MDDI 演講稿 · 2026-07-21
Josephine Teo部長在IBM Think on Tour新加坡站的講話
要點
- • 新加坡更新的《國家AI戰略》優先幫助企業採納AI並將其融入業務流程以實現可衡量的商業價值和投資回報率,將重點從個人生產力轉向企業級影響。
- • 新加坡啟動了針對四個關鍵部門的《國家AI任務》——先進製造、醫療、金融和連線——這些部門合計佔國家GDP的40%。
- • 新加坡開發了「AI雙語」專業人才模式,培訓過程工程師、律師和會計師等領域專家,使其將深度領域知識與AI素養相結合,以便與資料科學家有效協作。
- • 兩個互補的計劃支援中小企業AI採納:《國家AI影響計劃》與SaaS平臺合作,而《企業計算倡議》為定製AI解決方案提供補貼計算資源。
- • 《數字領袖加速啟動營》是多方合作計劃,IBM是早期參與者,為業務領導者提供實踐AI經驗、風險意識和組織內可持續、可擴充套件的AI實施方法。
- • 新加坡開發並在東盟各成員國間通過小國論壇分享SEA-LION大語言模型——一個擁有170億引數、針對東南亞語言和文化細微差別最佳化的模型。
- • 新加坡在WEF達沃斯論壇推出了世界上第一個代理AI治理框架,認可自主代理系統產生不同於傳統人為失敗的新型風險,需要新的治理方法。
完整譯文(繁體中文)
MDDI 英文原文譯文 · 翻譯日期: 2026-07-28
主持人Ana Paula Assis,IBM歐洲、中東、非洲及亞太地區高階副總裁兼主席:我經常回到這樣一個想法,即「贏得」企業AI競賽在不同位置看起來是不同的。隨著新加坡更新的國家AI戰略的推出,該戰略引入了部門使命和由總理領導的新AI委員會,顯然你們正在提升新加坡對AI的抱負。從你的角度來看,你能否定義你們所追求的成功版本,以及是什麼促使了這裡的方法轉變?
部長Josephine Teo:我會將我們在更新的國家AI戰略中所做的工作描述為「雙擊」而不是系統重啟。當我們在2023年12月推出國家AI戰略2.0時,我們已經有了一種感覺,即發展速度會非常快,以至於我們一推出檔案,其中的一些部分就已經過時了,它總是需要更新。
但真正有趣的是,當我們實施這項戰略時,我們意識到與以前的技術週期相比,某些事情已經反轉了。對於之前引入的早期技術,我們作為個人的第一次接觸通常是作為勞動力的成員。我們的組織採用了該技術,然後進行了大規模的培訓輪次。我們先在工作中學會了如何使用該技術,然後才意識到該技術可能具有個人應用,並開始在家中使用它。
個人計算機就是這樣。我們對計算機的第一次接觸是在辦公室。對許多人來說,與電子郵件的第一次互動也是在辦公室。但AI是相當不同的。AI真正民主化了對能夠對我們的生活產生深遠影響的東西的訪問。你和我幾乎每天都使用AI。我相當確定,在你的智慧手機和其他裝置上,你已經在使用AI。今天,情況相反:我們可能比我們的組織更廣泛地使用AI。
你們中的許多人可能已經嘗試過vibe coding。你正在構建應用程式來跟蹤你孩子的日程。你正在使用它來掃描網際網路以查詢有趣的文章並將其呈現給你。我有一個代理為我做這件事。
所以這就是差距所在:個人生產力改進的速度比企業生產力更快。然後你考慮更大的挑戰。這項技術如何影響行業?它如何影響整個國家?這就是我們在更新國家AI戰略時的思考。
我們說我們必須更加強調幫助企業採用這項技術並將其整合到現有流程中。對所有企業來說自然而然,也必須有投資回報率。在某個時刻,這必須轉化為商業價值,轉化為美元和美分,產生真實的、有形的好處。所以這就是我們選擇強調的地方。
因此,推動並加快幫助企業,特別是在領導層,思考如何讓這項技術發揮作用的努力,不僅僅是為了個別員工,而是在企業背景下。
例如,我們還與IBM進行合作,針對那些在其組織中負責數字化的領導者。我們希望他們從戰略上思考如何在其運營中使用AI,以及他們如何可能重新思考其業務模式。
我們有一個國家AI影響專案,希望在更大規模上實現這一點。該專案補充了我們也希望通過國家AI使命實現的目標,這些使命更多關於部門的端到端轉型。它們包括先進製造業、醫療保健、金融以及連線性,這些共同對我們的GDP貢獻了40%。我們希望推進這些,以便好處不僅停留在個人水平,而是擴充套件到企業、行業、部門和國家水平。
主持人:繼續下一個問題。你的一個觀點真的引起了我的共鳴,那就是確保AI驅動包容性增長的承諾,而不僅僅是少數人的生產力。再次,我們深入思考AI如何可以增強人們的能力,而不是簡單地替代任務。新加坡如何應對這個機遇,到目前為止你看到了什麼早期進展和見解?
