While voices calling to temporarily slow down the pace of AI development to ensure safety are growing louder, the reality on the ground is that the development race is actually intensifying. Although companies publicly express concern about risks and advocate for a collective slowdown, there is a deep-seated anxiety that stopping first could lead to being left behind in the competition. Leading companies emphasize risk management, but a uniform deceleration is practically impossible due to China’s aggressive pursuit and conflicting interests within the United States. In fact, major tech companies are rapidly increasing the proportion of AI in their internal R&D operations, engaging in a fight with no room for compromise. In this context, questions are being raised about whether the “slowdown theory” can be a realistic alternative. In this article, we will examine the reality of the slowdown debate surrounding the AI industry and the complex motives of various nations.
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[Into the AI World] The Unstoppable AI Development Race Despite Calls for a Slowdown
1. The Dilemma of the Slowdown Theory
The argument that leading AI companies need time to manage the potential risks of the technology is rooted in the fear of side effects brought about by rapid technological advancement. Major companies like OpenAI and Anthropic have warned that indiscriminate development could lead to uncontrollable situations, urging the entire industry to voluntarily slow down. However, the more these claims are made, the more contradictory the scene becomes, as the very companies making these claims continue their R&D without pause. While shouting about safety on the surface, they are pouring massive resources and time into training next-generation models behind the scenes; this is the honest self-portrait of the industry today. Ultimately, as a game of chicken continues where no one dares to step back first, the slowdown theory risks remaining an empty slogan. No matter how loud the warnings about danger, it is extremely difficult to go against the instinct to secure market leadership. From a corporate perspective, slowing down development is a fatal blunder that immediately cedes the lead to competitors. While they expect someone else to stop first, the idea of their own company stopping is unimaginable; this is the harsh reality. Due to this structural dilemma, attempts to artificially control the pace of AI development are bound to reveal their limitations from the start.
Although the slowdown theory is proposed for safety, actual development speeds are increasing due to companies’ fear of being left behind.
2. China’s Aggressive Pursuit and Huawei’s Counterattack
The force most strongly braking the US-centric slowdown theory is undoubtedly China’s relentless technological pursuit. Major Chinese tech companies, including Huawei, are focusing all their efforts on building their own computing infrastructure, disregarding US semiconductor export restrictions. In fact, Huawei demonstrated its resilience by moving up the launch date of its next-generation AI semiconductor far earlier than originally planned, defying market expectations. US sanctions are ironically acting as a catalyst that enhances the self-sufficiency of Chinese companies. Industry insiders in China point out that they have not yet experienced the safety risks of advanced models that US companies are worried about. Therefore, they argue that rather than slowing down out of fear of risk, they should accelerate to reach a level where they can directly face and manage these risks. The Chinese government is also refining national standards related to AI agents without slowing the overall pace of technological development. The prevailing view is that the leading companies’ slowdown theory is merely a shield to maintain their technological advantage.
China views the US calls for a slowdown as a strategy to maintain the lead, and is accelerating its pursuit, as seen in Huawei’s early chip release.
3. Diverging Interests Within the United States
Even within the United States, opinions are completely divided over how to regulate the pace of AI development, leading to a fierce battle for leadership. Some have argued for the establishment of a public oversight body, similar to financial industry regulators, to manage safety standards across the industry. However, CEOs of giants like Meta, Nvidia, and Tesla have strongly opposed the creation of such a regulatory body, conveying their objections to the White House. They expressed concern that a uniform oversight system would concentrate excessive power in the hands of a few leading companies like OpenAI and Anthropic, undermining fair competition. Their consistent stance is that the responsibility for regulating development speed should be left to the conscience and thorough preparation of individual companies, rather than uniform regulations. In fact, Nvidia’s CEO emphasized self-responsibility by advising that if a product is not sufficiently prepared, its release should be boldly postponed. US President Donald Trump has also expressed reluctance to introduce additional government regulations, citing the risk of falling behind in the national competition with China. The voice demanding control over the potential risks of technology is in a stalemate with the logic that national leadership must not be lost.
Within the US, a power struggle continues as business leaders and the government disagree on the establishment of a uniform regulatory body.
4. AI Agents Taking Over Internal Operations
Even Anthropic, which has been a leading voice for the slowdown theory, is rapidly expanding the scope of AI utilization in its actual internal R&D environment. According to recently released data, Claude, developed by the company, is directly leading a significant portion of its internal R&D work. The proportion of work led by AI has surged by dozens of times compared to just a few months ago, with tens of thousands of AI agents simultaneously performing engineering tasks. This indicates a complete departure from the previous model where humans led research and AI played a supporting role. As such, companies cannot stop their efforts to advance AI to maximize productivity, regardless of external regulatory discussions. As the proportion of internal work handled autonomously by AI increases, the development speed enters a virtuous cycle of exponential acceleration. The moral imperative to slow down exists in theory, but in practice, the top priority is to improve performance as fast as possible, even by a single second. Ultimately, the voice worrying about technological risks and the practical need to pursue performance innovation will continue to clash.
Even companies advocating for a slowdown are heavily deploying AI in their internal research, thereby accelerating actual development work.
5. Doubts About the Effectiveness of Slowing Down
Skeptical views dominate regarding whether regulating the pace of AI development can be effective in the real world. In a marathon involving countless countries and thousands of companies, each with their own interests, it is nearly impossible for everyone to stop just because someone shouts a slogan. If one side brakes, the other side will inevitably try to fill the vacuum, leading to a fierce game of survival. The fear that a temporary pause for safety could lead to permanent exclusion from the market is the driving force that keeps all actors moving. Ultimately, while AI regulation and the slowdown theory provide a good justification for controlling technological risks, they are insufficient to reverse the massive flow of the capitalist market. Even if the government tries to forcibly impose a regulatory framework, it repeatedly hits a wall due to the huge barrier of inter-state hegemony competition. Companies will constantly seek detours to gain technological advantage while avoiding regulations, which will only make the competition more covert and intense. Therefore, rather than clinging solely to the idea of slowing down, it is urgent to develop practical alternatives for minimizing side effects in a rapidly changing technological environment.
Due to global hegemony competition and corporate survival logic, the AI slowdown theory is difficult to achieve in practice.
6. Future Outlook and Challenges
The AI ecosystem is expected to continue a constant tug-of-war between the moral imperative of the slowdown theory and the reality of accelerated development. There is no country on Earth that can resist the temptation of the immense benefits and productivity gains brought by technology. However, the international community’s efforts to establish minimum safety devices and ethical standards amid the indiscriminate speed race will continue. Companies should focus their capabilities on rapidly building safety-verified systems rather than simply slowing down. You, the readers, must accurately understand these complex dynamics in the AI industry and prepare for the future. It is time to pay close attention to how our society can adapt to the pace of technological development and minimize side effects. We need the wisdom to consistently monitor related news and prepare to find a wise path in the unstoppable flood of innovation. Let us watch together as we face the light and shadow of the upcoming AI era and hope for the establishment of a healthy technological ecosystem.
The conflict between speed and safety will continue, and companies and society should focus on establishing effective safety measures rather than just regulation.
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