[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fZRCuf011-pwcOrIUZ3Eo8GZwq6S53IDU_gG0eqxcO_A":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},1508,"AI驱动的未来技能发展图景发布","\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">近日，欧洲职业培训发展中心（Cedefop）发布一份长达133页的研究论文《为2040年做准备：AI驱动的四种技能持续发展图景》（Preparing for 2040: Four AI-powered scenarios for the future of continuing skills development）。论文描绘了未来几十年AI驱动下技能发展的可能性，以引导利益相关方共同构建一个面向2040年、具备韧性、包容性且适应未来的持续技能发展生态系统。该研究论文主要内容总结如下。\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">一、背景与研究方法\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">论文开篇即指出，在技术颠覆、人口结构变化和气候挑战日益加剧的今天，传统的、以教育机构为中心的继续职业教育与培训模式已难以为继。未来的技能发展必须是一个贯穿个人整个职业生涯和生活各种场景的连续过程，深度融合机构学习、自主学习和在工作场所中的学习。而在所有影响未来的趋势中，AI因其巨大的潜力和高度的不确定性，成为最核心的驱动力量，因此需要适应性策略以利用AI的潜力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">为应对未来挑战并深入理解持续技能发展领域的潜在机遇，Cedefop启动了这项战略前瞻研究项目，旨在构建面向2040年的持续技能发展的共同愿景，设计替代情景方案并制定战略目标。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">该论文研究过程中综合利用了图景构建、图景探索和愿景构建等方法。其中图景构建阶段包括：识别将影响持续技能发展未来发展的关键趋势；分析其潜在影响和不确定性；使用形态分析法识别不同的演变路径；制定图景纲要；通过半德尔菲调查验证图景纲要。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002F80fba42275bf4e2dad6cee0f53ae4efa\u002F企业微信截图_20251215084737.png\" width=\"341\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">这一过程最终形成了四种图景，分别从不同角度探讨了到2040年与持续技能发展相关的各种特征和条件可能如何演变。在整个研究过程中，Cedefop与多元利益相关方展开合作，包括未来学家与领域专家、各级政策制定者、雇员与雇主代表、民间社会组织以及教育\u002F培训\u002F职业指导机构，以确保研究成果能融合多维度视角与专业智慧。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">二、AI驱动的四种技能持续发展场景\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">这四个图景围绕AI应用趋势及其与其他趋势的交互作用展开，勾勒出多种可能的未来图景。基于趋势分析与形态学分析，在已识别的所有趋势中，AI最可能影响未来成人持续技能发展进程。在两次趋势分析迭代中，专家们一致评定所有AI相关趋势具有高度影响力（能影响多数其他趋势）与高度不确定性（专家对AI趋势实现的速度与规模存在分歧）。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">这些未来图景光谱涵盖两个极端：从AI增强人类能力并促进社会福祉的积极前景，到AI被主要用于控制与利润最大化、导致大规模失业、剩余岗位普遍缺乏保障与福利的黯淡未来。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">这些图景并非预测性质，而是探索性工具，旨在识别需关注的领域、需应对的威胁及应把握的机遇。通过探索未来潜在发展路径，这些图景可为构建持续技能发展的共同愿景提供依据，并指导制定2040年战略目标。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">各图景的核心假设与驱动趋势可概括如下：\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">1.图景A：充满机遇的未来——技术驱动的人才竞争\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">2040年，由于人口老龄化和移民流动减缓，欧盟劳动力正持续萎缩。然而在技术创新与AI的推动下，经济蓬勃发展并创造大量新岗位。虽然商业活动繁荣发展，但随着技能供需关系的逆向演变与技能缺口扩大，招聘困境持续加剧，人才争夺战达到前所未有的激烈程度。劳动力市场日趋紧缩。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">大多数劳动者和企业都受益于AI发展。以人为本的技能依然至关重要。对更多雇主而言，人才留存成为首要任务。以使命为导向的职业选择形成风潮，成为越来越多人的人生选项。技术变革与持续技能提升的需求，推动学习环境更深层次融入工作场所。机构教育与培训的边界将持续模糊，甚至可能完全消失。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">技能发展体系将更具灵活性、可及性与响应能力，能更好满足劳动力的多样化需求，为个人学习历程提供更顺畅的过渡与进阶通道。最终，非传统新兴参与者将成为学习内容的常态化创造者。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">2.图景B：独自驾驭浪潮——在AI对就业的冲击波中航行\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">2040年，接连不断的AI变革浪潮已彻底重塑职场格局，对劳动力市场产生强烈冲击，并以截然不同的方式影响着各类人群。随着国家和雇主逐步退出劳动力技能培养领域，适龄劳动者大多只能依靠自己——他们在技术浪潮中艰难前行，努力保持技能与时俱进，但成效参差不齐。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">有人娴熟地乘风破浪，有人却在生存线上苦苦挣扎，形成了我们如今所称的\"双层劳动力结构\"。AI冲击着欧洲绝大多数职业和行业，个人需自行承担持续技能提升的责任。这种变革难以掌控，仅有部分群体能从中获益。另有少数群体面临适应困境，为保住工作不得不牺牲心理健康、生理健康和社会经济福祉。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">3.图景C：勉强维持——错失AI机遇\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">2040年，AI持续发展但步伐平缓，对工作任务和就业岗位仅带来适度变革而非广泛冲击。这种变化节奏总体上可被雇主、劳动者及欧盟成员国所适应，渐进式调整通常已足够应对。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">与此同时，由于各行业、成员国和不同人群对AI的投资与参与程度不均，AI改善经济社会条件的潜力未能充分释放。变革处于可控范围内，部分群体从中获益，但多数人错失机遇，另一些人仍在艰难应对。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">技能开发与技能运用的重要性维持在当前水平，自主规划职业生涯的人群比例亦无显著变化。各类教育与培训选项尚未实现深度融合。学习内容仍主要由传统主体提供。AI对学习、教学及职业指导的影响依然有限。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">4.图景D：AI失控——主导职场与社会\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">2040年，AI技术与自动化已全面渗透生活工作各领域，深刻重构社会结构，导致所有行业、产业和技能层级出现前所未有的失业潮。少数掌控AI生态的巨头对政策制定者、经济和社会施加着巨大影响力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">对劳动者而言，这场变革具有颠覆性。随着AI接管多数工作任务，劳动者越来越多地以非标准合同形式受雇，技能发展机会、职业保障和福利待遇大幅缩水。企业无意对\"可弃置型\"劳动力进行技能投资，仅针对少数员工培养高阶AI相关技能。劳动者被迫完全自主承担技能提升责任，在频繁被动的职业转换中疲于应对。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">传统雇佣模式和工会岗位的消亡削弱了工会力量，劳动者失去维护权益的强力代言者。监管缺位导致权力失衡，不仅威胁民主制度，更加剧了环境恶化。AI彻底重塑了技能发展体系：正规与非正规教育培训的界限逐渐模糊，新型AI驱动工具和职业角色不断涌现。