部長:當我們考慮包容性時,它也可以涵蓋多個維度。
個人層面上存在包容性。我們關注勞動力中可能未充分接觸AI如何改變其領域的部分。如果你在技術融合的環境中工作,你很可能會接觸到AI工具。但在一些職業,在一些地區,採用可能滯後,可能需要一些時間。
因此,當我們實施勞動力能力發展專案時,一個領域值得更多關注。我們考慮了AI從業者、資料科學家、機器學習工程師。擴大新加坡此類從業者的範圍是一項有意義的工作,我們開始著手進行。
我們還注意到還有其他專業人士,各自領域的專家,他們有AI從業者沒有的東西。他們對他們在各自工作領域中面臨的所有問題都有深入的瞭解,但不太瞭解AI如何能幫助解決這些問題。
所以我們開發了AI雙語人才的概念——在各自領域的專家,他們掌握足夠的AI知識,使他們與資料科學家和機器學習工程師的互動變得更加有意義,也更有可能轉化為他們負責領域的真實好處。
我們討論的是流程工程師這樣的人,他們深刻了解生產線和生產流程。我們討論的是律師、會計師和人力資源專業人士,他們有一些東西要貢獻,他們可以幫助組織從AI採用中獲益更多。
這是包容性的一種型別:我們如何包括那些其組織和職業不太可能自行成為AI早期採用者的人。
但還有另一種非常重要的包容性。我知道你會很熟悉這一點:技術擴散,通常是處於前沿的公司,如IBM,以各種想象中的方式使用該技術來改進他們的運作方式。但也會有許多中小型企業缺乏知識和資源,甚至不知道從哪裡開始。如果我們真正具有包容性,我們也必須有接觸中小型企業(SMEs)的專案。
還有一種我們認為包容性也很重要的方式,那就是在國家層面。新加坡很幸運,因為我們承辦了像你們這樣的偉大技術公司(IBM),因此通過你們,我們接觸到了一些最先進的產品和服務。這在其他國家不一定如此,例如在我們的鄰國中可以看到。
因此,通過我們參與小國論壇(擁有108個成員)並擔任其召集人,我們制定了AI手冊。在東盟內部,我們分享我們的開源模型——東南亞語言統一網路(SEA-LION),大型語言模型。它不是很大。我認為只有170億個引數,與最大的模型相比很小。但它在我們的背景下有真正的用處,因為它捕捉了東南亞的語言和文化細微差別。
這些是我們希望能夠推廣包容性理念的不同方式。
主持人:我一直欣賞亞洲將所有人納入AI採用的方式,我認為這真的可以作為世界其他地區的藍圖。部長,你提到了SMEs,對吧?這不僅僅是一項將為大公司帶來好處的技術,這是一個非常難以平衡的問題:規模與增長。你如何確保這種規模的採用產生真實的影響,而不僅僅是打勾以確保你真的接觸到了所有部分?
