｢AI 기본법｣의 저널리즘 영역 적용 가능성 — AI 저널리즘 기술의 위험 분석을 통한 투명성 의무 및 고영향 AI 규정 해석 —

This study examines whether the Basic Law on AI Development and the Establishment of Trust (the “AI Basic Law”), scheduled to take effect in January 2026, can function as a regulatory framework that imposes legal responsibility on the use of artificial intelligence (AI) in journalism beyond existing self-regulatory approaches. Taking risk as the core criterion for legal intervention, the study analyzes the operational mechanisms and structural risks of major AI technologies deployed across the news life-cycle, including newsgathering, production, editing, and distribution, and assesses the applicability of the AI Basic Law’s transparency obligations and high-impact AI provisions to journalistic practice. The analysis shows that, in ordinary news production and distribution processes, media organizations and portal platforms generally do not bear direct legal responsibility as AI developers or operators, except in exceptional cases where they directly develop and provide generative AI systems. Moreover, under the current draft guideline framework, journalism is excluded from the first-stage statutory high-impact AI domains, such that the second-stage risk assessment under Article 24 of the Enforcement Decree is not formally required for most journalistic AI technologies. Nevertheless, the study demonstrates that the absence of formal legal classification as high-impact AI does not imply the absence of significant risk. Applying the second-stage risk assessment criteria proposed in the draft guidelines—functional criticality, system reliability, potential harm from malfunction, data accuracy and processing capacity, and the degree of autonomy and decision-making—the study finds that LLM-based automated news writing, AI-generated video production, personalized news recommendation algorithms, and comment detection and filtering systems constitute a high-risk category in practice. In conclusion, the AI Basic Law, as currently structured, does not directly regulate the journalism sector except in highly limited circumstances. While this reflects the principle of minimal regulation in light of freedom of expression and press freedom, it simultaneously reveals a regulatory blind spot in which high-risk technologies that shape the public sphere and information visibility remain outside direct legal oversight. Accordingly, this study argues that the key regulatory task lies not in expanding the formal scope of high-impact AI, but in developing a collaborative, ecosystem-level governance framework. In particular, it suggests that the journalism sector should voluntarily adopt differentiated accountability and internal governance mechanisms for high-risk technologies comparable to those required for high-impact AI. This study aims to provide an analytical foundation for designing such a responsibility-centered and self-regulatory system.