MOE 演讲稿 · 2026-04-01
教育部长李智陞先生在海峡时报（ST）教育论坛「高等教育中的人工智能——炒作还是希望」的讲话
教育部长李智陞先生在海峡时报（ST）教育论坛「高等教育中的人工智能——炒作还是希望」的讲话
要点
- • 教育部的「四项学习」框架指导学生的AI准备：学习什么是AI、学习如何使用AI、与AI共学，以及超越AI而学以保持人类掌控。
- • 小学从小学四年级开始系统地引入AI，采取密切监督和低初期接触，随后根据教学实践逐步增加使用。
- • 新加坡国立大学的AI评分工具用于英文能力测试，每年为3000多名学生评分，准确率达95%以上，每年节省超过100个工作日。
- • 教育区分了「横向」AI能力（AI擅长的通用任务如写作和总结）和「纵向」能力（需要人类判断的领域专业知识）。
- • 未来的课堂和校园模式以四项关键转变为中心：基于探究的学习、实践应用、跨学科协作和对变化需求的适应性。
完整译文（中文）
MOE 英文原文译文 · 翻译日期: 2026-08-24
Karamjit Kaur女士，《海峡时报》副编辑。我的各位对话嘉宾
1. 下午好。很高兴能与你们和我们的对话嘉宾一起讨论人工智能对我们教育格局的影响。
2. 事实上，几周前我在爱沙尼亚的塔林参加了国际教学专业峰会（ISTP）。我们在新加坡面临的挑战和问题，无论是在普通教育还是高等教育领域，对我们来说并非独有的。这些问题正在世界各地被应对。
3. 人工智能以惊人的速度发展，生成式人工智能系统现在已广泛可供学生、教育工作者和工作人员使用。因此，我们可以预期我们学习、工作和生活的方式会发生重大变化。其中一些变化将会突然爆发，而一些则会缓慢蔓延。
4. 这给我们提出了根本性的问题：如果思考和行动越来越可以由机器完成，那么作为人类、作为个人，我们的角色将是什么？
5. 那么，我们的高等教育机构（IHL）的角色是什么？这些机构长期以来一直致力于为我们的人民提供知识、技能和价值观，以便他们能够茁壮成长。
6. 要回答这个问题，回顾教育如何演变可能会很有用。教育系统从来都不是静止的。它们一直在随着社会、经济和技术的变化而不断适应。
7. 中世纪欧洲最早的大学，如牛津大学，是以对话和辩论为中心的小型学术共同体。学习通过讲座和口头答辩进行。当时知识稀缺，通过手写手稿仔细传递。
8. 几个世纪后，欧洲和美国研究型大学的兴起改变了我们所知的高等教育。
9. 实验室、科学探究和学科专业化蓬勃发展——特别是在工业时代和20世纪科学和工程进步的时期。
10. 大学成为不仅传承知识，而且创造知识的场所。
11. 在新加坡，我们的高等教育机构（IHL）也同样随着时间的推移而演变。
12. 我们的大学最初专注于基础学科，培训新兴国家所需的专业人员。
13. 随着时间的推移，我们通过加强跨学科学习、建立研究能力以及通过新加坡理工学院（SIT）和新加坡社科大学（SUSS）等大学开发应用途径来扩展和多样化。
14. 同样，我们的理工学院和工教院（ITE）最初成立是为了培训技术技工以支持新加坡的工业化。
15. 这些机构随后从纯粹提供技术培训发展为在包括艺术、设计和媒体、商业、卫生科学等众多学科中培养工作准备就绪的毕业生。
16. 我们还加强了继续教育和培训（CET），我们的高等教育机构在SkillsFuture运动中发挥了重要作用。
17. 在技术周期变短的时代，终身学习变得越来越重要，我们需要不断更新我们的知识和技能。
18. 今天，我们正在见证又一次重大的技术转变。
19. 在短短几年内，我们看到了人工智能系统变得有多么强大和广泛。ChatGPT已成为家喻户晓的名字，每一代新的生成式人工智能模型都比前一代更强大。
20. 这些发展既带来了机遇也带来了风险。
21. 对于我们的学生来说，人工智能可以提供更个性化和定制的教育体验。然而，也存在这样的风险：人工智能可能成为绕过思考和学习的捷径，导致认知卸载，使学生对人工智能输出过度依赖或信任。
22. 对于劳动力来说，人工智能可以增强人类能力，使工作者的生产力大幅提高。
23. 这对新加坡等小国特别有价值。
24. 但人工智能也可能造成经济混乱，实质上重塑工作角色和需求的技能。
25. 这些机遇和风险促使我们所有人做出反应。无论我们是否准备好，人工智能已经来临，并且正在快速发展——我们的学生已经在使用它，公司正在竞相将人工智能融入他们的工作流程。
26. 但前进的道路并不清晰，即使行业领导者对人工智能将如何完全改变他们的部门也不确定。