部長:這真的很有趣,因為當我與一些小企業互動時,我對他們嘗試使用AI的創意程度印象深刻。
我去過一個小型食品和飲料店。當我與業主交談時,他們告訴我他們已經在使用AI,我很好奇他們是如何使用的。嗯,有兩個人,他們最初獲得AI技能的方式是去參加培訓。
我們有一個個人學習賬戶,稱為SkillsFuture。政府在其中投入信用。你可以使用信用去參加培訓,這兩位企業家正好這樣做了。他們去培訓提供商處學習如何提示。他們進行業務的平臺也建立了一個AI助手,他們學會了如何利用它來分析他們的銷售資料。
他們在這個平臺上的業務不是他們全部業務——它佔他們收入的約20%。但這對他們來說足以理解他們的銷售促進活動。因此,通過學習提示的技能,他們使用由平臺提供的這個AI助手來找出他們的哪些促銷活動正在產生更好的回報。他們還學會了使用AI工具來生成他們自己的營銷材料。
所以雖然可能存在資源或知識差距,但一旦你填補這個差距,採用可以很快。我們建立的計劃——國家AI影響專案——與已經為許多中小型企業提供軟體即服務(SaaS)產品和服務的合作伙伴合作,我認為向產品中新增AI工具的想法是一種真正合理的方式讓企業學習這項技術如何能為他們帶來好處。
我們也非常熱心於思考可能有更具定製需求的公司。換句話說,通過SaaS的標準產品可能不會滿足他們的需求,所以我們有一個平行的專案——我們稱之為企業計算倡議,通過與合作伙伴合作,我們提供計算資源,以嘗試緩解SMEs的支出需求。這特別適用於當他們需要開發更加定製化的東西,是他們無法通過中介獲得的東西時。
所以這些是我們試圖給予SMEs優勢的不同方式,並將AI是一種民主化技術的想法變為現實。
主持人:你們有一個很出色的專案叫「數字領袖加速訓練營」(Digital Leaders Acceleration Bootcamp)。能否為我們進一步介紹一下這個專案如何助力民主化戰略?
部長:好的,這源於我們與許多人就其組織內的經驗進行的交流。一些人告訴我們「我在學習AI技能,但我的老闆沒有」。還有許多其他人可能仍然略微落後。所以人們告訴我們需要幫助業務領導者理解這項技術的實用性,我們不能僅僅依靠理論。我們需要給他們實際操作的經驗,向他們介紹他們可以合作的潛在合作伙伴,以便在他們的組織中以可持續的方式實施AI。
畢竟,AI不是一種廉價技術。如果架構設計不當,你很容易就會用完代幣。這些因素總是會影響業務所有者的計算:需要多少成本?使用這個工具需要花我多少錢?
數字領袖加速訓練營(Digital Leaders Accelerator Bootcamp)就是為了這個目的而設計的。它旨在讓業務領導者,特別是中小企業業務領導者,對AI的各個方面有更全面、更深入的瞭解,包括風險而不僅僅是好處,以及他們如何建立正確的系統和流程以有效使用AI。
我們決定這不是政府應該單獨完成的事情。我們應該與合作伙伴合作,因為技術發展非常迅速,我們從他們在其他領域(可能在其他國家)的經驗中受益。我們已經有這樣一個專案,因為數字化之旅為我們推動更廣泛的AI採納提供了很好的基礎。因此,擴充套件這個專案,注入更多AI元素,是一個非常自然的進展。
主持人:非常好,我們為能加入這個專案而感到非常自豪。我認為我們是第三個這樣做的組織,我們採取的方式是整合我們在業務轉型諮詢方面的專業知識與我們的企業AI技術,幫助組織識別有意義的用例,快速構建最小可行產品(MVP),最重要的是,建立內部能力,以便在專案結束後很久繼續他們的AI之旅。因此,知識轉移,對於許多組織來說,挑戰不是AI雄心的缺乏。而是知道從哪裡開始以及如何負責任地擴充套件,這正是我們希望為專案做出貢獻的地方。
部長,我想稍微改變一下話題,因為我們剛才討論的關於抱負、包容性和規模的一切,只有在其下有信任的基礎時才能成立。信任、治理和代理AI。我在我的演講中強調的一點是,信任真的必須首先來,因為沒有它,AI採納根本無法擴充套件。當你從實驗階段轉向在真實運營中嵌入AI時,治理對於維持信任變得至關重要。你在世界經濟論壇達沃斯論壇上推出了世界上第一個代理AI框架,並且已經更新了它。當你將信任和治理的這些原則從框架轉化為真實世界的實踐時,你學到了什麼?
