainty and turbulence.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cem style=\"color: rgb(165, 165, 165);\">Source:\u003C\u002Fem>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cem style=\"color: rgb(165, 165, 165);\">UNESCO. AI and the future of education Disruptions, dilemmas and directions. https:\u002F\u002Funesdoc.unesco.org\u002Fark:\u002F48223\u002Fpf0000395236\u003C\u002Fem>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">[News Source] Frontiers of International Education \u003C\u002Fspan>\u003Ca href=\"https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20250902A08KQ300\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(187, 187, 187);\">https:\u002F\u002Fnews.qq.com\u002Frain\u002Fa\u002F20250902A08KQ300\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(187, 187, 187);\">（This article is reposted by this website to provide readers with more information and news. The content does not constitute investment or consumption advice. If there are any questions about the facts of the article, please verify with the relevant parties. The views expressed in the article are not the views of this website, and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3A852e0992-3608-4996-a2d3-a7575d185c16%3A0.wav?Expires=1774838477&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=YpEy428SC9sZAkJcfaJmP%2FMfKrY%3D","852e0992-3608-4996-a2d3-a7575d185c16",17262790]