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">三、共性问题与矛盾焦点\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">尽管存在差异，上述图景仍呈现出若干共同特征，同时揭示出未来挑战与机遇的复杂多元格局。这些深层问题在不同图境中表现强度各异，但在构建持续技能发展的未来愿景及其战略目标时，它们至关重要。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">1.AI的双重潜力\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">AI在增强人类能力、推动创新和改善社会成果方面具有巨大潜力。在图景A中，AI被用于创造经济增长、社会流动性和环境可持续性的新机遇，从而提升个人、经济体和社会的生活质量。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">然而，AI的双重性也带来重大风险——当其部署主要受控于权力掌控和利润最大化动机时尤为明显。如图景D所示，不受约束的AI发展可能导致权力与财富的集中，加剧社会经济不平等，并侵蚀民主制度。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">此外，AI的影响还可能呈现更微妙的复杂性，这在图景B中得以印证：其效益与影响分配不均。优势群体能利用AI巩固其地位，而边缘群体则被抛在后面，面临获取机会、参与权和社会流动的重重障碍。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">但AI应用不足同样存在风险，如图景C所描绘的——对AI投入不足及未能释放其潜力将导致停滞与自满，最终丧失竞争力与创新能力，错失应对气候变化、社会凝聚力和教育等紧迫社会挑战的良机。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">2.职场转型挑战\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">AI与工作场所的融合催生了两种路径间的张力：一种聚焦自动化与效率提升，另一种则强调人类能力的增强与赋能。这种二元对立对劳动力发展、工作质量以及学习与工作的融合具有深远影响。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">在图景A中，自动化技术被用于将劳动者从程式化任务中解放，使其能投身目标导向的职业发展并投资于有意义的工作。这形成了技能提升与再培训的良性循环——劳动者可转向更高价值的岗位，雇主则能获得技能更精湛、投入度更高的劳动力。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">与之形成鲜明对比的是图景B所展现的割裂图景：部分企业利用AI增强人类能力，另一些则优先考虑岗位替代。这导致职场出现阶层分化：部分劳动者在技术赋能的动态环境中蓬勃发展，另一些则被局限在重复性、低技能且职业前景有限的岗位上。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">图景D的展望更为严峻——AI技术取代了多数人类岗位，迫使劳动者与机器争夺日益减少的工作机会。个体丧失对职业轨迹的掌控权，因不可抗力频繁遭遇非自愿的职业变更。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">但同样存在中间路线，如图景C所示：AI以相对平稳的共存模式辅助人类。在此图景下，许多岗位仍依赖经AI解决方案强化的技术能力，基于重复性任务的岗位并未被大规模替代。工作岗位与职责渐进式演变而非剧烈颠覆，使得技能需求保持适度——除非身处技术变革冲击最显著的行业。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">3.学习、指导与咨询服务的转型\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">将AI融入学习、指导及咨询流程，对提升这些服务的质量与效能具有重大潜力。然而，要实现这些优势，取决于能否建立并实施负责任的框架、以人为本的设计原则以及优先保障学习者自主权与福祉的决策机制。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">在图境A中，AI的进步使得创建个性化、自适应学习环境成为可能，这些环境能精准满足个体的独特需求与偏好。该方法有望推动教育领域实现更高程度的包容性与公平性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">相反，图境B与图境D（尽管程度不同）都凸显了加剧教育不平等、进一步边缘化弱势群体的风险。此外，这些图境还警示了过度依赖由技术平台和AI驱动培训系统主导的学习生态可能引发的后果，包括加剧社交孤立、提升焦虑水平以及对身心健康造成负面影响。而在图境C中，AI仅作为辅助工具支持学习、指导与咨询实践，并未动摇专业从业者的核心角色。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">4.个体责任鸿沟\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">社会日益期望个人自主掌握技能发展与职业规划，这对那些缺乏必要能力、资源或支持的人来说尤为困难。这种鸿沟可能加剧现有的社会经济差距——处于弱势背景的个体往往难以应对快速变化的就业市场，也难以获得技能提升与转型的机会。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">在图景B和D中，这一问题尤为突出，劳动者被迫独自应对挑战；而图景A和C则展现出更乐观的前景，个体能更好地适应劳动力市场的变化。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">5.就业格局的演变\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">当前就业格局正经历深刻变革，其显著特征是传统雇佣模式与非传统且往往不稳定的就业形式并存发展。这种转变呈现出明显的区域与行业差异，既影响着劳动者的职业安全与利益代表机制，也对社会对话和集体协商构成挑战。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">不同图景下转型的速度与性质各异：情景A呈现平稳过渡，劳动者通过灵活工作安排为多重雇主提供服务并从中获益；图景B与图景D则展现更剧烈的转变——传统雇佣关系被微任务、项目制工作和临时性关系所取代，但结果截然不同——图景B催生出新型劳动者代表机制，而图景D中工会力量的式微使得劳动者丧失维护权益的强有力发声渠道；图景C展现出更复杂的图景，非传统就业形式仅适度增长，但滞后的社会对话机制难以构建与之匹配的社会保护网络，同时工会参与度持续走低。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">6.日益扩大的不平等\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">个体、地区、企业、职业和行业之间适应技术变革能力不同，导致不平等加剧。这造成了有机会获取资源者与无缘机会者之间的鸿沟。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">图景B和D会恶化这一问题——远程办公与人工智能技术分别催生出\"机会荒漠\"与地域两极分化，进而引发人才外流、优质教育与就业机会匮乏，使不平等现象持续固化。相较而言，图景C呈现复杂图景：AI红利未能普惠共享；而图景A则展现出乐观前景：经济繁荣，不平等现象减少，但前提是数字鸿沟得到管理且机会具有包容性。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">四、对社会对话的启示\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">这四种图境对利益相关方的角色责任及社会对话的演变产生了深远影响。理解这些变化对于构建各方共同认可、持续推进技能发展的统一愿景至关重要。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">初步分析表明，传统社会对话模式亟需调整转型，以应对格局变迁带来的挑战与机遇。在图境A与C中，劳资关系预计将保持相对稳定，但两者社会对话的本质差异显著。图境A通过工会、雇主组织与政府的协同努力强化社会对话，三方共同应对技术变革的挑战与机遇。非传统雇佣形式日益凸显的重要性，促使工会将服务范围拓展至传统劳动合同未覆盖的劳动者，确保所有工作者都能获得代表与保护。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">图境C在未发生系统性大规模裁员的前提下，社会对话更具情境敏感性，着力精准识别技能需求并开发适配的培训方案，确保所有学习者群体都不掉队。虽然特定行业可能需要对新型工作组织与雇佣模式做出重大调整，但整体而言社会对话聚焦于推动终身学习与技能发展。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">相比之下，图境B与D为社会对话带来了更具挑战性的格局，其特征表现为碎片化、被动应对与战略规划缺失。图境B显著偏离传统三方对话机制，转向以企业专属谈判为主、仅限定基础框架条件的碎片化被动协调模式，导致战略规划与主动参与缺位，谈判内容局限于短期利益与损害管控。