The regulatory landscape for technology and media is undergoing a significant transformation, driven largely by the rapid advancement and widespread adoption of Artificial Intelligence (AI). Previously, issues related to broadcasting and telecommunications were handled by a single regulatory body. However, the same concerns can now draw the attention of multiple agencies simultaneously, including those overseeing personal information protection, fair trade, and science and technology, as well as legislative bodies. This overlapping jurisdiction presents a complex challenge for businesses operating in the tech sector.
The Evolving Regulatory Environment
According to legal experts, a key shift in the regulatory environment is the increasing overlap between different legal frameworks. What was once considered a matter solely within the purview of broadcasting and telecommunications regulators can now also involve issues related to personal information, fair competition, data security, and user notification. This is particularly true as AI services are integrated into platforms, data processing, and traditional media offerings.
Previously, regulations for broadcasting, personal information, fair trade, and media operated relatively independently. However, the current environment means that even minor adjustments to a platform’s recommendation algorithms can trigger concerns across multiple regulatory domains. Companies utilizing large language models (LLMs) must now consider the source of training and input data, the basis for personal information processing, and potential cross-border data transfers – all simultaneously.
Introducing the Integrated TMT Center
To address this evolving complexity, the law firm Yulchon has established an integrated Technology, Media, and Telecommunications (TMT) Center. This specialized unit consolidates expertise in broadcasting and telecommunications regulation, licensing and market entry, personal information and data, AI and new technologies, cybersecurity, platform fair trade, and response to misinformation and disinformation. The center is spearheaded by experienced lawyers who have previously managed significant business operations and includes contributions from other seasoned legal professionals.
While Yulchon has a history of interdisciplinary collaboration, the firm recognized that project-specific cooperation was insufficient in the current AI-driven era. The creation of the integrated TMT Center signifies a move towards a more permanent, unified approach to tackling these multifaceted regulatory challenges.
Navigating AI-Related Risks
Platform services fundamentally rely on how data is collected, utilized, and connected to user services. When algorithms are modified, even slightly, it can lead to a cascade of issues beyond fair trade, potentially impacting personal information, data security, and overall service integrity. During this transition period, where traditional platform services are merging with AI capabilities, companies must consider data flow, algorithmic impact, user notification, security, and fair trade practices from the initial stages of service design.
The risk of conflicting regulatory interpretations is significant when agencies address issues independently. A rationale developed with one agency’s perspective in mind might be misunderstood or incompatible with another agency’s requirements. This necessitates a coordinated effort to ensure a consistent and coherent regulatory strategy.
Furthermore, legislative bodies play a crucial role. Discussions around new laws, data requests, and public opinion formation can substantially influence the regulatory environment. Relying solely on broadcasting and telecommunications perspectives may prove insufficient when facing scrutiny from consumer groups, fair trade bodies, or legislative committees.
Common Misconceptions in AI Compliance
One of the most significant mistakes companies make regarding AI compliance is focusing exclusively on the AI Basic Act. While AI-specific regulations are important, real-world compliance often involves a complex interplay of laws governing personal information, copyright, advertising, and fair trade. Implementing an AI service requires a holistic review, encompassing data collection and usage, output display, consumer protection, and potential competitive restrictions, not just the AI Basic Act itself.
Companies using external LLMs must exercise extreme caution regarding data. This includes verifying the source and legitimacy of incoming data used for training and ensuring proper authorization for any outgoing data or delegated tasks. Cross-border data transfers are particularly sensitive; without appropriate agreements, they can lead to substantial penalties, especially when dealing with foreign entities.
The most perilous type of data in AI training involves sensitive personal information. Beyond legally defined sensitive data, information that individuals perceive as private—such as health, genetic, financial data, or details about union membership—requires careful handling. Robust metadata management is essential to track the source, legal basis, and scope of retention and usage for all collected data.
Ensuring Fair Competition and Data Security
In cases of alleged market dominance abuse by platforms, not only the outcome but also the intent and purpose behind actions are critical. Fair trade authorities often examine internal documents, chat logs, and emails to ascertain intent. Companies must maintain documented evidence demonstrating that algorithm changes were made to enhance user convenience and satisfaction.
In the event of a cyber intrusion, prompt action is crucial. The immediate priority is to identify the root cause and implement containment measures if there’s a risk of ongoing data leakage. Subsequently, it’s vital to determine the extent of any data breach and assess reporting and notification obligations. Delays in response can fuel suspicions of concealment and increase the burden of managing consumer dissatisfaction and public backlash.
The Yulchon Integrated TMT Center’s Unique Approach
The strength of Yulchon’s integrated TMT Center lies in its collaborative culture. However, the current AI and digital regulatory shifts demand more than just project-based cooperation; they require a continuously integrated response system. By moving beyond the level of individual team collaboration to operate as a single unit, the center enhances information sharing speed and the intensity of cooperation.
This integrated approach allows companies to have their AI, data, personal information, fair trade, and cybersecurity issues reviewed and addressed within a unified framework, rather than dealing with each issue separately. This offers a significant advantage for businesses navigating the complex regulatory landscape.
Key Risks for TMT Businesses in the Coming Year
The core challenge for TMT businesses this year is integration. Risks must be viewed from multiple perspectives, and a unified direction is essential to provide effective solutions to clients. As AI and data permeate all aspects of the tech industry, businesses require comprehensive, one-stop solutions to manage these complex and interconnected challenges.