部長:好的,如果我們回顧一下,即使在我們推出第一個國家AI戰略之前,我們就已經制定了AI治理框架。所以,作為部長,我也對我的前任在我們推出一套戰略之前就已經考慮到治理感到相當驚訝。我們繼續強調創造一個受信任的AI實施環境。
事實上,AI創造的風險不同於我們習慣的風險。我們的風險管理框架,我們為各種系統安全、消防安全、飛行安全而設定的保障——所有這些都是為了應對人類在迴圈中時所建立的問題而設想和設計的。
但是,當你使用代理時,當代理被設計為代表人類做出決定時,產生的錯誤、風險和安全問題型別,老實說,還沒有被完全理解。在我們完全理解代理被釋放時可能產生的問題範圍之前,需要相當長的時間。
我們知道我們人類會建立的問題型別,我們已經設計來防止這些問題變成災難。我們不確切知道代理系統是否會產生相同範圍的錯誤。因此,我們必須退一步問自己:那麼我們需要做什麼才能促進代理的採納?
因此,對我們來說,理解我們為什麼設計代理工作流程是非常重要的,我們真的需要花時間思考約束條件、原則以及如何在問題出現時對其進行緩解。
所以還處於早期階段。我會說,在這方面,我們的意圖是與那些幫助他們的客戶和網路更有效地使用代理的合作伙伴合作。我認為通過從他們的實際經驗中學習,我們有更好的機會改進我們的方法並在這些系統完全投入生產之前設計測試。
主持人:部長,我們的對話即將結束。現在讓我們展望一下未來——讓我們談論量子。新加坡有自己的國家量子戰略。你認為該國在量子領域最大的機遇在哪裡,你今天是如何考慮為此做準備的,而不僅僅是五年後?
部長:事實上,大約20年前,我們就已經投資建立了量子技術中心,很長一段時間以來,我們有專家深入研究這個課題並將他們的能力提升到世界級水平。我真的很高興他們能夠做到這一點。如果你與國際科學界交流,他們會意識到新加坡內的能力。所以這是一個非常好的基礎。
當我們開始思考提升我們的量子能力併為量子時代做準備時,有幾個我們關注的領域。首先是,你是否有量子安全通訊的選項?因為有了強大的量子計算機,今天解密的任何東西可能不再受保護。除了建立量子安全通訊網路外,我們如何幫助人們遷移到量子安全密碼學?所以這些是一直吸引我們的活動。
最近還有兩個令人興奮的發展。一個是我認為我們處於量子計算發展的階段,對我們來說提出如何建立技能以開發量子演算法並能夠增長、構建將與我們的背景相關的應用以及什麼將與新加坡的背景相關的應用是合理的。
每年我們要處理數百萬個集裝箱的移動,如果你去過集裝箱堆場,你就會知道這些集裝箱現在堆積得幾乎十層高。所以,你從一艘船卸下的箱子是堆在第二層還是第八層是有區別的,因為當你需要將這個集裝箱重新裝到下一艘船上時,如果你把它堆在正確的位置,工作會少得多。
但這些是非常複雜的計算。古典計算機每次箱子無法裝載或在不同時間裝載時進行一次評估都需要花費數年。所以對我們來說有一個使用案例。當然,我們的金融部門也有量子計算的用途。我們認為對演算法和應用已經有了需求的基礎。這是我們正在努力的一個領域。
另一個領域同樣令人興奮。直到最近,我們不知道新加坡甚至可以有意義地參與某些型別的量子計算機元件的製造。事實證明,生產過程與我們的半導體制造能力有相關性,特別是在先進封裝方面。
不久前在達沃斯,我坐在諾貝爾物理學獎得主約翰·馬蒂尼斯旁邊,解釋新加坡對量子的興趣,突然他舉起手說「我要去新加坡!」。我很好奇,所以我問他「你去新加坡做什麼?」。他說「因為你們有先進封裝、半導體制造」。他的初創公司,一家名叫Qolab的公司,實際上正在與我們的聯合鑄造廠合作,設計和生產超導計算機的元件。所以這裡有非常令人興奮的發展。
主持人:太令人興奮了。最後,部長,你希望房間裡的人們從新加坡的未來方向中帶走什麼,這對我們所有人意味著什麼?
