KT推出AI安全评估与风险管控技术，提升AI服务可靠性。
Responsible AI Technical Report
- 基于本土环境构建AI风险分类体系，系统识别全周期风险
- 提出验证模型安全与鲁棒性的评估方法，支持实际风险管控
- 开源实时防护工具SafetyGuard，助力国内AI生态安全
KT开发了负责任人工智能（RAI）评估方法与风险缓解技术，确保AI服务的安全性和可靠性。通过分析《AI基本法》实施情况及全球AI治理趋势，建立了符合本土监管要求的方法体系，系统识别并管理从AI研发到运营全过程中的潜在风险因素。本文提出一种可靠的评估方法，依据适用于本国环境的KT AI风险分类体系，系统验证模型的安全性与鲁棒性，并提供实用的风险管理与缓解工具。随着本报告发布，KT还开源了专有防护工具Guardrail: SafetyGuard，可在实时运行中拦截有害响应，支持本土AI开发生态的安全性提升。研究结果对寻求发展负责任AI的组织具有重要参考价值。
原文摘要 · Abstract (English)
KT developed a Responsible AI (RAI) assessment methodology and risk mitigation technologies to ensure the safety and reliability of AI services. By analyzing the Basic Act on AI implementation and global AI governance trends, we established a unique approach for regulatory compliance and systematically identify and manage all potential risk factors from AI development to operation. We present a reliable assessment methodology that systematically verifies model safety and robustness based on KT's AI risk taxonomy tailored to the domestic environment. We also provide practical tools for managing and mitigating identified AI risks. With the release of this report, we also release proprietary Guardrail : SafetyGuard that blocks harmful responses from AI models in real-time, supporting the enhancement of safety in the domestic AI development ecosystem. We also believe these research outcomes provide valuable insights for organizations seeking to develop Responsible AI.
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