South Korea - User Protection for Generative AI Services

Overview

The "Generative AI Service User Protection Guideline" was published by the South Korea Broadcasting and Communications Commission (KCC) on 28 February 2025 and entered into effect on 28 March 2025. The guideline is a practical, non‑binding framework for generative AI developers and service providers that sets out four core principles and six implementation approaches to prevent harms associated with AI‑generated text, audio and images. It was developed through a joint KCC‑KISDI research process and stakeholder consultations; the final text and accompanying examples are available from the KCC website for download. The document emphasises proactive risk management, transparency about AI generation, protection of personality and human dignity, and institutional responsibility for remedial measures, with an explicit two‑year review cycle to ensure the guidance stays current as the technology evolves. See the KCC announcement and download page for the full text: KCC – Press release and guideline (PDF).

Definitions

The guideline defines key terms used throughout the text in service‑oriented language: "generative AI services" (systems that create novel content such as text, images, audio, or video derived from learned patterns); "inputs" (user provided prompts, images, voice samples and other training/use data); "outputs" (generated artefacts delivered to users); "user harm" (including privacy invasion, defamation, discriminatory outcomes, and facilitation of illegal acts); and "service provider/developer" (entities operating or delivering generative AI systems). Definitions are functional and tailored to implementation, emphasizing the operational boundary between pre‑trained models, fine‑tuning/continued learning, and runtime generation. The guideline also uses the term "personality rights" to capture harms to reputation, likeness, and identity arising from generated outputs.

Governance and Institutional Framework

The guideline places responsibility on both developers and service providers to adopt corporate governance measures that align with the four principles. It recommends appointing a designated responsible officer for generative AI user‑protection, creating cross‑functional oversight committees (compliant with guidance models reviewed with KISDI), documenting risk‑acceptance processes, and instituting internal monitoring and reporting channels. The KCC encourages collaboration with sectoral regulators (e.g., data protection authorities and consumer protection bodies) and suggests that larger or consumer‑facing services adopt formal accountability mechanisms similar to internal audit or external assurance programs. The document explicitly references the consultative design process used by KCC and KISDI during development; readers can consult KISDI materials and KCC announcements for background: KISDI conference materials and KCC announcement.

Key Focus Areas

The guideline’s execution measures concentrate implementation on six operational priorities: (1) protection of users’ personality and dignity — including detection and control algorithms to prevent non‑consensual likeness generation and defamation; (2) disclosure and explainability — requiring clear labelling of AI‑generated content and provision of accessible information on model behaviour and limitations; (3) respect for diversity and fairness — encouraging bias assessment, filtering tools for discriminatory outputs, and reporting channels for biased results; (4) input data governance — emphasising prior informed consent for using user inputs in training and clarity about retention/use; (5) responsibility and participation in problem solving — expecting providers to define roles and remediation paths and to provide accessible complaint and take‑down procedures; and (6) healthy distribution practices — promoting moderation, platform controls, and contextual guidance to limit spread of harmful outputs. The guideline includes practical examples and suggested controls so operators can apply a risk‑based approach proportional to their service footprint and user base. These focus areas are consistent with KCC’s view of immediate harms (deepfakes, biased outputs, privacy risks) and are intended to be read in conjunction with other national laws and sectoral obligations: KCC guideline.

Implementation Framework

The recommended implementation approach is risk‑based and iterative: providers should (a) map use cases and user populations to identify high‑risk flows; (b) undertake pre‑deployment safety testing and red teaming; (c) apply layered mitigations (input sanitization, output filters, human review on high‑risk outputs); (d) publish transparency materials for users (labels, model fact sheets, high‑level decision flow descriptions); and (e) establish incident response and remediation workflows including user complaint channels, correction/takedown procedures, and post‑incident reporting. The guideline provides examples and checklists to help small and large operators adopt measures proportionate to scale and risk. It also suggests governance artifacts (role descriptions, monitoring dashboards, periodic risk reviews) as practical deliverables for compliance and external scrutiny. For background on the development and stakeholder engagement, see KCC and conference materials: policy briefing (South Korea.kr) and KISDI materials.

Monitoring and Evaluation

The guideline asks providers to maintain monitoring and evaluation programs that combine automated detection metrics (false‑positive/false‑negative rates for harmful output detection), qualitative reviews, user feedback channels, and periodic public reporting of adoption of protections. Providers are encouraged to log inputs and outputs (subject to applicable privacy rules), conduct periodic audits of bias and safety controls, and update models or filters in response to observed failures. The KCC states it will review the guideline’s effectiveness on a two‑year cycle and will consider adjustments or statutory steps based on empirical monitoring and stakeholder feedback. See the KCC release for the stated review cadence: KCC – review commitment.

Penalties, Liability, and Appeals

As a guideline (framework), the document does not itself impose administrative fines; instead it creates an expected baseline of practice that can inform future enforcement actions or referrals. The KCC explains that failure to adopt reasonable protective measures may lead to reputational consequences and to investigations or enforcement actions under existing statutes (for example, personal data protection rules, broadcasting and communications laws, or other consumer protection regimes). The guideline therefore recommends that providers maintain records of measures taken and remediation actions to demonstrate due diligence. It also advises providers to design accessible user appeals and remediation routes for contesting outputs and seeking corrections or takedowns. For the official framing and caveats about enforcement, consult the KCC announcement: KCC press release.

Relationship to Other Instruments

The guideline is positioned to complement existing Korean laws and sectoral regulation — including national personal data protection rules, network and information security rules, telecommunications and broadcasting statutes, and consumer protection measures — and to serve as a practical bridge between technical risk controls and legal obligations. The KCC collaborated with KISDI and other agencies during development; it frames the guidance as interoperable with international instruments and as an input into potential future legislation should voluntary adoption prove insufficient. Providers should map obligations under this guidance to obligations under the Personal Information Protection Act (PIPA) and other applicable statutes in South Korea when designing compliance programs.

International Alignment

The guideline references international best practices and ongoing global policy debates and is intentionally framed to align with common principles found in other national and regional approaches (risk‑based oversight, transparency, human‑centred safeguards, and accountability). While not a legal instrument for cross‑border enforcement, the document signals South Korea’s intent to harmonize expectations for generative AI safety with international frameworks and to coordinate with technical and policy partners. The KCC referenced international examples and engaged external experts during preparation (see KISDI and KCC materials): KISDI and KCC.

Implementation Timeline

Sources and References