部長:好的,用簡單的一句話說,我們希望新加坡成為AI創新的家園,我們歡迎你成為我們充滿活力的AI中心的一部分。
主持人:我們接受邀請,部長。非常感謝你抽出時間,感謝你為這次對話帶來的願景的清晰性。能夠與新加坡和你合作是一個巨大的榮幸。
英文原文
MDDI 官網原始記錄 · 抓取日期: 2026-07-28
Moderator Ana Paula Assis, Senior Vice President and Chair for IBM Europe, Middle East, Africa and Asia Pacific: I often come back to the idea that “winning” the enterprise AI race looks different depending on where you sit. With Singapore’s updated National AI Strategy, which introduced the sectoral missions and the new AI Council, led by the Prime Minister, it is clear that you are stepping up the ambition for AI in Singapore. From your perspective, could you please define the version of success that you're aiming for, and what prompted the shift in approach here?
Minister Josephine Teo: I would characterise what we're doing in the updated National AI Strategy as a “double click” rather than a system reboot. When we put out National AI Strategy 2.0 in December 2023, we kind of already had a sense that the developments were going to happen at such a fast clip, that as soon as we put the document out, parts of it would already be outdated, and it would always need a refresh.
But what was really interesting is that, as we implemented the strategy, we realised something had inverted compared to previous technology cycles. With earlier technologies that were being introduced, our first contact as individuals was usually as members of the workforce. Our organisations adopted the technology, then conducted massive rounds of training. We learned how to use the technology at work before we realised that this technology could have personal applications and started using it at home.
The personal computer was like that. Our first encounter with the computer was in the office. For many people, the first interaction with email was in the office too. But AI is quite different. AI is truly democratising access to something that can have a profound impact on our lives. You and I use AI almost daily. I am pretty sure that on your smartphone and other devices, you are already using AI. Today, the converse is true: we might be using AI to a larger extent than our organisations are.
Many of you have probably tried vibe coding. You are building apps to keep track of your children's schedule. You are using it to scan the internet for interesting articles and to surface them to you. I have an agent that does that for me.
So here's where the gap is: individual productivity is improving is at a faster clip than enterprise productivity. Then you think about the bigger challenge. How does this technology impact industries? How does it impact the entire nation? That was what we were thinking about when we refreshed our National AI Strategy.
We said we have to put more emphasis on helping enterprises adopt this technology and integrate it into their existing processes. As is natural for all businesses to expect, there also has to be an ROI. At some point, this has to translate into commercial value, into dollars and cents producing a real, tangible benefit. So that was where we chose to place the emphasis.
Hence, the push to accelerate and boost efforts in helping businesses, especially at the leadership level, think about how they can make this technology come alive, not just for individual employees, but in the enterprise context.
For example, we have also a collaboration with IBM targeting leaders who hold responsibility for digitalisation in their organisations. We want them to think strategically about how AI can be used in their operations and how they might rethink their business models.