27. 因此，我们必须摸着石头过河，不能采取观望的态度。在我们的学校和高等教育机构（IHL）中，我们需要学习、适应和成长。
28. 我们的学校必须帮助我们的学生进入劳动力市场，准备好在人工智能时代增加价值。
29. 我们还必须通过继续教育和培训（CET）帮助现有工作者提升技能，用明天工作所需的新技能来增强他们的经验和技能。
30. 那么问题是——我们如何实现这一点？
31. 越来越多的，我们的工作将从知识的常规应用转向判断、创意和创新、建立关系以及与人和智能系统的协作。
32. 为了更好地理解AI如何重塑工作，有必要区分一些人所说的「水平」和「垂直」能力。
33. 水平能力是指跨越许多工作的广泛、通用任务——例如写作、总结信息或准备演示文稿。这些是AI已经非常有效并快速改进的领域。
34. 另一方面，垂直能力是特定领域的，建立在深层专业知识基础上。它们涉及在复杂的现实世界环境中应用知识，其中判断、经验和责任至关重要。这种垂直专业知识仍然更难被复制。
35. 这就是为什么教育必须有意图地演变。
36. 我们必须不仅要让学生具备使用「水平」AI工具的能力，而且要让他们具备在「垂直」应用中良好使用这些工具的深厚知识、经验和判断力，这些应用将成为真正的游戏改变者。
37. 为了指导我们如何开发这些能力，教育部推出了一个我们称之为四个「学」的共同框架，以使我们的学生为AI做好准备。它们是什么？
38. 首先，学习关于AI。学生需要了解什么是AI、它如何工作、它的影响是什么以及它的限制是什么。随着技术的发展，这些内容仍在不断变化。
39. 第二，学习如何使用AI。学生将学习如何有效且负责任地利用AI工具。
40. 第三，与AI一起学习。教育工作者将在教学和学习中融入AI，以增强我们的学生成果和学习。
41. 第四，最重要的是，超越AI学习，以便我们保持技术的主人。当AI可以即时产生输出时，评估、质疑和对这些输出负责的能力变得不可或缺。
42. 我们的学校和高等学府必须继续在学生身上培养这些人类能力。这些能力必须在教育的不同阶段逐步建立。
43. 在每个阶段，我们必须努力建立牢固的基础。学生必须首先在核心概念和深入的学科知识中建立坚实的基础。
44. 即使在信息可以轻松访问或由AI生成的时代，这些基础知识仍然是必不可少的。
45. 实际上，我们认为那些最能够使用AI的人是那些具有最深层专业知识的人，因为他们可以提出更好的问题、更批判性地解释输出、有意义地应用它们，并利用AI来突破界限。
46. 除了深入的知识外，我们还必须磨练深层直觉、加强批判性思维，并让学生扎根于强有力的道德和伦理判断。
47. 因此，我们一直致力于仔细调整我们的方法：
48. 对于年幼的学生，我们将优先学习基础知识。大部分内容涉及触觉学习、在课堂和户外课堂中的真实世界物理学习。
49. 因此，我们仅在小学4年级引入AI，在密切监督下进行，接触程度低。
50. 此后，我们根据教学实践逐步增加AI的使用。在这个阶段，AI应该像教师一样运作——促使学生思考并向他们提问、指导他们进行学习——而不是直接给予答案或提供懒惰的捷径。
51. 在高等学府级别，学生必须一方面利用AI，另一方面加深独立思维——学会自信地质疑、分析、创建和交流。
52. 综合起来，这些转变将从根本上重塑课堂和校园。未来的课堂和校园需要以四个关键转变为基础：探究、应用、协作和适应性。
53. 为了实现这一愿景（这是正在进行的工作），我们必须重新思考教育工作者如何教授学生和开展工作，涵盖三个主要领域。
54. 首先，AI用于生产力。我们的教育工作者和机构必须找到利用AI的方法来改进他们在高等学府的管理、减少重复任务，或进行设置以便教育工作者能够专注于教学，从而释放带宽来专注于与学生在教室和实验室中的有意义互动。
55. 例如，NUS、NTU、SIT和SUTD的教育工作者已经开始使用AI工具来支持学生作业的评分。
56. NUS用于评分英语能力测试的AI工具每年用于评分超过3,000名学生，确保准确率超过95%，每年的时间节省超过100个人·天。
57. 对于学生来说，AI评分还提供了更高的一致性和更公平的结果，因为AI不会显示评分者间的变异性。
58. 尽管如此，所有AI辅助评分仍然必须由教育工作者审查和监督，他们最终保留对最终成绩准确性的完全责任。这对我们的学生很重要。
