The Power of Asking, Not Telling (1)

NUCB Associate Dean Dr. Wong sits down with fellow NUCB professor Dr. Lim to discuss how AI is transforming educators’ roles. As AI handles knowledge-based tasks, educators are shifting from delivering information to fostering judgment, critical thinking, and human-centered managerial wisdom.

Reimagining the Educator’s Role in the AI Era

Dr. Wong:​  Our opening topic is how faculty roles are changing. As AI advances rapidly, already surpassing human performance on many tests, faculty are shifting from knowledge transmitters to facilitators. What high-value interventions must educators provide in this new era?

Dr. Lim:  Learning has three parts: knowledge, skills, and wisdom —knowing ‘what,’ ‘how,’ and ‘why.’ AI handles the “what” well. We should focus on the “why,” where human judgement remains essential.

Dr. Wong:​  Exactly. We are no longer information brokers delivering facts. Our role is helping students move beyond generating information to synthesizing it and constructing meaning.

Dr. Lim:  Bob Bruner, once a young casewriter for HBS professor Roland Christensen and later Dean of the Darden Business School, summarized his teaching philosophy as “Ask often, tell seldom.” MIT professor Ed Schein calls this “humble inquiry.”

Dr. Wong:​  Our value lies not in linear knowledge transfer but in constructive disruption. By sparking discussion, challenging assumptions, and sharpening thinking, we guide students in uncovering the deeper “why.”

Dr. Lim:  Yes, we move from “sages on the stage” to “guides on the side.” Like Socrates, we ask seemingly naive questions to stimulate critical thought.

Dr. Wong:​  You previously delivered a lecture on how the case method grew from the Socratic method. In a world where students can get instant answers from AI, how does questioning hold up?

Dr. Lim:  AI’s convenience in giving answers, “telling,” risks intellectual inertia; real learning starts with questions that disrupt and being willing to say, “I don’t know.”

Dr. Wong:​  So we shift from answering to questioning, emphasizing the process rather than the solutions.

Dr. Lim:  Exactly. In a case classroom, ideas may take unexpected paths. Our craft lies in knowing when to guide and when to let students explore.

Dr. Wong:​  That is why we continually refine our craft and host events where faculty share teaching practices with partners across Asia and beyond.

Dr. Lim:  Both young and veteran faculty must keep sharpening. Christensen once described a colleague who lost the spark in his classroom. Believing he was asking questions, the teacher had subtly shifted from “What do you think?” to “Don’t you think?”: he was no longer “asking” to invite thought, but rather “telling.” It’s a reminder that by gaining control, we drain the students’ energy.

Dr. Wong:​  Humility and renewal are essential.

Dr. Lim:  More than ever.

Dr. Wong:​  Some professors respond to AI by banning it, while others worry it erodes critical thinking skills. How should we guide students?

Dr. Lim:  Over‑reliance leads to atrophy, but a total ban on AI is disabling. Like spreadsheets or PowerPoint in earlier decades, AI is a tool—a research assistant, brainstormer, and organizer. Students should learn to use many tools wisely, not depend on just one.

Dr. Wong:​  AI itself must also be studied. Students need to understand both its strengths and limitations. It can act as a coach by asking questions, but it may be overly agreeable or inaccurate, so outputs require careful verification. If treated merely as a shortcut, we miss its real value.

Dr. Lim:  Students should practice using AI before entering the workplace. We can even prompt AI to question us—“Ask often, tell seldom.”

Dr. Wong:​  Faculty can often feel overwhelmed by the pace of change. How can they keep up without adding an unsustainable workload?

Dr. Lim:  By embracing humility. Accept that students may know more. Say, “I don’t know. Can you show us?” In doing so, we become co-learners.

Dr. Wong:​  Which brings us back to the central question: in an AI era, what is the value of the educator?

Developing Human-Centered Managerial Competence

Dr. Lim:  If AI is strong in knowledge, educators should focus on wisdom.
Wisdom—or its subset, judgment —is recognizing that truth often resides in the middle. At times we must be bold; at others, cautious. Knowing that a tomato is a fruit is knowledge; knowing not to put it in a fruit salad is wisdom. AI may one day grasp this sense of “the middle,” but it does not yet.
Learning involves more than skills such as calculating IRR or preparing budgets; it also requires emotional and social judgment. How do you work with difficult people? How do you correct without offending? The diversity of the NUCB case classroom provides a powerful setting to practice these skills. How do you draw insights from more reserved students while channeling the energy of more assertive ones in a multicultural classroom? These experiences translate directly into more effective engagement with diverse colleagues in the workplace.
Another essential managerial skill is helping others become teachers themselves. Managers routinely “teach” their teams. As Professor Bruner suggests, rather than tell people what to do, good managers ask questions that help others discover on their own. When done constructively, this approach builds ownership and responsibility instead of resentment.

Dr. Wong:  This aligns with research on AI. As data-intensive tasks are increasingly delegated to AI, human strengths such as communication, empathy and emotional skills become even more important. As educators, we need to recognize that soft skills are becoming more important than purely technical ones.

Dr. Lim:  Managers must shift among multiple roles. As Henry Mintzberg described, management requires wearing at least ten different hats —leader, liaison, negotiator, and more —at the right time. AI may not yet know when to wear such hats.

Dr. Wong:  That raises the ethical dimension. I'm not convinced AI can guide students in ethical judgement. Even in major technology companies, humans remain responsible for managing AI’s ethical use.

Dr. Lim:  Exactly. Aristotle urged his students to seek the virtuous mean—the balance between deficiency and excess. Ethical dilemmas arise precisely when no option is purely right or wrong, when every choice benefits some stakeholders and harms others. Humans navigate such dilemmas through iterative systems thinking: considering how one action affects one group, how that effect ripples to others, and adjusting accordingly.

Dr. Wong:  These ideas connect with research on tacit knowledge — knowledge that cannot easily be documented or stored. AI models learned mainly from recorded data, but tacit knowledge often resides only in experienced leaders and practitioners. That is why educators remain essential in facilitating learning.

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