In the age of AI, the issue is not a lack of real estate information, but rather an overwhelming abundance of it. Some YouTube channels report rising housing prices, while others claim they are falling. Online portals display asking prices, and the government provides actual transaction prices and various statistics. With the advent of generative AI, forecasts about the real estate market are becoming more prevalent. As information floods in, determining what to trust has become increasingly challenging.
The Korea Real Estate Agency's role in the AI era begins here. AI does not set housing prices; rather, prices are determined when buyers and sellers meet, influenced by interest rates, income, loans, supply, population, and employment. No matter how advanced AI becomes, it cannot replace the fundamental principles of this market.
Predicting which apartments will appreciate is a domain for numerous private experts and companies to compete in. The public sector has a different responsibility: to accurately depict what is currently happening in South Korea's real estate market.
The real estate market generates vast amounts of data, including actual transaction prices, asking prices, sales and rental prices, transaction volumes, unsold units, subscriptions, and occupancy rates. However, having abundant data does not guarantee market transparency. It is essential to connect disparate information based on different criteria, filter out errors, and create reliable standards that the public can trust and utilize.
The Korea Real Estate Agency should become an institution akin to the Bank of Korea for real estate data in the AI era. Just as the Bank of Korea's economic statistics serve as crucial benchmarks for economic judgment, the agency's data should be the first resource sought for understanding the real estate market. In the age of AI, institutions with trustworthy data will be more powerful than those with merely abundant data.
AI can bring this data to life. By analyzing countless transactions occurring nationwide, it can quickly identify regions with sudden changes in transaction volumes, transactions that deviate from surrounding market prices, and abnormal movements in sales and rental prices. AI should act as a microscope, revealing market changes that may be overlooked by the human eye, rather than as a fortune teller predicting housing prices.
Translating statistics into language the public can understand is also crucial. Previously, announcements like "apartment prices rose by 0.1%" or "transaction volumes decreased by 10%" were common. Now, generative AI can explain what these numbers mean. For instance, if a citizen asks, "Have transactions in my neighborhood increased compared to last year?" the agency can provide clear, accessible information based on public data.
This service should differ from an 'investment AI' that encourages buying homes or forecasts housing prices. Instead, it should function as a 'real estate AI assistant' that helps citizens find objective facts, enabling them to make their own judgments. AI should not replace human judgment but assist in understanding complex data.
This distinction clarifies the roles of the private and public sectors. Real estate tech companies, portals, and financial institutions can compete to offer more convenient services and innovative analysis models. The Korea Real Estate Agency does not need to compete by creating better apps. Its role is to establish accurate data and standards, providing a foundation for verified data to lead to private innovation.
While the private sector competes in forecasting, the public sector must ensure factual accuracy. There may be differing predictions about which areas will appreciate, but there must be reliable standards for what transactions have actually occurred, how the market is moving, and which data can be trusted.
As the use of AI expands, the issue of accountability becomes increasingly important. In areas like public pricing, which affect taxes, burdens, welfare, and property rights, AI-generated results cannot simply be accepted as correct. It is essential to explain which data was used and why certain outcomes were reached, and if errors occur, humans must correct them, with institutions bearing responsibility.
AI analyzes, humans judge, and institutions are accountable. This is the principle that public AI must uphold. Algorithms should not replace human responsibility. As AI becomes more integrated into significant decisions, the need for explainability, verification processes, and clear accountability becomes even more critical.
The AI transformation that the Korea Real Estate Agency, led by Lee Heon-wook, is pursuing is not merely about implementing a few systems. It involves connecting data, enhancing quality, quickly identifying market changes, and making complex statistics understandable to the public. If successful, the agency can evolve from merely a statistical body into the data infrastructure for South Korea's real estate market.
As AI continues to advance, the number of real estate forecasts will increase. However, an abundance of information does not guarantee the presence of truth. In fact, distinguishing fact from fiction may become more challenging. Thus, paradoxically, the value of reliable public data will grow in the AI era.
The Korea Real Estate Agency does not need to strive to be smarter than the market. It simply needs to provide the most accurate facts to enable citizens to make their own judgments about the market. While the private sector competes in forecasting, the public sector must ensure factual accuracy. Ultimately, the most important asset for the Korea Real Estate Agency in the AI era is trust.
Lee Heon-wook, Director of the Korea Real Estate Agency:
Lee Heon-wook, a former lawyer, has served as the head of the People's Solidarity for Participatory Democracy's Hope for Livelihood Division and as president of the Gyeonggi Housing and Urban Corporation (GH). Since taking office as the director of the Korea Real Estate Agency, he has emphasized fair market order and housing stability for citizens. He is working to establish an accurate and reliable real estate information infrastructure through AI-based research and analysis and innovation in real estate data.
* This article has been translated by AI.
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