NUS Festival: As AI Advances, Learning to Learn Becomes the Human Edge
As AI grows more capable, knowing how to use it will not be enough, according to speakers at the third NUS Lifelong Learning Festival. NUS President Professor Tan Eng Chye said the paradox of the age of AI is that the smarter machines get, the more distinctively human skills matter.
- NUS President Tan Eng Chye said "learning to learn" matters more as AI gets smarter, speaking at the third NUS Lifelong Learning Festival on 28 September 2026.
- Prof Tulika Mitra said AI has raised the floor of what people can do, and people should raise the ceiling by redesigning workflows rather than just speeding up old tasks.
- Speakers said accountability for AI output and agent actions must stay with people.
- Prof Simon Chesterman said credentials and grades alone may become less effective differentiators, with soft skills gaining weight.
- Singtel's Aileen Tan advised workers to build "career optionality" as careers become less linear.
Learning is more than getting answers
Speaking at the festival on 28 September 2026, Professor Tan Eng Chye argued that lifelong learning is becoming more important because of AI, not less. "AI can give us answers, but learning is actually more than just providing solutions," he said, according to NUS News. In his words, learning is about "learning to learn", including the struggle of asking questions, making detours, failing and trying again.
The festival was themed "Human in the Age of AI" and brought together educators and industry leaders to discuss how AI is reshaping work and learning. It also marked the 10th anniversary of the NUS School of Continuing and Lifelong Education (SCALE). NUS said a broader shift emerged across the discussions: as AI makes knowledge and some capabilities more widely accessible, the advantage will increasingly lie not simply in what people know, but in how they think.
Raising the ceiling as AI raises the floor
Professor Tulika Mitra, NUS Vice Provost (Special Projects) and Dean of the School of Computing, said AI has already raised the "floor" of what people can accomplish. Knowledge, analysis, coding and content creation are now far more accessible, even to novices. She said this should prompt people to raise the ceiling rather than lower their expectations. "When AI can answer questions, who asks the right question? Who frames the right question?" she asked.
Prof Mitra cautioned against using AI only to do existing tasks faster, which she described as accelerating "yesterday's work". That can help productivity but is not necessarily transformational. The larger opportunity, she said, is to redesign workflows and ask what can now be achieved that was previously impractical or impossible.
Panellists from Singtel, Raffles Medical Group, ST Engineering and NUS-ISS described approaches ranging from workforce-wide AI training and experimentation to deploying AI agents and developing specialist capabilities. Mr Victor Chua of NUS-ISS called AI a "force multiplier", a co-partner or co-pilot rather than an autopilot.
Professor Jochen Wirtz of NUS Business School looked at what comes next: the convergence of large language models, large behavioural models and agentic AI could let service robots converse more naturally, remember previous interactions, reason and plan, and autonomously execute service transactions. He said this could help alleviate labour shortages while freeing employees for higher-value human interactions.
Accountability stays with people
Speakers stressed that greater AI capability does not shift responsibility away from humans. Professor Simon Chesterman, NUS Vice Provost (Educational Innovation), described generative AI as a "very smart intern with a drinking problem": capable of impressive work, but prone to hallucinations and in need of supervision. Humans remain responsible for deciding what to delegate, scrutinising results and intervening when necessary.
Prof Mitra made the same point about AI agents: "We can delegate the actions to AI agents, but accountability needs to really stay with the people." Prof Wirtz listed risks involving ethics, fairness, privacy, agency, and health and safety as AI moves into physical settings, and said autonomous systems would still need human oversight for exceptions, auditing, errors and escalations.
Prof Chesterman observed that while degrees remain important, credentials and grades alone may become less effective differentiators as AI lifts how well people perform some cognitive tasks. The "human edge" will increasingly include soft skills such as creativity, empathy, teamwork and leadership. Disciplinary expertise still matters, Prof Mitra said: "If you have zero foundation, you multiply it by AI, you still end up with zero foundation." Prof Chesterman described the NUS approach as "X plus AI" rather than "AI plus X", starting with a person's expertise and asking how AI can enhance it.
Careers that are less linear
Ms Aileen Tan, Group Chief People and Sustainability Officer at Singtel, suggested that workers with longer careers may need to pivot into different areas several times rather than expect to climb a single ladder. She encouraged employees to think about "career optionality", building skills that allow movement between roles and domains. Curiosity, a growth mindset and the ability to keep learning will be crucial to those transitions.
Prof Mitra said lifelong learning in the AI era should not be seen simply as reskilling or upskilling to catch up with technology, but as continually "discovering new possibilities" as AI opens up new ways of working.