59. 我们在ITE的同事也获得了AI工具，例如D2L Lumi Pro，这些工具帮助教育工作者生成其教学材料的初稿，他们可以根据学生的学习需求进行调整和定制。
第二，用于教学的人工智能。我们必须重新思考教学和学习的进行方式。例如，通过将人工智能工具直接融入教学和学习中，同时建立适当的防护措施。
我们五所理工学院——南洋理工学院、义安理工学院、共和理工学院、新加坡理工学院和淡马锡理工学院——的讲师们启动了他们所称的「联合理工学院教育人工智能（AiE）」项目，他们利用人工智能更好地、更系统地早期识别和支持有风险和成绩不理想学生的学习需求，并为这些学生支持数据驱动教学策略的设计。
在新加坡社会科学大学，他们设计了「自适应学习系统」来诊断学习差距，并通过提供个性化支持（如提示和反馈）帮助学习者提升他们的能力。
我们也可能看到人工智能赋能的作业兴起，学生根据他们与人工智能协作解决问题或创建产品的有效性进行评估。
第三，人工智能赋能。我们的课堂必须为学生装备好在人工智能改造的世界中取得成功的能力，其中工作和产业将快速发展。
这包括培养学生在自己学科范围内有意义地应用人工智能的能力。
在新加坡科技设计大学，其城市科学、政策与规划硕士学生设计并主持了一个使用他们自己定制建立的人工智能代理的总体规划讲习班。学生使用生成式人工智能将参与者的想法瞬间转换为视觉效果，提高了讨论的质量，因为参与者可以超越仅仅对话，转而看到并想象他们的想法可能看起来的样子。
人工智能代理也可以提供关于这些想法在技术和基础设施角度是否可行的反馈。想象一下这会给教师和讲师带来什么能力。
在新加坡管理大学，其「用人工智能讲故事」课程的学生使用人工智能生成高质量的多媒体内容，无需广泛的预算或拍摄资源。这使他们能够更频繁和更密集地学习。
为了让你更好地了解这是什么样的，而且因为新加坡管理大学是我们的主办方，我们提出了请求，新加坡管理大学为你准备了一部短视频供观看。
这是我们高等教育机构师资正在试验、尝试和融合人工智能以促进学习的一个例子。
除了教学生如何在各自领域使用人工智能外，我们还需要加强学生的21世纪能力和人工智能今天不易复制的独特人类能力，如批判性思维、自信沟通和跨文化理解。
我们的高等教育机构认识到这一点的重要性。
例如，淡马锡理工学院的毕业生获得了正式的技能成绩单，与学术成绩单一起，展示技术技能以及软技能和课外成就。
新加坡管理大学的课外活动成绩单类似地展示了毕业生通过课外参与所开发的软技能。
我们还必须在学生毕业后长期赋能他们。随着技能需求继续演变，工作者需要在整个职业生涯中不断提升技能。
上月，我们宣布了支持新加坡职场工作者这样做的举措，包括由技能未来和新加坡理工学院开发的简单自诊断工具，帮助个人了解他们的人工智能就绪水平，以便他们可以被指向针对其理解水平的课程。
从今年下半年开始，我们所有的高等教育机构将为其校友提供精选的人工智能相关课程，享受显著折扣，为期一年。
这些举措将帮助我们的工作者在人工智能普遍的经济中刷新他们的技能。
为了将新加坡定位在高等教育人工智能的前沿，我们将建立一个新的高等教育人工智能委员会，领导我们高等教育机构的下一阶段转型。
今天，我们的自主大学、理工学院和工艺教育学院已经拥有各种工作小组，这些小组汇集了教师——不仅在各自机构内，还在机构间——分享人工智能采用的最佳实践，我们已经看到它们如何帮助加快各机构间的学习和创新。
然而，随着人工智能不断迅速发展并重塑教育格局，需要在系统层面做更多工作，以在整个高等学习领域集体识别机遇并应对挑战。
因此，我们加倍努力，通过建立这个新的高等教育人工智能委员会来加强我们的工作，我将担任主席。
该委员会还将包括教育部高级政务次长普杰立医生，以及我们自主大学的校长和所有理工学院和工艺教育学院的校长和首席执行官。
为了推动对高等教育人工智能更具战略性和协调的方法，该委员会将服务于两个关键目的。
首先，提供战略方向、方向引导和监督，以加强我们的高等教育机构在关键人工智能优先事项上的协调和协作，即使每个高等教育机构继续用人工智能进行实验和创新。
其次，深化我们的高等教育机构之间在高等教育中使用人工智能的最佳实践、经验和新兴发展的分享。
通过在领导层加强分享和协调，以及支持技术和工作层面的工作小组架构，我们可以基于现有努力并以更大的目标和雄心迈进，不仅适应变化，而且当我们校园的高等学习未来演变时积极主动地塑造它。
除了建立高等教育人工智能委员会外，教育部我的同事还将加强关于人工智能如何能推进高等教育阶段教学和学习的研究，通过支持我们高等教育研究基金的机构间人工智能项目。