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">图境D中，传统产业关系与集体协商机制的瓦解严重削弱了社会对话，劳动者与弱势群体丧失有效发声渠道。由此产生的谈判呈现碎片化与被动性特征，雇主与企业利益被置于劳动者权益之上，就业保障、工作条件与环境可持续性等关键议题遭到忽视。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">所有图境都迫切要求适应工作性质与经济形态的变革。这需要各方积极探索新型劳动者代表机制与社会保护形式，将终身学习与技能发展置于优先地位，并确保所有工作者在决策过程中享有话语权。唯有如此，社会对话才能在构建更具包容性与公平性的经济生态中发挥关键作用——让AI与技术进步的福祉惠及全体劳动者，使劳动者权益得到切实保障与提升。\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(136, 136, 136);\">【新闻来源】国际与比较教育研究所\u003C\u002Fspan>\u003Ca href=\" https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002Fmzzy7F-6NGpLDkMsy1w69g\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\"> https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002Fmzzy7F-6NGpLDkMsy1w69g\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(136, 136, 136);\">（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\u002F12\u002Fe8ccf3f5ae9b47b4ac45b69df78ed65b\u002Fd3ceb214-e320-4d27-b9ff-62bd5ab11fa0.jpg","https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002Fthumbs\u002Fe8ccf3f5ae9b47b4ac45b69df78ed65b\u002Fd3ceb214-e320-4d27-b9ff-62bd5ab11fa0.jpg",0,1,59,"2025-12-15 08:48",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%3Ab0d2c61e-910f-476a-9c4b-afc4cd97af50%3A0.wav?Expires=1765768600&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=Q3YpV6E%2BQiYps20mfhMD1gTR1Qg%3D",28291530,"b0d2c61e-910f-476a-9c4b-afc4cd97af50","2025-12-12 08:33","AI-driven Future Skills Development Landscape Released","\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px; color: rgb(255, 153, 0);\">Recently, the European Centre for the Development of Vocational Training (Cedefop) published a 133-page research paper titled \"Preparing for 2040: Four AI-powered scenarios for the future of continuing skills development.\" The paper outlines the possibilities of skill development driven by AI in the coming decades, aiming to guide stakeholders in building a resilient, inclusive, and future-ready continuous skills development ecosystem for 2040. The main content of this research paper is summarized as follows.\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">I. Background and Research Methods\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The paper begins by pointing out that traditional, education institution-centered continuing vocational training models are no longer sustainable in today's context of technological disruption, demographic changes, and increasingly severe climate challenges. Future skill development must be a continuous process throughout an individual's career and various life scenarios, deeply integrating institutional learning, self-directed learning, and workplace learning. Among all future trends, AI, due to its huge potential and high uncertainty, has become the most critical driving force, thus requiring adaptive strategies to leverage its potential.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">To address future challenges and gain deeper insights into potential opportunities in the field of continuous skills development, Cedefop launched this strategic foresight research project, aiming to build a shared vision for continuous skills development towards 2040, design alternative scenarios, and develop strategic objectives.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">During the research process, the paper comprehensively utilized methods such as scenario building, scenario exploration, and vision building. The scenario building phase included: identifying key trends that will affect the future of continuous skills development; analyzing their potential impacts and uncertainties; using morphological analysis to identify different evolution paths; developing scenario outlines; and validating the scenario outlines through semi-Delphi surveys.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cimg alt=\"undefined\" src=\"https:\u002F\u002Fimage.51xinwei.com\u002F2025\u002F12\u002F80fba42275bf4e2dad6cee0f53ae4efa\u002F企业微信截图_20251215084737.png\" width=\"341\" height=\"undefined\" style=\"display: block; margin: auto;\">\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">This process ultimately formed four scenarios, each exploring how various characteristics and conditions related to continuous skills development may evolve by 2040 from different perspectives. Throughout the research process, Cedefop collaborated with diverse stakeholders, including futurists and domain experts, policymakers at all levels, employee and employer representatives, civil society organizations, and educational\u002Ftraining\u002Fvocational guidance institutions, to ensure that the research outcomes integrate multidimensional perspectives and professional wisdom.