Trends on Google: Issues with chatGPT Downtime

Dependence on Generative AI and Its Challenges

On June 10, 2025, users around the world experienced unexpected disruptions with OpenAI's ChatGPT and related services. With the message 'Hmm... something seems to have gone wrong' as the last notification, many people's daily lives came to a halt. It was not just a single chatbot that stopped working. This incident served as a warning of how quickly and profoundly we have come to rely on generative AI.

Normalized AI, but an invisible foundation

ChatGPT is no longer just a simple personal assistant. It plays a central role in a variety of fields, including report writing, email drafting, translation, coding, data analysis, and even video editing. Students rely on it for assignments, businesses utilize it for workflow automation, and developers entrust it with code generation and error checking. When the recent outage occurred, the multitude of users expressing their frustrations on platforms like Reddit, X, and Slack was not merely due to inconvenience, but rather the shock of a structure where work can no longer function without AI.

Interconnected system that stops like dominoes

ChatGPT was not the only problem. Numerous services built on it—Sora, educational tutor bots, counseling chatbots, productivity tools—also came to a halt. Thousands of startups and applications that rely on the OpenAI API essentially share the same roots, and a single failure can domino-effect across the entire ecosystem. This means that, like a power outage in cloud services or power grids, a single point of failure can halt the entire system.

New Risks of the Generative AI Era

We have only looked at the advancement of technology from the perspective of efficiency and innovation. However, this recent disruption raises another issue of vulnerability due to dependency. Questions arise: Are we prepared to carry out our tasks without AI? Is it truly safe to be overly dependent on specific companies (like OpenAI)? Are alternative solutions sufficiently prepared? Without having answers to these questions, we are entrusting countless decisions to AI every day.

Future Tasks

This incident was not just a simple service disruption but a test of the risk management capabilities of society as a whole. In the future, we will face the following challenges: Multi-AI Utilization Strategy: We need to establish parallel usage and alternative strategies for various generative AIs such as Claude, Gemini, and Mistral, not just ChatGPT. Preservation of Offline Work Capabilities: Beyond technological dependence, there is a need for education and training that maintain human-centered critical thinking and responsiveness. AI Governance Based on Public-Private Collaboration: To avoid dependency on specific companies, it is essential to develop open-source AI in the public sector and establish a regulatory framework.

Conclusion

The one-day interruption of ChatGPT was not just a minor incident. It revealed how deeply our society relies on generative AI, while also serving as a warning that we are not adequately prepared. Generative AI is undoubtedly a tool that can change the future, but blind dependence on it can put us at risk of another danger. To maintain this technology as a means, we must develop the ability to coordinate alongside it rather than stand on top of it.