这将汇集教育工作者和研究人员，探索创新的学习方法，就什么有效生成证据，并将这些洞察转化为我们机构的教学实践。
这项高等教育部门的工作也支持我们更广泛的国家人工智能战略，这将由新的国家人工智能理事会领导，由总理黄循财担任主席。
总而言之，新加坡在教育中应用人工智能的方法既不应该危言耸听，也不应该自满。我们将继续谨慎地进行实验，作为整体系统快速学习，必要时进行调整。
那么，正如今天会议的主题所问的「高等教育中的人工智能是炒作还是希望」？我认为这取决于我们如何回应。
如果我们把人工智能当作捷径，仅仅用来绕过思考，我们就会削弱教育的根本目的。但如果我们把人工智能当作催化剂，一种使教育中真正重要的东西更加敏锐的工具，它就能加强我们的高等学府（IHLs）并强化我们的人民。
应对这一转变需要集体努力。政府机构、我们的高等学府（IHLs）、产业合作伙伴、教育工作者和学生本身必须合作，分享观点，负责任地开展实验，并分享来自全球发展的学习要点。这将有助于确保新加坡在受人工智能影响的世界中保持竞争力。
因此，在这方面，我重视你们在稍后对话中的观点和想法。谢谢。
英文原文
MOE 官网原始记录 · 抓取日期: 2026-08-24
Ms Karamjit Kaur, Associate Editor, The Straits Times My fellow panellists
1. Good afternoon. I'm very glad to be here with you and our panellists to discuss the impact of AI on our education landscape.
2. In fact, a couple of weeks ago I was in Tallinn, Estonia, for the International Summit on the Teaching Profession (ISTP). The challenges and issues that we are grappling with here, both in general education and higher education in Singapore, are not unique to us. They are issues that are being grappled with all around the world.
3. AI is advancing at a remarkable speed, and Generative AI systems are now widely accessible to students, educators, and workers. So, we can expect big changes in how we learn, work, and live. Some of it will just explode at the seams, and some of it will be incremental creep.
4. This raises fundamental questions for us: If thinking and doing can increasingly be done by machines, what would our role be as humans, as people?
5. And what is the role of our Institutes of Higher Learning (IHLs), which have long been central to nurturing our people with the knowledge, skills and values to thrive?
6. To answer this, it might be useful to step back and consider how education has evolved. Education systems have never been static. They have continually adapted alongside changes in society, economy and technology.
