[INTERVIEW] Singapore Management University president highlights growing role of social sciences in AI era

Singapore Management University President Lily Kong said social sciences and management will matter more as AI reshapes work, business and public policy in Singapore. She said universities must teach students to question AI output, judge its consequences and use it responsibly. SMU has introduced an AI education strategy that moves students from basic use to critical evaluation and real-world application.

Kong said the more capable AI becomes, the more valuable human judgment becomes.

SMU has launched an AI education strategy that teaches students to use AI, learn with it and critically evaluate its output across all four undergraduate years.

In capstone projects, students may use AI but must show their own contribution and critically interrogate AI answers.

Kong said autonomous vehicles show that technology also depends on governance, trust, psychology and law before it can be widely adopted.

Published Sep 17, 2026 7:00 am KST

Lily Kong stresses critical thinking, ethical reasoning and human judgment

Singapore Management University President Lily Kong / Courtesy of Singapore Management University

This is the fourth in a series of interviews as The Korea Times speaks with leading university presidents across the globe to examine how institutions are redefining education, research and international collaboration in an era shaped by artificial intelligence, demographic shifts and geopolitical uncertainty. The series is supported by the Korea Press Foundation's Press Promotion Fund.

SINGAPORE — As artificial intelligence (AI) reshapes how businesses operate, governments make policy and people work, the skills needed to navigate its impact are extending far beyond technology — putting greater emphasis on human judgment, critical thinking and an understanding of society.

Singapore Management University (SMU) President Lily Kong believes that shift will make the social sciences and management increasingly important in the AI era, as universities are tasked not only with teaching students how to use the technology, but also to question its output, understand its consequences and apply it responsibly.

“I think that the more capable that AI becomes, the more valuable human judgment becomes,” Kong said in a recent interview with The Korea Times.

For Kong, AI is not just a technological shift. As it reshapes workplaces, business decisions and public policy, universities must equip students to understand and manage its broader impact on society.

She said SMU’s focus on management, social sciences and technology puts it in a strong position to prepare students for that challenge.

“How do we manage AI? How do we think about the consequences of AI on society?” Kong said. “This nexus of management, social sciences and technology is going to be increasingly important for all universities.”

Students need to know how to use AI, Kong said, but technical skills alone are not enough. As AI makes answers increasingly accessible, the greater challenge is knowing what to ask and how to judge the results.

“It’s not so much finding the right answers, because AI can find you many answers at your fingertips, but it’s being able to ask the right question,” she said.

Students must also be able to judge whether AI-generated answers are accurate and appropriate to the context, she said — a task that requires critical thinking, ethical reasoning and empathy, skills rooted in management and the social sciences.

The Singapore Management University campus / Courtesy of Singapore Management University

Teaching students to work with AI

The university has embraced AI as part of learning rather than trying to keep it out of the classroom.

Kong said the university initially shared concerns that generative AI could be used for cheating when tools such as ChatGPT emerged in late 2022, but soon concluded that banning them was not the answer.

“AI is here to stay,” she said. “In working life, people will use it. So our role must be to help students learn how to use it ethically, responsibly, applying human judgment.”

SMU has since introduced an AI education strategy that progressively teaches students how to use AI, learn with it and critically evaluate its output.

Programs span all four undergraduate years, with students moving from basic AI use to critical evaluation and eventually applying the technology to real-world problems.

In capstone projects, for example, students work with industry partners or government agencies to tackle actual problems. They are allowed to use AI, but must demonstrate their own contribution rather than simply presenting AI-generated solutions.

“They have their value add. They have critically interrogated the AI answers,” Kong said.

Students pose in front of Singapore Management University’s School of Law during the university’s commencement ceremony, July 28. Courtesy of Singapore Management University

Making technology work for society

Kong believes the same changes that are driving universities toward STEM fields could ultimately make non-STEM disciplines even more important.

A technology can function perfectly from an engineering perspective and still fail in society, she said. People may not trust it, businesses may struggle to afford or implement it, or governments may lack rules governing its use.

Those are questions of psychology, economics, management, law and governance.

Kong pointed to autonomous vehicles as an example. Even if the technology works, widespread adoption will depend on governance issues such as who is liable in an accident — the passenger, manufacturer or algorithm developer.

“Technology has many possibilities, but we need the social science, the governance, the management before we can really leverage the technology,” she said.

