Coding as Design in the Age of AI

Taery Kim, Ph.D. | Director of Carnegie Institute

Artificial intelligence is forcing educators, policymakers, education institutions, and parents to confront a reality that can no longer be ignored: AI systems once regarded simply as tools now retrieve knowledge, perform calculations, and generate images, code, and even design concepts with a fluency that has already surpassed human expertise in some domains, while rivaling it in many others. In this new environment, education must not train children to perform tasks that AI can already do more efficiently but cultivate the strictly human skills that AI may be able to imitate, but can never replace.

The essential human advantage now lies not in solving problems already given, but in defining them: in asking questions of consequence, situating them within human contexts, weighing their ethical implications, and sustaining inquiry and creativity through uncertainty. Nowhere is this question more urgent than in the field of coding education, where the rhetoric of creativity and critical thinking collides with the reality of competitions, certifications, and drills.

Schools and academies often highlight “creativity” as an important part of their coding curricula. Yet what determines success remains what is easily quantified: robotics contests, algorithm Olympiads, timed drills, and technical certificates. Students are rewarded for solving problems with speed and building solutions based on technicality, rarely for endurance, inquiry, creativity, or appropriateness of design in human contexts. Coding should serve as a gateway to new forms of thought, but too often it has become another treadmill of measurable performance, disguised in the language of innovation and creativity.

Now, in the age of AI, where the technicality of coding is increasingly irrelevant, and in light of Korea’s decision to make coding mandatory from 2025, the stakes have intensified. Without a shift in pedagogy, this mandate risks further amplifying competitions and credentials while preparing children for tasks that AI will perform more quickly. Infrastructure and access are not enough; what matters is a pedagogical reframing of coding education.

What is needed is not the abandonment of coding but its re-grounding. The paradigm must shift from coding as programming to coding as design, from technical drill to computational design thinking. At its heart, this is not only a pedagogical framework but also a call for the Humanities to return to the forefront of education.

Computational design thinking integrates the methods of computing with the insights of human-centered design and the interpretive traditions of the Humanities. It anchors coding in the questions that have always defined human life: Why does this matter? For whom? At what cost? These are not technical questions, but ethical and cultural ones; they require the enduring skills of inquiry, reflection, and interpretation.

Students, therefore, must be guided to:

  1. Begin with research into human contexts

  2. Define problems before rushing to solve them

  3. Apply human-centered design methods to build unique solutions for human contexts

  4. Judge solutions by appropriateness and ethical consequence

  5. Treat code as a medium for collaboration and storytelling

In this way, coding becomes more than a technical skill. It becomes an entry point into the Humanities, a practice of inquiry and reflection, a space to cultivate judgment, empathy, and responsibility. These are the very capacities that AI can never truly replace.

Korea’s decision to make coding mandatory in 2025 is, therefore, a pivotal moment. If pursued as technical training alone, it will intensify competitions and credentials, preparing children for tasks AI will perform more efficiently. But reframed as computational design thinking, coding can become a gateway to the deeper capacities rooted in the Humanities: curiosity, endurance in uncertainty, ethical responsibility, and the ability to situate problems within human life.

The age of AI demands more than rote knowledge or technical training. It demands better questions, human judgment, and the courage to ask why. By bringing the Humanities back to the center of education, we can ensure that students are not only equipped to use AI but prepared to shape the human futures in which AI will operate.

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