7. The earliest universities in medieval Europe, such as Oxford, were small scholarly communities centred on dialogue and debate. Learning took place through lectures and oral defences. Knowledge then was scarce and carefully transmitted through handwritten manuscripts.
8. Centuries later, the rise of research universities across Europe and America transformed higher education as we know it.
9. Laboratories, scientific inquiry, and disciplinary specialisation flourished – particularly as science and engineering advanced during the Industrial Age and the 20 th century.
10. Universities became not just places to transmit knowledge, but to create it.
11. And in Singapore, our IHLs have similarly evolved over time.
12. Our universities began by focusing on foundational disciplines, training professionals needed for a fledging nation.
13. Over time, we have expanded and diversified by strengthening interdisciplinary learning, building research capabilities, and developing applied pathways through universities like SIT and SUSS.
14. Likewise, our Polytechnics and ITE were first established to train skilled technicians to support Singapore's industrialisation.
15. These institutions have since evolved from purely providing technical training to preparing work-ready graduates in a wide range of disciplines including the Arts, Design and Media, Business, Health Sciences and so on.
16. We have also strengthened Continuing Education and Training (CET), with our IHLs playing a major role in our SkillsFuture movement.
17. Lifelong learning is increasingly important in an era where technological cycles are getting shorter, and we need to constantly refresh our knowledge and skills.
18. Today, we are witnessing yet another major technological shift.
19. In just a few years, we have seen how powerful and widespread AI systems have become. ChatGPT has become a household name, and each new generation of Generative AI models is becoming more capable than the previous.
20. These developments present both opportunities and risks.
21. For our students, AI can provide more personalised and tailored educational experiences. However, there is also a risk that AI may become a shortcut that bypasses thinking and learning, and causes cognitive offloading, and that students become overly reliant or trusting of AI output.
22. For the workforce, AI can augment human capabilities, enabling workers to be far more productive.
23. This is particularly valuable for small countries like Singapore.
24. But AI can also create economic disruption, substantially reshaping job roles and the skills in demand.
25. These opportunities and risks compel all of us to respond. Whether we are ready or not, AI is here to stay, and it is advancing rapidly – our students are already using it, and companies are racing to incorporate AI into their workflows.
26. But the path ahead is not clear, with even industry leaders uncertain about how AI will fully transform their sectors.
27. So, we must feel the stones as we cross the river, and cannot take a wait-and-see approach. Across our schools and IHLs, we need to learn, adapt, and grow.
28. Our schools must help our students emerge into the workforce ready to add value in an AI age.
29. We must also help our existing workers upskill through CET to augment their experience and skills with new skills needed for tomorrow's jobs.
30. And so the question is – how will we do this?
31. Increasingly, our work will move away from routine application of knowledge, towards judgement, creativity and invention, relationship-building, and collaboration, with both people and intelligent systems.
32. To better understand how AI is reshaping work, it is useful to distinguish between what some have described as "horizontal" and "vertical" capabilities.
33. Horizontal capabilities are broad, general tasks that cut across many jobs – such as writing, summarising information, or preparing presentations. These are the areas where AI is already highly effective, and improving very rapidly.
34. Vertical capabilities, on the other hand, are domain-specific and built on deep expertise. They involve applying knowledge in complex, real-world contexts, where judgement, experience, and responsibility matter. Such vertical expertise remains harder to replicate.
35. This is why education must evolve in a deliberate way.
36. We must equip students not just with the abilities to use "horizontal" AI tools, but with the depth of knowledge, experience and judgment to use them well in "vertical" applications that will be true game-changers.
37. To guide how we develop these capabilities, MOE has introduced a common framework that we call the four 'Learns', to enable our students to be AI-ready. What are they?
38. First, learn about AI . Students need to know what AI is, how it works, what its impact is, and what its limitations are. And this continues to be dynamic as technology evolves.
39. Second, learn how to use AI . Students will learn how to harness AI tools effectively and responsibly.
40. Third, learn with AI . Educators will incorporate AI in teaching and learning to enhance our student outcomes and learning.
41. Fourth, and most importantly, learn beyond AI so we remain masters of technology. When AI can produce outputs instantly, the ability to evaluate, challenge, and take responsibility for those outputs become indispensable.