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">II. Four AI-Powered Scenarios for Continuous Skills Development\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">These four scenarios revolve around AI application trends and their interactions with other trends, outlining multiple possible future scenarios. Based on trend analysis and morphological analysis, AI was found to have the highest potential impact on future adult continuous skills development processes among all identified trends. In two iterations of trend analysis, experts consistently rated all AI-related trends as highly impactful (affecting most other trends) and highly uncertain (experts differ in their assessments of the speed and scale of AI trends).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">These future scenarios cover two extremes: from a positive outlook where AI enhances human capabilities and promotes social well-being, to a bleak future where AI is mainly used for control and profit maximization, leading to mass unemployment and widespread lack of job security and benefits.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">These scenarios are not predictive but exploratory tools aimed at identifying areas of concern, threats to be addressed, and opportunities to be seized. By exploring potential future development paths, these scenarios can provide a basis for building a shared vision for continuous skills development and guiding the formulation of strategic goals for 2040.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The core assumptions and driving trends of each scenario can be summarized as follows:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">1. Scenario A: A Future Full of Opportunities - Technology-Driven Talent Competition\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">By 2040, the EU labor force is continuously shrinking due to an aging population and slowed migration flows. However, economic prosperity and the creation of numerous new jobs are driven by technological innovation and AI. Although business activities thrive, recruitment difficulties continue to intensify due to the reversal of the supply-demand relationship for skills and the widening skill gap, making talent competition more intense than ever before. Labor markets are becoming increasingly tight.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Most workers and companies benefit from AI development. Human-centric skills remain crucial. For more employers, retaining talent becomes the top priority. Career choices driven by purpose form a trend, becoming an increasing number of people's life options. Technological change and the need for continuous skill enhancement push learning environments to be more deeply integrated into the workplace. The boundaries between institutional education and training will continue to blur, possibly even disappearing entirely.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The skills development system will be more flexible, accessible, and responsive, better meeting the diverse needs of the workforce, providing smoother transitions and progression channels for individual learning journeys. Ultimately, non-traditional emerging participants will become regular creators of learning content.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">2. Scenario B: Navigating the Waves Alone - Sailing Through the Impact of AI on Employment\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">By 2040, the continuous waves of AI transformation have completely reshaped the employment landscape, having a strong impact on the labor market, affecting different groups in drastically different ways. As countries and employers gradually withdraw from the field of labor skill development, most working-age individuals can only rely on themselves — they struggle to keep up with the technological waves, trying to maintain their skills, but with varying degrees of success.