Experiment, Don’t Regulate: The AI Basic Act Should Promote Flexibility and Creativity Through Negative Regulation

AI has established itself as a technology that is reshaping the landscape of industry and society. Generative AI is already complementing human thinking and labor across a wide range of fields, including education, healthcare, finance, and design, and the pace of future technological development will exceed human expectations. In this context, how the state’s institutions and policies respond to this transformative technology is a matter of great importance.

Technology evolves through experimentation, yet we are preoccupied with regulation before institutions have even adapted. The recently passed “Framework Act on AI” emphasizes ethics and safety, but in practice it adopts a control-oriented structure, including prior registration, risk-level classification, and the establishment of a dedicated regulatory body. Imposing a legal framework first on a technology whose direction is still uncertain may stifle creative efforts in the private sector.

Regulation must not get ahead of innovation. This is especially true for early-stage technologies like AI, where diverse experimentation is essential. In an environment where companies must first determine whether each new service violates the law, they are more likely to choose avoidance over bold attempts. Technological development inevitably involves failure and repetition, and institutions must be able to accommodate and support that process.

Through the “Framework Act on AI,” the government has presented the principle of “negative regulation”—that is, allowing everything except what is explicitly prohibited. This approach can encourage more flexibility and creativity than the traditional positive regulatory model, but it remains uncertain how consistently this principle will actually be applied in practice.

To secure competitiveness in advanced strategic industries such as AI and semiconductors, systematic testing spaces such as regulatory sandboxes are essential. By temporarily suspending regulations so that companies can test new technologies in real-world environments, it is possible to pursue both innovation and risk management at the same time. To respond to the complex risks inherent in AI technologies, such as algorithmic bias and violations of personal information, institutional infrastructure must also be built, including data sharing, technology standardization, and global cooperation.

AI in particular is a comprehensive industry closely linked to semiconductors, data, and talent. Alongside the creation of experimental spaces, institutional reforms that can support the entire industrial ecosystem must proceed in parallel. Expanding R&D investment, easing working-hour regulations, creating advanced industrial clusters, establishing related academic departments, and improving enrollment quota regulations are all essential conditions for accelerating technological innovation and securing talent. Laws and institutions designed to grow industry must contain both regulatory easing and incentives for experimentation.

Korea now stands at a crossroads. It must decide clearly whether it will create institutions that foster industry or laws that suppress it. It should encourage creative attempts while holding actors clearly accountable, and it must institutionally provide a space for free experimentation in between. What is needed is not regulation that limits the possibilities of technology, but institutions that help realize those possibilities.

The government must redefine its role—not as a supervisor or regulator, but as a facilitator that provides infrastructure and space for experimentation. Creating an environment in which the private sector can innovate freely and consumers can choose freely—that is the key to future competitiveness.

Experimentation is both the foundation of R&D and the final means of verifying policy. Only by creating an environment where experimentation is possible and supporting effectiveness-oriented R&D can innovation truly happen. Rather than relying on regulation for control, we must build a system in which one experiment can reduce ten instances of waste, and one verification can prevent ten failures. The truth that experimentation must come before regulation remains just as valid in this era of technological competition.

Sang-yeop Kim, Researcher, Center for Free Enterprise (CFE)

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Original title: 규제보다 실험, ‘AI 기본법’ 네거티브 규제로 유연성과 창의성 장려해야

Author: Sang-yeop Kim

Date: 2025-07-29

Source: https://www.cfe.org/bbs/bbsDetail.php?cid=press&idx=27931