42. Our schools and IHLs must continue to nurture precisely these human capabilities in our students. These capabilities must be built progressively across different stages of education.
43. At every stage, we must try to build strong foundations. Students must first develop a firm grounding in core concepts and deep disciplinary knowledge.
44. Even in an age where information can be easily accessed or generated by AI, these fundamentals remain essential.
45. In fact, we think that those who are best able to use AI are those with the deepest expertise, because they can ask better questions, interpret output more critically, apply them meaningfully, and use AI to push the boundaries.
46. Beyond deep knowledge, we must also hone deep instinct, strengthen critical thinking, and ground students in strong moral and ethical judgement.
47. Hence, we have sought to carefully calibrate our approach:
48. For younger students, we will prioritise learning the fundamentals first. And so a lot of that has got to do with tactile learning, real world physical learning in the classroom and in the outdoor classroom.
49. So, we introduce AI only at Primary 4, under close supervision and with low exposure.
50. Thereafter, we increase AI usage progressively, grounded in pedagogical practice. At this stage, AI should seek to function like a teacher – prompting students to think and asking them questions, guiding them to derive learning – rather than spoon feeding answers or giving lazy shortcuts.
51. At the IHL level, students must both leverage AI on one hand and deepen independent thinking on the other – learning to question, analyse, and create and communicate with confidence.
52. Taken together, these shifts will fundamentally reshape the classroom and the campus. The classroom and campus of the future will need to be anchored in four key shifts: Inquiry, Application, Collaboration, and Adaptability.
53. To bring this vision to life, and this is a work in progress, we must rethink how educators teach their students and do their work, across three main areas.
54. First, AI for productivity . Our educators and institutions must find ways to harness AI to improve their administration in the IHLs, to reduce repetitive tasks, or to set up so that they then can go in to teach, so that educators can free up bandwidth to focus on meaningful interactions with students in classrooms and laboratories.
55. For example, educators in NUS, NTU, SIT, and SUTD have begun using AI tools to support the grading of student work.
56. NUS's AI tool to grade English Competency Tests has been used to grade over 3,000 students per year with an assured accuracy of beyond 95%, and the time saving is more than 100 man-days per year.
57. For students, the AI marking also provides higher consistency and fairer outcomes, since AI does not show inter-rater variability.
58. Notwithstanding this, all AI-assisted grading will and must still be reviewed and supervised by educators, who ultimately retain full responsibility for the accuracy of the final grades. And this is important for our students.
59. Our colleagues at ITE are also provided with AI tools such as D2L Lumi Pro, which help educators generate the first cut of their teaching materials, which they can then adjust and customise based on the learning needs of their students.
60. Second, AI for pedagogy . We must reimagine how teaching and learning take place. For example, by incorporating AI tools directly into teaching and learning, with appropriate guardrails in place.
61. Lecturers in our five Polytechnics – Nanyang Polytechnic, Ngee Ann Polytechnic, Republic Polytechnic, Singapore Polytechnic and Temasek Polytechnic – embarked on what they call the Joint Polytechnic Analytics in Education (AiE) project, where they use AI to better and more systematically identify and support the learning needs of at-risk and underperforming students early, and support the design of data-informed teaching strategies for these students.
62. At SUSS, they designed the Adaptive Learning System to diagnose learning gaps and help our learners level up their competencies by providing individualised support such as hints and feedback.
63. We may also see a rise of AI-enabled assignments, where students are assessed on how effectively they collaborate with AI to solve problems or create products.
64. Third, AI for empowerment . Our classrooms must equip students with the capability to succeed in an AI-transformed world, where jobs and industries will evolve rapidly.
65. This includes building up students' ability to apply AI meaningfully within their own disciplines.
66. At SUTD, its Urban Science, Policy & Planning Masters students designed and facilitated a master-planning workshop using their own custom-built AI agents. The students used Generative AI to translate participants' ideas into visuals instantly, enhancing the quality of discussions as participants can move beyond mere dialogue to seeing and visualising how their ideas might look like.
67. The AI agents can also provide feedback on whether the ideas are feasible from the technical and infrastructural angle. And imagine the capabilities this gives the teachers and lecturers.
