[Lim Woong] When competence becomes cheap

Professor Lim Woong argues that AI and other powerful technologies do not destroy expertise but relocate it, drawing parallels to historical shifts caused by photography, the postal service, and medical AI. He observes that his graduate students now wield AI tools to produce professional-level work, prompting a societal renegotiation of what expertise means. Lim contends that lower-order skills become automated while higher-order, richer problems emerge for human experts.

Last spring, I sat through a presentation by some of my graduate students and felt something I had not felt in twenty years of teaching: the quiet panic of being surpassed. Their slides were better than mine. The analysis looked like professional work. My students had not yet achieved mastery. But they were wielding AI tools in ways that made them look like experts. We are in the middle of one of those periodic crises in which an entire society must renegotiate the meaning of expertise. We have been through this before, and if you look back across the centuries, you can almost see the pattern. Each time a powerful technology arrives, the prophets of doom and the prophets of utopia go head-to-head, and nobody wins in the end. Consider three historical episodes that illuminate what is happening now. First, when photography arrived in the 1830s, the panic in art studios was real and nearly existential. Painters who had spent lifetimes perfecting the rendering of the human face suddenly confronted a machine that could do the same thing faster, cheaper and without complaint. The trade journals of the period were funereal. But photography did not destroy painting. It liberated it. Painters were released from the obligation of accurate mimesis, opening the door to Impressionism, Cubism, Modernism and the magnificent arc of twentieth-century art. The painter's job changed. It was no longer about reproducing the world faithfully, but about rendering the world as it is felt. Expertise moved upward, and the painter found himself solving a different, ultimately richer problem. Consider, second, the postal service, which many people in the 1990s had declared dead. Email would replace letters, and the post office would close. But the post office did not vanish. It migrated. It became the logistical backbone of e-commerce, part of a vast choreography of supply chains that can move a parcel from Berlin to Seoul in three working days. The skill of hand-sorting letters became the skill of coordinating goods across continents. The letters themselves, paradoxically, became more precious than they had been in the era of necessity. They are now small, deliberate artifacts of affection, written on heavy paper by people who mean what they say. Then there is medicine, where the deeper revolution is taking place. When IBM’s Watson entered oncology, the obituaries for physicians were written again. A newer system such as Microsoft’s MAI Diagnostic Orchestrator, tested on difficult published diagnostic cases, has reported accuracy higher than that of participating generalist physicians. Here was a computer that had read every medical paper, never grew tired and knew things no single doctor ever could. Still, people head to the hospital when they realize they need real physicians. Yes, people look up symptoms online, especially those troubling questions they feel too embarrassed to ask a doctor. The internet has become our doctor. But when you see a good doctor, you choose them over your AI chatbot. In that respect, little has changed. What has changed is the ecology of medicine. Surgical robots now sit in operating rooms, translating a surgeon's movements into microscopic precision. Biomedical engineering has become a quiet miracle: artificial joints that let grandparents walk again, cochlear implants that bring sound to a deaf child, and prosthetic limbs that respond to neural signals. More people are living longer and better because surgeons and engineers have learned to speak the same language. The boundaries among medicine, biology, engineering and data science have become wonderfully porous. New specialties have emerged, and older ones have grown more sophisticated. So there is, I think, a pattern. New technologies do not so much destroy expertise as relocate it. They sweep away lower-order functional skills, such as rendering a face exactly, hand-sorting the morning post, or memorizing a voluminous textbook, and deposit them partly in the realm of machines and partly in the realm of craft and nostalgia. The human, if fortunate, is promoted unmistakably to a harder problem. This is the part of technological change that few talk about because it is not glamorous. Instead, people talk about productivity and which professions will disappear and which will be re invented. Yet we do not talk enough about the inner life of the worker who survives the transition, or the moral cost of having to remake oneself again and again over the course of a career. Watching my colleagues and my students at Yonsei, I have noticed that the question is no longer simply, "What do I know?" It is becoming, "Who am I, and what do I bring to the table that others will value and support?" That is not merely a technical question. It is also a moral one. In fact, it may be the oldest moral question there is. Adam Smith observed that economic life rests on a foundation of sympathy, moral imagination and the capacity to see oneself in another. The same is true, I suspect, of the intelligence economy taking shape around us. The technology will be spectacular. The efficiency will be dazzling. But the foundation on which the whole edifice rests will remain human: the look in a doctor's eye, the sentence a teacher takes time to choose in order to motivate a struggling student, the way a colleague remembers your daughter's name. These are not soft skills. They are the load-bearing walls of a civilized life. I do not know what expertise employers will expect from college graduates in 2030. I do not know which skills will become obsolete or which will prove unexpectedly precious. But I have come to believe that the protagonist of whatever comes next will not be a model. It will be the student who holds on to those small, stubborn, irreducible qualities: attention, presence, the capacity for surprise, a commitment to service, high ethical standards, and a sense of agency, that is, the willingness to keep showing up on the days when it would be easier not to. No high-tech system can do that for us. And in the end, that may be what matters most. - - - Lim Woong Lim Woong is a professor at the Graduate School of Education at Yonsei University in Seoul. The views expressed here are the writer’s own. — Ed. khnews@heraldcorp.com