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Some master the waves, while others struggle to survive, forming what we now call the \"two-tier labor structure.\" AI is impacting the majority of professions and industries in Europe, and individuals must take responsibility for continuous skill enhancement. This transformation is difficult to control, and only a few groups can benefit from it. Others face adaptation difficulties, sacrificing mental health, physical health, and socio-economic well-being to keep their jobs.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">3. Scenario C: Struggling to Maintain - Missing Out on AI Opportunities\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">By 2040, AI continues to develop but at a slow pace, bringing moderate changes rather than widespread impacts on work tasks and jobs. This pace is generally manageable by employers, workers, and EU member states, with gradual adjustments usually sufficient to cope with the changes.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">At the same time, due to unequal investment and participation in AI across industries, member states, and different groups, the potential of AI to improve socio-economic conditions remains underutilized. The changes are within manageable limits, with some groups benefiting, but most missing out on opportunities, while others continue to struggle.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The importance of skill development and skill application remains at current levels, with no significant change in the proportion of people who plan their careers independently. Educational and training options have not yet achieved deep integration. Learning content is still primarily provided by traditional entities. The impact of AI on learning, teaching, and career guidance remains limited.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">4. Scenario D: AI Out of Control - Dominating the Workplace and Society\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">By 2040, AI technology and automation have fully permeated all aspects of life and work, profoundly restructuring the social structure, leading to unprecedented waves of unemployment across all industries, sectors, and skill levels. A few major players controlling the AI ecosystem exert significant influence over policymakers, economies, and societies.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">For workers, this transformation is disruptive. As AI takes over most tasks, workers are increasingly employed in non-standard contracts, with significantly reduced opportunities for skill development, job security, and benefits. Companies are unwilling to invest in \"disposable\" labor, focusing only on training a few employees in advanced AI-related skills. Workers are forced to bear the responsibility of skill enhancement independently, struggling to cope with frequent involuntary career changes.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The decline of traditional employment models and union positions weakens union power, leaving workers without strong advocates for their rights. Regulatory gaps lead to power imbalances, not only threatening democratic systems but also exacerbating environmental degradation. AI completely transforms the skills development system: the boundaries between formal and informal education and training gradually blur, and new AI-driven tools and job roles continuously emerge.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">III. Common Issues and Contradictions\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Despite differences, these scenarios still show several common features and reveal a complex and diverse landscape of future challenges and opportunities. These underlying issues vary in intensity across different scenarios, but they are crucial when building a future vision for continuous skills development and its strategic objectives.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">1. The Dual Potential of AI\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">AI has great potential to enhance human capabilities, drive innovation, and improve social outcomes. In Scenario A, AI is used to create new opportunities for economic growth, social mobility, and environmental sustainability, thereby improving the quality of life for individuals, economies, and societies.