68. At SMU, its students in the "Storytelling with AI" course use AI to generate high-quality multimedia content without the need for extensive budgets or filming resources. And this allows them to learn more frequently and learn more intensively.
69. To give you a better sense of what this looks like, and because SMU is our host, we made a request, and SMU has prepared a short for your viewing.
70. This is an example of how our IHL faculties are experimenting, trying and weaving AI to enable learning.
71. Beyond teaching students how to use AI in their respective domains, we also need to strengthen students' 21 st century competencies and uniquely human abilities that AI cannot easily replicate today, such as critical thinking, confident communication, and cross-cultural understanding.
72. Our IHLs recognise the importance of this.
73. For example, graduates from Temasek Polytechnic receive an official skills transcript alongside their academic transcript, which showcases both technical skills as well as soft skills and co-curricular achievements.
74. SMU's Co-Curricular Transcript similarly showcases soft skills that graduates have developed through their co-curricular participation.
75. We must also empower our students long after they have graduated. As skills demands continue to evolve, workers will need to upskill all through their careers.
76. Last month, we announced moves to support Singaporeans in the workplace to do this, including a simple self-diagnostic tool developed by SkillsFuture Singapore and the Singapore Institute of Technology to help individuals understand their AI readiness levels, so that they can be directed to courses pegged at their level of understanding.
77. And from the second half of this year, all our IHLs will offer selected AI-related courses at significant discounts for their alumni, for a period of one year.
78. These moves will help our workers refresh their skills in an AI-pervasive economy.
79. To position Singapore at the forefront of AI in Higher Education, we will establish a new Committee for AI in Higher Education to spearhead the next phase of transformation across our IHLs.
80. Today, our Autonomous Universities, Polytechnics, and ITE already have various workgroups that bring faculty members together – not just within their institution, but across institutions – to share best practices in AI adoption, and we have seen how they helped to accelerate learning and innovation across institutions.
81. However, as AI continues to evolve rapidly and reshape the education landscape, more needs to be done at the system-level, to identify opportunities and address challenges collectively across the whole higher learning landscape.
82. Hence, we are doubling down our efforts by establishing this new Committee for AI in Higher Education, which I will chair.
83. This Committee will also include Senior Minister of State for Education Dr Janil Puthucheary, as well as the Presidents of our Autonomous Universities and the Principals and CEOs of all our Polytechnics and ITE,
84. To drive a more strategic and coordinated approach towards AI in Higher Education, this Committee will serve two key purposes.
85. First, to provide strategic direction, steer and oversight, so as to strengthen coordination and collaboration across our IHLs on key AI priorities, even as each IHL continues to experiment and innovate with AI.
86. And second, to deepen sharing of best practices, experiences, and emerging developments in the use of AI in higher education among our IHLs.
87. By strengthening sharing and coordination at the leadership level, and supporting the architecture of workgroups at the technical and working level, we can build on existing efforts and move with greater purpose and ambition, not only adapting to change but seeking to shape it proactively as the future of higher learning in our campuses evolve.
88. Beyond establishing the Committee for AI in Higher Education, my colleagues at MOE will also strengthen research on how AI can advance teaching and learning at the tertiary level, by supporting inter-IHL AI projects through our Tertiary Education Research Fund.
89. This will bring together educators and researchers to explore innovative approaches to learning, generate evidence on what works, and translate these insights into teaching practice across our institutions.
90. This work within the higher education sector also supports our broader AI national efforts, which will be spearheaded by the new National AI Council, chaired by PM Lawrence Wong.
91. To sum up, Singapore's approach to AI in education must neither be alarmist nor complacent. We will continue to experiment carefully, learn quickly as a whole system, and adjust where necessary.
92. So, is "AI in higher education hype or hope" as the theme of today's conference asks? I would say that it depends on how we respond.
93. If we treat AI as a shortcut, to simply bypass thinking, we will diminish the very purpose of education. But if we treat AI as a catalyst, a tool to sharpen what truly matters in education, it can strengthen our IHLs and strengthen our people.
94. Navigating this transformation requires collective effort. Government agencies, our IHLs, industry partners, educators, and students themselves must work together to share perspectives, experiment responsibly, and share learning points from global developments. This will help ensure that Singapore remains competitive in an AI-impacted world.
95. So in that regard, I value your views and ideas during the dialogue later. Thank you.