In the middle of the 21st century, South Korea's disaster safety system remains trapped behind the "analog fences" of the 20th century. Even more deplorable is that while the nature of disasters is becoming increasingly complex and violent due to climate change, the bureaucracy in charge of safety policies and regulations remains idle, failing to even include the word "AI (Artificial Intelligence)" in its legislation.

1. Archaic Disaster Management Practices Unsuited for the Advanced Scientific Era

 While technology is knocking on the doors of the field with breathtaking advancements, those in charge of the law remain complacent, comfortable in their vested interests. They stifle the seeds of innovation by citing "unverified safety" and "regulatory walls," while relevant government departments engage in a game of ping-pong to avoid responsibility, claiming that incorporating AI into legislation is a new, untested endeavor. Do these bureaucrats truly not realize that such negligence constitutes a dereliction of duty that leaves the public's safety abandoned?

We live in an era where unprecedented disasters—such as massive wildfires, electrical fires in complex urban buildings, and battery thermal runaways—threaten our daily lives. Yet, our fire safety system remains stuck in a reactive mode of "detecting, reporting, and deploying to suppress after a fire has already broken out."

2. Why We Must Reform the Disaster and Safety Management Act First

 It is time to clearly introduce the concept of "forecasting" into the Disaster and Safety Management Act and the Fire Prevention Act. This is because the damage caused by a disaster is a function of time. Insisting solely on post-disaster response in the face of fires that spread by the second is inadequate for protecting human lives. Legislating "forecasting" is both a testament to our resolve to shift the paradigm of national disaster response and safety policy from "recovery-centered" to "preemptive prevention," and a fundamental duty of the state. The reasons for prioritizing the amendment of the Disaster and Safety Management Act are as follows:

∆ Codifying the legal definition of "AI-based forecasting": An "early warning system," through which AI detects and notifies of precursor patterns before disasters and fires occur, must be mandated as a legal requirement.

∆ Making forecasting systems mandatory for state-managed facilities: A legal basis for mandatory adoption must be established so that innovative private technologies can be immediately implemented in the public sector.

∆ Removing barriers to technology adoption through regulatory innovation: We must introduce flexible technical standard guidelines that allow AI technology to be integrated into the field without being constrained by outdated facility standards.

∆ Reorganizing field operations based on data: The national disaster management paradigm must be completely transformed from "post-disaster recovery" to "preemptive prevention based on digital data."

∆ Institutional basis for digital safety platforms: The legal responsibilities and authority for technology utilization must be clearly defined so that AI can function as a core tool for disaster situation rooms and on-site command.

3. Expected Benefits of Integrating the "AI-based Forecasting" Concept into the Disaster and Safety Management Act

∆ A grand shift in the disaster management paradigm: Reflecting the concept of "AI-based forecasting" in the Disaster and Safety Management Act will drive a national paradigm shift from "reactive response" to "preemptive prevention," contributing to a safer human civilization.

∆ Maximizing response capabilities: AI can analyze report contents in real-time to secure a golden time and suggest optimal dispatch routes, thereby increasing the success rate of initial suppression.

∆ Ensuring firefighter safety through the scientific approach of field command: Digital twins and AI simulations can predict fire spread paths to prevent misjudgment by on-site fire commanders, while thermal imaging drones can visualize hidden risks to minimize casualties among rescue personnel.

∆ Blocking disasters at the source through constant monitoring: By combining IoT sensors and data analysis algorithms, we can proactively detect high-risk factors like aging facilities and batteries, creating an intelligent, 24/7 preventive safety net.

4. Disasters Are Not an Unavoidable Fate; We Must Reduce Them Through Human Will

 Disasters are subjects of management that can be predicted and controlled through data. We must conduct a comprehensive review of the outdated regulations hiding behind the complacency of the bureaucrats who draft safety policies, remove those that do not fit the era of scientific advancement, and allow the law to give wings to AI technology.

Moving toward an era of digital safety that blocks disasters at the source is the most solid duty of a nation to protect the lives of its people and an inevitable task of our time. Relevant safety departments must contribute to building a safer world by adopting AI-based technological innovation. I sincerely hope that this advice regarding South Korea's safety management is taken to heart.

◆ Young-jin Cho, CEO

CEO of Roze AI