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">However, the dual nature of AI also brings significant risks—particularly when its deployment is mainly controlled by power and profit motives. As shown in Scenario D, uncontrolled AI development could lead to concentration of power and wealth, exacerbate socioeconomic inequality, and erode democratic systems.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Additionally, the impact of AI may present more subtle complexities, as demonstrated in Scenario B: uneven distribution of benefits and impacts. Advantageous groups can use AI to consolidate their position, while marginalized groups face重重 obstacles in accessing opportunities, participation, and social mobility.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">But there are also risks of insufficient AI application, as depicted in Scenario C—the lack of investment in AI and failure to realize its potential will lead to stagnation and complacency, eventually losing competitiveness and innovation, missing the opportunity to address urgent social challenges such as climate change, social cohesion, and education.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">2. Challenges of Workforce Transformation\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The integration of AI with the workplace has created tensions between two paths: one focused on automation and efficiency improvement, and the other emphasizing the enhancement and empowerment of human capabilities. This binary opposition has profound implications for workforce development, work quality, and the integration of learning and work.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">In Scenario A, automation technologies are used to free workers from routine tasks, allowing them to pursue goal-oriented career development and invest in meaningful work. This creates a virtuous cycle of skill enhancement and retraining—workers can move to higher-value positions, and employers can obtain more skilled and committed labor forces.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">In contrast, Scenario B presents a fragmented picture: some companies use AI to enhance human capabilities, while others prioritize job replacement. This leads to a stratification of the workforce: some workers thrive in a dynamically empowered environment, while others are confined to repetitive, low-skill, and limited career prospects jobs.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Scenario D presents a more severe outlook—AI replaces most human jobs, forcing workers to compete with machines for increasingly scarce job opportunities. Individuals lose control over their career trajectories, frequently facing involuntary career changes due to uncontrollable circumstances.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">However, there is also a middle path, as shown in Scenario C: AI coexists relatively smoothly with humans. In this scenario, many jobs still rely on AI-enhanced technical capabilities, and jobs based on repetitive tasks are not replaced on a large scale. Jobs and responsibilities gradually evolve rather than being drastically disrupted, keeping skill demands moderate—unless in industries most significantly affected by technological changes.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">3. Transformation of Learning, Guidance, and Advisory Services\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Integrating AI into learning, guidance, and advisory processes has significant potential to improve the quality and effectiveness of these services. However, realizing these advantages depends on establishing and implementing responsible frameworks, human-centered design principles, and decision-making mechanisms that prioritize learners' autonomy and well-being.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">In Scenario A, AI advancements make it possible to create personalized, adaptive learning environments that precisely meet individual unique needs and preferences. This approach has the potential to promote a higher degree of inclusiveness and fairness in education.