That approach is also shaping SMU’s research agenda. Its Resilient Workforces Institute studies how workers, organizations and governments can adapt as AI transforms jobs, from redesigning work around human-AI collaboration to developing training and funding policies.

Kong said universities have a dual role: rethinking how they educate students while producing research that helps businesses and governments navigate the transition.

A graduate poses during Singapore Management University’s commencement ceremony, July 28. Courtesy of Singapore Management University

Turning research into real-world impact

Beyond AI, SMU is focusing its interdisciplinary research on three major challenges: aging populations, changing workforces and urban transformation.

Kong said academic rigor and publications remain essential, but research should ultimately translate into real-world impact by informing government policy and business practices.

“How do we work with policymakers? How do we work with businesses? How do we work with government departments to turn some of this knowledge that is created into economic impact or impact on social and cultural life?” she said.

SMU’s university-level research institutes reflect that approach, bringing together researchers across disciplines to tackle complex challenges and connect their findings with policymakers, businesses and other outside partners.

Autonomous vehicles, for example, involve more than technology, Kong said.

“It’s not just a technology question. It’s a governance question. It’s a psychological question. It’s a trust question,” she said.

Kong said such interdisciplinary research is increasingly important in the AI era, when technological advances are closely intertwined with broader social, economic and governance challenges.

As AI becomes better at generating information and answers, Kong said universities should focus on developing the human skills needed to assess them, understand their implications and make sound decisions.

“The individuals who will do well,” she said, will be those with “the flexibility to pivot, the resilience to face difficult circumstances, the empathy to work with different cultures and different people.”

新加坡管理大学校长孔莉莉表示，随着人工智能重塑新加坡的工作、商业和公共政策，社会科学和管理学的重要性将日益凸显。她指出，大学必须教会学生质疑人工智能的输出结果，评估其后果，并负责任地使用人工智能。新加坡管理大学已推出一项人工智能教育战略，旨在引导学生从基础应用逐步过渡到批判性评估和实际应用。

孔先生表示，人工智能能力越强，人类的判断就越有价值。

新加坡管理大学 (SMU) 推出了一项人工智能教育战略，旨在教会学生在本科四年期间使用人工智能、通过人工智能进行学习并批判性地评估其输出结果。

在毕业设计项目中，学生可以使用人工智能，但必须展示自己的贡献，并对人工智能的答案进行批判性审视。

孔先生表示，自动驾驶汽车表明，一项技术在被广泛采用之前，还取决于治理、信任、心理和法律。

发布于2026年9月17日 上午7:00（韩国标准时间）

莉莉·孔强调批判性思维、伦理推理和人类判断。

新加坡管理大学校长孔莉莉 / 图片由新加坡管理大学提供

这是《韩国时报》系列访谈的第四篇。该系列访谈旨在采访全球顶尖大学校长，探讨在人工智能、人口结构变化和地缘政治不确定性等因素影响下，各高校如何重新定义教育、科研和国际合作。本系列访谈由韩国新闻基金会新闻推广基金资助。

新加坡——随着人工智能 (AI) 重塑企业运营方式、政府制定政策方式和人们工作方式，应对其影响所需的技能远远超出了技术范畴——更加强调人类的判断力、批判性思维和社会理解。

新加坡管理大学 (SMU) 校长 Lily Kong 认为，这种转变将使社会科学和管理学在人工智能时代变得越来越重要，因为大学不仅要教学生如何使用这项技术，还要质疑其输出，了解其后果并负责任地应用它。

“我认为人工智能的能力越强，人类的判断就越有价值，”孔在最近接受《韩国时报》采访时表示。

在孔看来，人工智能不仅仅是一项技术变革。随着它重塑工作场所、商业决策和公共政策，大学必须让学生了解并应对其对社会的更广泛影响。

她表示，SMU 注重管理、社会科学和技术，这使其在帮助学生应对这一挑战方面处于有利地位。

孔教授说：“我们该如何管理人工智能？我们该如何思考人工智能对社会的影响？管理学、社会科学和技术的融合对所有大学来说都将变得越来越重要。”