We have a National AI Impact Programme that hopes to do this on a wider scale. This programme complements what we are also hoping to do through the National AI Missions, which are more about the end-to-end transformation of sectors. They are advanced manufacturing, healthcare, finance, as well as connectivity, which together contribute 40% to our GDP. We are hoping to push these, so that the benefits don't stay at the individual level, but expand to enterprise, industry, sectoral, and national levels.
Moderator: On to the next question. One point of yours that really resonates with me is this commitment to ensuring AI drives inclusive growth, not just productivity for the few. And again, we're thinking deeply about how AI can augment people and enhance their capabilities, not simply replacing tasks. How is Singapore approaching this opportunity, and what early progress and insights are you seeing so far?
Minister: When we think of inclusivity, it can also cover several dimensions.
There is inclusivity at the individual level. We're concerned about pockets of our workforce that may not have adequate exposure to how AI can transform their domains. If you work in a technology-infused environment, you are very likely to be exposed to AI tools. But in some professions, in some areas, adoption may lag, and it may take some time.
So, when we were implementing our workforce capability development programmes, one area deserved greater attention. We were thinking of AI practitioners, data scientists, machine learning engineers. Expanding the pool of such practitioners in Singapore was a meaningful exercise, and we set about doing it.
We also noticed there are other professionals, experts in their own domains, who had something the AI practitioners did not. They have intimate knowledge of all the problems that they faced in their respective areas of work, but not quite how AI could help solve them.
So we developed this idea of AI bilinguals – experts in their own field who pick up enough AI knowledge that their interactions with the data scientists and machine learning engineers become far more meaningful, and far more likely to translate into and real benefits in their areas of responsibility.
We are talking about people like process engineers, who know the manufacturing line and the production processes deeply. We are talking about lawyers, accountants and HR professionals, who have something to bring to the table, who can help organisations benefit more from AI adoption.
That was one type of inclusivity: how we include people whose organisations and professions were unlikely, on their own, to become early adopters of AI.
But there is also another very important type of inclusivity. I know you would be very familiar with this: technology diffusion, it is very often the companies at the frontier, like IBM, that use the technology in every way imaginable to improve how they function. But there will be many small and medium enterprises who lack the knowledge and resources, and who don't even know where to begin. If we are truly inclusive, we must also have programmes that reach the small and medium enterprises (SMEs).
There is one other way which we think inclusivity also matters, and that's at the country level. Singapore is very fortunate in the sense that we host great technology companies like yourselves (IBM), and so through you, we have exposure to some of the most advanced products and services available. This is not necessarily the case in other countries, as can be seen among our neighbours, for example.
So through our participation in, and as convener of the Forum of Small States, which has 108 members, we developed an AI playbook. Within ASEAN, we share our open-source model – the Southeast Asian Languages in One Network (SEA-LION), large language model. It is not very large. I think only 17 billion parameters, which is small compared to the biggest models. But it has real usefulness in our context because it captures the languages and the cultural nuances of Southeast Asia.
These are the different ways in which we hope to be able to promote the idea of inclusivity.
Moderator: I always admire the way that Asia is bringing all the people along in the adoption of AI, and I think that this could really serve as a blueprint for the rest of the world. Minister, you talked about SMEs, right? It is not just a technology that is going to drive benefits to the large corporations, and this is a very tough balance to strike: scale versus growth. How do you make sure adoption at that scale creates real impact, not just ticking the boxes to make sure that you really reached all the segments?
Minister: It is really quite interesting because when I interacted with some small businesses, I was quite struck by how creative they were in trying to use AI.
I've been to a small F&B outlet. When I was talking to the business owners, they told me that they were already using AI, and I was very curious how. Well, there are two people, and the way in which they first picked up AI skills was to go for training.
We have an individual learning account, called SkillsFuture. The Government puts credits in it. You can use the credits to go for training, and these two entrepreneurs did exactly that. They went to a training provider and learnt how to prompt. The platform they were doing business on had also created an AI assistant, which they learnt to tap to analyse their sales data.