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Conversely, Scenarios B and D (albeit to different extents) highlight the risk of increasing educational inequality and further marginalizing vulnerable groups. Additionally, these scenarios warn about the consequences of over-reliance on learning ecosystems dominated by technology platforms and AI-driven training systems, including increased social isolation, heightened anxiety, and negative impacts on mental and physical health. In Scenario C, AI serves only as an auxiliary tool supporting learning, guidance, and advisory practices, without undermining the core role of professionals.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">4. The Gap in Individual Responsibility\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Society increasingly expects individuals to take charge of their own skill development and career planning, which is particularly challenging for those lacking necessary abilities, resources, or support. This gap may exacerbate existing socioeconomic disparities—individuals from disadvantaged backgrounds often struggle to adapt to rapidly changing labor markets and access opportunities for skill enhancement and transition.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">This issue is particularly prominent in Scenarios B and D, where workers are forced to tackle challenges alone; while Scenarios A and C offer a more optimistic outlook, where individuals can better adapt to changes in the labor market.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">5. Evolution of the Employment Structure\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The current employment structure is undergoing profound changes, characterized by the coexistence of traditional employment models and non-traditional, often unstable forms of employment. This transformation shows clear regional and industry differences, affecting both workers' job security and representation mechanisms, as well as posing challenges for social dialogue and collective bargaining.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">The speed and nature of transformation vary across different scenarios: Scenario A presents a smooth transition, with workers benefiting from flexible work arrangements serving multiple employers; Scenarios B and D showcase more drastic changes—traditional employment relationships are replaced by micro-tasks, project-based work, and temporary relationships, but with contrasting outcomes—Scenario B gives rise to new worker representation mechanisms, while Scenario D sees the weakening of union power, leaving workers without effective channels to voice their rights; Scenario C presents a more complex picture, with non-traditional employment forms growing moderately, but lagging social dialogue mechanisms struggle to build matching social protection networks, while union participation continues to decline.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">6. Widening Inequalities\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Differences in the ability of individuals, regions, companies, occupations, and industries to adapt to technological changes lead to worsening inequalities. This creates a gap between those who have access to resources and those who do not.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Scenarios B and D worsen this issue—remote work and AI technology respectively create \"opportunity deserts\" and regional polarization, leading to brain drain, lack of quality education and employment opportunities, and perpetuating inequality. In contrast, Scenario C presents a complex picture: AI benefits are not evenly distributed; while Scenario A shows an optimistic outlook: economic prosperity, reduced inequality, but with the caveat that the digital divide must be managed and opportunities must be inclusive.