孔教授表示，学生需要了解如何使用人工智能，但仅仅掌握技术技能是不够的。随着人工智能让答案越来越容易获得，更大的挑战在于知道该问什么问题以及如何判断结果。

“关键不在于找到正确的答案，因为人工智能可以让你轻松找到很多答案，而在于能够提出正确的问题，”她说。

她还表示，学生必须能够判断人工智能生成的答案是否准确且符合语境——这项任务需要批判性思维、道德推理和同理心，这些技能都根植于管理学和社会科学。

新加坡管理大学校园 / 图片由新加坡管理大学提供

教学生如何与人工智能合作

该大学已将人工智能纳入教学之中，而不是试图将其排除在课堂之外。

孔教授表示，该大学最初也曾担心生成式人工智能可能会被用于作弊，例如在 2022 年底 ChatGPT 等工具出现时，但很快就得出结论，禁止这些工具并不是解决办法。

“人工智能已成为我们生活的一部分，”她说。“在工作中，人们会用到它。因此，我们的职责是帮助学生学习如何以合乎道德、负责任的方式运用人工智能，并运用人类的判断力。”

此后，新加坡管理大学推出了一项人工智能教育战略，逐步教学生如何使用人工智能、如何利用人工智能进行学习以及如何批判性地评估人工智能的输出结果。

课程涵盖本科四年，学生从人工智能的基本使用逐步过渡到批判性评估，最终将该技术应用于现实世界的问题。

例如，在毕业设计项目中，学生会与行业伙伴或政府机构合作解决实际问题。他们可以使用人工智能，但必须展示自己的贡献，而不仅仅是呈现人工智能生成的解决方案。

“他们有自己的价值所在。他们对人工智能的答案进行了批判性的审视，”孔说道。

7月28日，新加坡管理大学法学院学生在大学毕业典礼上于法学院大楼前合影。图片由新加坡管理大学提供。

让技术服务于社会

Kong认为，推动大学向STEM领域发展的相同变革，最终可能会使非STEM学科变得更加重要。

她表示，一项技术从工程角度来看可能完美无缺，但在社会上仍然可能失败。人们可能不信任它，企业可能难以负担或实施这项技术，或者政府可能缺乏规范其使用的规则。

这些涉及心理学、经济学、管理学、法律和治理等问题。

孔以自动驾驶汽车为例。即便这项技术可行，其广泛应用仍取决于监管问题，例如事故责任的归属——乘客、制造商还是算法开发商。

“科技有很多可能性，但在真正利用科技之前，我们需要社会科学、治理和管理，”她说。

这种方法也影响着新加坡管理大学（SMU）的研究方向。其韧性劳动力研究所研究随着人工智能改变工作岗位，劳动者、组织和政府如何适应，研究内容包括围绕人机协作重新设计工作，以及制定培训和资助政策。

孔教授表示，大学扮演着双重角色：一方面要重新思考如何教育学生，另一方面要开展研究，帮助企业和政府应对转型。

7月28日，新加坡管理大学毕业典礼上，一位毕业生留影。图片由新加坡管理大学提供。

将研究成果转化为实际影响

除了人工智能之外，新加坡管理大学还将其跨学科研究重点放在三大挑战上：人口老龄化、劳动力变化和城市转型。

孔表示，学术严谨性和发表论文仍然至关重要，但研究最终应该通过为政府政策和商业实践提供信息而转化为现实世界的影响。

她说道：“我们如何与政策制定者合作？我们如何与企业合作？我们如何与政府部门合作，才能将这些产生的知识转化为经济影响或对社会文化生活的影响？”

新加坡管理大学 (SMU) 的大学级研究机构体现了这种理念，将不同学科的研究人员聚集在一起，共同应对复杂的挑战，并将他们的研究成果与政策制定者、企业和其他外部合作伙伴联系起来。

孔先生表示，例如，自动驾驶汽车涉及的不仅仅是技术。

“这不仅仅是一个技术问题，而是一个治理问题，一个心理问题，一个信任问题，”她说。

孔教授表示，在人工智能时代，这种跨学科研究变得越来越重要，因为技术进步与更广泛的社会、经济和治理挑战紧密相连。

孔表示，随着人工智能在生成信息和答案方面变得越来越好，大学应该专注于培养评估人工智能、理解其影响并做出合理决策所需的人类技能。

她表示，“那些能够灵活调整、有韧性面对困难环境、有同理心与不同文化和不同人群合作的人，将会取得成功。”