Their business on this platform was not all of their business - it made up about 20% of their revenues. But that was enough data for them to make sense of their sales promotions. So, through learning the skill of prompting, they used this AI assistant that was provided by the platform to figure out which of their promotions were generating better returns. They also learned to use AI tools to generate their own marketing materials.
So while there may be a resource or knowledge gap, the adoption can be quick once you plug this gap. The programme that we put in place, the National AI Impact Programme, works with partners who perhaps already offer Software as a Service (SaaS) products and services to many small and medium enterprises, and the idea that you can add an AI tool to the offerings is, I think, a really reasonable way for the enterprises, to get to learn how this technology can benefit them.
We are also very keen to think about companies that may have more bespoke needs. In other words, a standard offering, through SaaS may not satisfy their needs, so we have a parallel programme – we call it the Enterprise Compute Initiative, where by working with partners, we make compute available, to try and moderate the expense requirement for SMEs. This is especially when they need to develop something that is more bespoke, something that they can't quite get through an intermediary.
So these are the different ways in which we are trying to give our SMEs a leg up, and bring to life the idea that AI is a democratising technology.
Moderator: You have this great initiative called the Digital Leaders Acceleration Bootcamp. Can you tell us a little bit more about how that helps in that democratisation strategy?
Minister: Well, it comes from talking to many individuals about their experiences in their organisations. Individuals were telling us that “I'm learning AI skills but my bosses aren't”. There are many others who are, perhaps, still slightly behind the curve. So people were telling us that we need to help business leaders understand the usefulness of this technology, and we cannot just rely on theories. We need to give them hands-on experience, introduce them to prospective partners that they can also work with, so as to implement AI in a sustainable way in their organisations.
After all, AI is not a cheap technology. You can easily use up tokens if you did not architect it right. These things will always feed into a business owner's calculations: How much does it take? How much does it cost me to use this tool?
The Digital Leaders Accelerator Bootcamp was designed with this purpose in mind. It was designed to give business leaders, particularly SME business leaders, a fuller and deeper understanding of all that comes with AI, including the risks, not just the benefits, and how they can put in place the right systems and processes in order to use AI effectively.
We decided that this was not something the Government should do on its own. We should work with partners because the technology moves very fast, and we benefit from their experiences in other domains, perhaps in other countries as well. We already have such a programme because the digitalisation journey serves as a very useful foundation for us to promote wider AI adoption. So expanding this programme, infusing more AI elements in it, is a very natural progression.
Moderator: That's very good, and we are very proud to join the programme. I think we're the third organisation to do that, and we are doing that as one idea – bringing together our consulting expertise in business transformation with our enterprise AI technology, to help organisations identify meaningful use cases, build Minimum Viable Products (MVPs) quickly, and most importantly, develop the internal capability to continue their AI journey long after the programme ends. So, transferring the knowledge, and for many organisations, the challenge isn't a lack of AI ambition. It's knowing where to start and how to scale responsibly, and that's exactly what we hope to contribute to the programme.
Minister, I want to shift gears slightly because everything we've just discussed in terms of ambition, inclusion, scale only holds up if there's trust underneath it. Trust, governance, and agentic AI. One thing that I emphasize in my talk is that trust really comes first, because without it, AI adoption simply doesn't scale. As you move from experimentation to embedding AI in real operations, governance becomes critical to sustain the trust. You launched the world's first framework for agentic AI at WEF Davos and you have already updated it. What are you learning as you translate these principles of trust and governance from framework to real world practice?
Minister: Well, if we take a step back, even before we put out the first National AI Strategy, we had articulated an AI governance framework. So, for me as a minister, I was also quite struck that my predecessors had already thought about governance even before we put out a set of strategies. We have continued this emphasis on creating a trusted environment for AI implementation.
