Kia in the Classroom: The Economics of Boldness in Teaching with AI

 By Richard Sebaggala

On September 3, 2025, a lecture hall at Simon Fraser University will host a moment that feels closer to science fiction than to the routines of academic life. Students will gather expecting a professor at the podium, but instead will find two figures waiting. One is Steve DiPaola, a familiar human presence, and beside him is Kia, a three-dimensional artificial intelligence rendered with startling realism.

The digital figure meets the audience with a direct gaze, smiles at the right moment, and speaks in measured tones that carry the authority of an academic voice. The class is no longer a monologue delivered by a single lecturer but a dialogue between flesh and code, a human mind and its synthetic counterpart. For students who grew up with animated avatars and digital companions, Kia may not appear entirely alien. What makes the moment extraordinary is that it unfolds within a university classroom, one of the last places where knowledge has been carefully guarded by human authority.

The arrival of Kia is not a cautious step in educational technology but an unmistakable act of boldness. Around the world, universities hesitate to integrate AI openly, unsettled by fears of plagiarism, shallow assignments, or the erosion of genuine intellectual effort. DiPaola has chosen a different path. Rather than shielding his students from the technology, he has brought it into the centre of the classroom as a living demonstration. The decision transforms the lecture hall into a theatre of inquiry, where the question is not whether AI exists but whether it can belong at the core of teaching. Economists would call this innovation under criticism, a dynamic that has accompanied every major technological shift since the age of mechanization.

History shows that new tools are rarely welcomed without resistance. The typewriter was once distrusted, the calculator dismissed as the death of numeracy, and the personal computer regarded as a passing fad. Those who pressed forward despite the doubts gained more than a reputation for daring. They accumulated knowledge that others lacked, learning where the tools succeeded and where they fell short. Uncertainty became capital. DiPaola’s decision to place Kia in the classroom follows this tradition. This idea is far from new; economists have long studied the strategic role of bold moves. The concept of first‑mover advantage, for instance, frames how being first in a market can confer durable benefits such as reputational surplus, learning gains, and control over resourcesBy facing skepticism now, he accepts reputational risk in exchange for insight. That willingness to trade risk for knowledge is what allows innovation to move.

What makes Kia disquieting is not the information it can process but the social space it inhabits. It gestures, pauses, and responds with the timing of a colleague. Professor DiPaola himself has admitted that, despite decades of teaching and research, he occasionally finds Kia explaining certain concepts more clearly than he can. That admission resonates with many of us who have discovered that AI sometimes performs better at tasks we once considered our strengths. The unsettling question follows: is Kia a substitute for the professor or a complement to him? If it substitutes, it competes with the teacher, offering lectures without fatigue, explanations without limit, and perhaps even performance with greater flair. If it complements, it enlarges the professor’s presence, leaving him to design, mentor, and evaluate while the AI carries the weight of repetition and performance.

DiPaola insists on the latter. Kia will not design the syllabus or grade assignments. Its role is that of a partner in dialogue, a provocateur, an intellectual sparring figure. The authority remains firmly human, while the AI performs more like a chorus in ancient drama: commenting, provoking, and enriching, but never directing. Economists would recognize this as the difference between substitution and complementarity. Calculators did not erase the work of teaching mathematics; they moved it toward problem-solving. Online databases did not make librarians unnecessary; they turned them into navigators of vast digital landscapes. In the same way, Kia does not erase the professor but reshapes the meaning of teaching.

If this experiment works, the classroom becomes more productive. Students gain a source of explanation that does not tire, while lectures acquire immediacy and theatrical power. A professor’s energy is finite, but a digital persona can sustain attention endlessly. Economists call this capital deepening: the process by which new tools increase the return on human effort. Just as tractors increased the yield of farmers, systems like Kia could raise the intellectual return of every hour spent in teaching. Productivity in education cannot be reduced to exam scores alone. It is better measured in comprehension that lasts and insights that endure. By animating concepts in real time, Kia may heighten those outcomes beyond what conventional lectures achieve.

The further horizon is less certain but more provocative. Other educators may attempt their own digital partners: an AI Socrates in philosophy, an AI judge in law, an AI diplomat in international relations. Universities may then institutionalize these figures, treating them as distinguishing assets, just as libraries or laboratories once defined reputation. “Come study with Professor X and EconAI” could become a marketing pitch. With time, the border between teaching and performance may fade. Lectures could evolve into choreographed dialogues where human and artificial voices weave together, and students may come to expect a form of intellectual theatre. The professor’s role would then shift decisively to mentorship, ethical judgment, and the cultivation of wisdom, qualities that resist automation.

The greater risk lies not in adopting such tools too early but in refusing them altogether. Universities that avoid experiments like Kia risk producing graduates unprepared for a world where artificial intelligence is embedded in every profession. Avoidance may seem prudent, yet it carries its own danger: irrelevance. The opportunity cost of inaction is high, which is what makes DiPaola’s decision consequential. By accepting visible dangers such as criticism, failure, or embarrassment, he seeks to prevent the greater invisible danger of an institution unprepared for its future.

The introduction of Kia will not end the debate about AI in education. Critics will argue that it reduces teaching to spectacle and weakens the authenticity of intellectual exchange. Supporters will answer that it enriches learning and mirrors the environment students will encounter in their lives and work. Both positions have weight, but what is certain is that the demonstration will alter the conversation. For the first time, a digital persona will stand on equal footing with a professor in a lecture, and the world will be forced to ask what that means.

The essential question is not whether Kia will surpass the professor but whether educators and universities are willing to design a partnership between human insight and artificial presence. History suggests that institutions willing to take that risk, to transform criticism into knowledge, are the ones that shape the trajectory of change. When Kia begins to speak before students, the trial will not only measure the capacity of an AI system. It will measure the courage of higher education itself.