[Reading Science]Before Creating an AI Department

Is AI an Academic Discipline or a Tool?

The University Craze for "AI" Begins with the Name

The Korea Advanced Institute of Science and Technology (KAIST) is preparing to establish an AI College, while the Daegu Gyeongbuk Institute of Science and Technology (DGIST) is planning to launch an AI Department. However, what exactly will be taught in these programs remains unclear. There is no disagreement about the importance of artificial intelligence (AI). Yet, simply acknowledging the significance of AI does not necessarily justify the immediate need for an AI department.

Recently, universities have been rapidly introducing new AI departments, AI convergence departments, and AI graduate schools. Just as semiconductor and big data departments became popular a few years ago, AI has now become the most powerful brand in higher education. However, universities are not institutions that merely chase trends; rather, they are places that teach knowledge that endures even after trends have faded.

The real issue is not speed, but direction. While universities talk about cultivating AI talent, they have yet to provide clear explanations about what kind of curriculum they will offer or how it will differ from existing computer engineering or software programs. Sometimes, it is even unclear whether the curriculum should come first or the department's name.

Perhaps there is a fundamental question we have yet to answer: Should AI be taught as an independent academic field, or is it a new tool that every discipline should utilize?

Universities are supposed to teach not just the tools themselves, but how to use those tools to understand the world and solve problems. Researchers use AI to discover new drugs, meteorologists use AI to predict precipitation, and engineers use AI to design semiconductors. The key is not AI itself, but the problems that can be solved through AI.

Even more pressing questions concern today's students. University freshmen now arrive having already used AI to study, code, and complete assignments. Some possess application skills that rival those of professionals in the field.

What, then, can universities teach students who already know how to use AI over the course of four years? This is not a question about the necessity of AI departments, but rather about their very reason for existence.

If the purpose is merely to teach how to use AI services, it is difficult to justify the role of university education. Generative AI evolves every few months. Usage instructions can be learned more quickly on YouTube or through online courses than in a classroom.

The role of universities is not to teach which buttons to press. Rather, it is to help students understand the principles behind AI, recognize the limitations of algorithms, and consider how AI can be applied in various industries and academic fields.

This changes the question: Is expanding the number of AI departments the answer, or should AI education be integrated throughout the entire academic system?

Universities abroad are also expanding AI education. However, the focus is not on the AI name itself, but on combining AI with existing disciplines. For example, Nanjing University of Information Science and Technology in China operates an educational model that merges atmospheric science and AI, and major universities in the United States are prioritizing the integration of AI throughout their curricula rather than creating separate AI departments. At the same time, there are concerns about "hastily rebranded" programs and "purposeless AI degrees" that simply repackage existing courses under the AI label.

Ultimately, the key is not the name "AI department." It is the ability to explain what AI is combined with, what problems it will help solve, and how it differs from existing disciplines.

In the future, society will need not only AI experts, but also people who deeply understand their own fields and can apply AI within them. However, at present, many AI departments at universities remain indistinguishable from computer engineering, software, or data science departments.

Of course, AI education must be expanded. However, simply attaching "AI" to everything is not innovation. Creating new departments should not be an administrative decision that follows trends, but a philosophical declaration about the kind of talent a university seeks to nurture.

What is needed in the age of AI is not more AI departments. Instead, we must first be able to explain why AI should be taught, what should be taught, and how it differs from existing academic disciplines. If we continue to create departments without first answering these questions, we risk not teaching AI, but simply consuming the "AI" label.

This content was produced with the assistance of AI translation services.