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cstrong style=\"font-size: 18px;\">IV. Implications for Social Dialogue\u003C\u002Fstrong>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">These four scenarios have profound implications for the roles and responsibilities of stakeholders and the evolution of social dialogue. Understanding these changes is crucial for building a shared vision that is recognized by all parties and continues to promote skills development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Preliminary analysis indicates that traditional social dialogue models urgently need to be adjusted and transformed to address the challenges and opportunities brought by the changing landscape. In Scenarios A and C, labor relations are expected to remain relatively stable, but there is a significant difference in the essence of social dialogue. Scenario A strengthens social dialogue through coordinated efforts among unions, employer organizations, and governments to jointly address the challenges and opportunities of technological change. The increasing importance of non-traditional employment forms prompts unions to expand their service scope to include workers not covered by traditional employment contracts, ensuring all workers receive representation and protection.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">Scenario C, without systemic large-scale layoffs, exhibits greater contextual sensitivity in social dialogue, focusing on accurately identifying skill needs and developing tailored training programs to ensure no learner group is left behind. Although certain industries may require significant adjustments to new work organization and employment models, overall social dialogue focuses on promoting lifelong learning and skills development.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">In contrast, Scenarios B and D present more challenging landscapes for social dialogue, characterized by fragmentation, passive response, and a lack of strategic planning. Scenario B significantly deviates from the traditional tripartite dialogue mechanism, shifting toward a fragmented, passive coordination model centered on corporate-specific negotiations, resulting in a lack of strategic planning and active participation, with negotiation content limited to short-term interests and damage control.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">In Scenario D, the collapse of traditional industrial relations and collective bargaining mechanisms severely weakens social dialogue, leaving workers and vulnerable groups without effective channels to voice their concerns. The resulting negotiations exhibit fragmented and passive characteristics, with employer and corporate interests taking precedence over workers' rights, and key issues such as employment security, working conditions, and environmental sustainability are neglected.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"font-size: 18px;\">All scenarios urgently require adaptation to changes in the nature of work and economic forms. This requires exploring new mechanisms for representing workers and forms of social protection, placing lifelong learning and skills development at the forefront, and ensuring all workers have a voice in decision-making processes. Only in this way can social dialogue play a key role in building a more inclusive and equitable economic ecosystem—ensuring that the benefits of AI and technological progress reach all workers, and that workers' rights are genuinely protected and enhanced.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(136, 136, 136);\">【News Source】 Institute for International and Comparative Education\u003C\u002Fspan>\u003Ca href=\" https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002Fmzzy7F-6NGpLDkMsy1w69g\" rel=\"noopener noreferrer\" target=\"_blank\" style=\"color: rgb(136, 136, 136);\"> https:\u002F\u002Fmp.weixin.qq.com\u002Fs\u002Fmzzy7F-6NGpLDkMsy1w69g\u003C\u002Fa>\u003C\u002Fp>\u003Cp class=\"ql-align-justify\">\u003Cspan style=\"color: rgb(136, 136, 136);\">（This article is reprinted by this site 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 in the article, please verify with the relevant parties. The views expressed in the article are not the views of this site, and are for reference only.）\u003C\u002Fspan>\u003C\u002Fp>","https:\u002F\u002Fxinwei-dev-test.oss-cn-shenzhen.aliyuncs.com\u002Fintelligent\u002Faudio%3Adf57cdc8-43a6-4b38-83dc-40866d8de5de%3A0.wav?Expires=1774838443&OSSAccessKeyId=LTAI5tNvY2RkKjZw4LLWsrPK&Signature=1SgztLZDigzBrd91Yzo4n1idFLw%3D","df57cdc8-43a6-4b38-83dc-40866d8de5de",17431862]