The truth of it is that AI creates risks that are different than the risks we are used to. Our risk management frameworks, safeguards we put in place to all kinds of systems-building safety, fire safety, aircraft safety – all of these were conceived of and designed to tackle the kind of issues that humans create, when humans are in the loop.
But when you use agents, when agents are designed to make decisions on behalf of humans, the kinds of errors, risks, and safety issues that arise, are honestly not completely well understood. It will be quite a long time before we fully appreciate the range of problems that could be created when agents are unleashed.
We know the kinds of problems that we humans create, and we have designed to prevent those problems from becoming disasters. We don't exactly know whether agent systems will produce the same range of errors. Therefore, we have to take a step back and ask ourselves: What then do we do in order to be able to promote agent adoption?
So, it is very important for us to understand what we are designing the agent workflow for, and we really have to spend time thinking about the harnesses, the principles, and how to mitigate problems as they arise.
So it is still early days. I would say that in this regard, it is our intention to work with partners who are in the business of helping their clients and networks use agents in a more effective way. I think through learning from their actual experience, we have a much better chance of improving our methods and designing tests before these systems are fully put into production.
Moderator: Minister, we are starting to come to a close in our conversation. Let's now take a peek into the future – let's talk about quantum. Singapore has its own national quantum strategy. Where do you see the biggest opportunity for the country in quantum, and how are you thinking about preparing for it today, not just five years down the road?
Minister: As it turns out, from about 20 years ago, we already invested in starting up a centre for quantum technologies, and for the longest time, we had experts who were working to deeply research the topic and bring their capabilities up to world-class levels. I'm really glad that they've been able to do so. If you talk to the international scientific community, they are aware of the capabilities within Singapore. So that's a really good foundation.
When we started thinking about levelling up our quantum capabilities and preparing for the quantum age, there were a few areas that we were concerned about. The first was, do you have the option of quantum safe communications? Because with powerful quantum computers, whatever is decrypted today may no longer be protected. How do we also, apart from building up quantum-safe communications network, help people to migrate to quantum-safe cryptography? So those were the activities that have been engaging us.
Two more recent developments bring a lot of excitement. One is that I think we are at the stage of development in quantum computing that it is reasonable for us to ask how do we build up the skills in order to develop quantum algorithms and to be able to grow, build the applications that will be relevant in our context, and what would be relevant in Singapore's context.
Every year we are dealing with millions of container movements, and if you have been to a container yard, you will know that these containers are stacked by now almost ten levels high. So, it makes a difference whether the box that you are unloading from one vessel is stacked at level two or stacked at level eight, because when you need to reload this container to the next vessel, if you stacked it at the correct place, there's a lot less work.
But these are very complex computations. It would take a classical computer years to make one assessment each time the box could not be loaded or was loaded at a different time. So there is a use case for us. Certainly, our financial sector also has uses for quantum computing. We think that there is already a basis for demand for algorithms and applications. That's one area that we're putting effort into.
The other area is equally exciting. Until recently, we did not know that Singapore could participate meaningfully even in the manufacturing of components for certain types of quantum computers. It turns out the production process has adjacencies with our semiconductor manufacturing capability, particularly in advanced packaging.
Not long ago at Davos, I was sitting next to Nobel Physics Prize winner, John Martinis, explaining Singapore's interest in quantum, when he shot his hand up and said, "I'm going to Singapore!” I was very curious, so I asked him, "What are you going to Singapore for?” He said, "Because you have advanced packaging, semiconductor manufacturing”. His startup, a company by the name of Qolab, is in fact working with our federated foundry to design and produce components for superconducting computers. So there are very exciting developments here.
Moderator: Super exciting. To conclude, Minister, what is the one thing that you hope people in this room take away about Singapore's future direction and what could it mean for all of us?
Minister: Well, in a simple sentence, we would like Singapore to be the home of AI innovation, and we welcome you to be part of our vibrant AI hub.
Moderator: We accept the invitation, Minister. Thank you so much for your time, the clarity of the vision that you brought to this conversation, it's a big privilege to partner with Singapore and with you.