[2509.20057] Responsible AI Technical Report

Computer Science > Computation and Language arXiv:2509.20057 (cs) [Submitted on 24 Sep 2025 (v1), last revised 19 Mar 2026 (this version, v4)] Title:Responsible AI Technical Report Authors:KT: Yunjin Park, Jungwon Yoon, Junhyung Moon, Myunggyo Oh, Wonhyuk Lee, Sujin Kim, Youngchol Kim, Eunmi Kim, Hyoungjun Park, Eunyoung Shin, Wonyoung Lee, Somin Lee, Minwook Ju, Minsung Noh, Dongyoung Jeong, Jeongyeop Kim, Wanjin Park, Soonmin Bae View a PDF of the paper titled Responsible AI Technical Report, by KT: Yunjin Park and 17 other authors View PDF HTML (experimental) Abstract: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 in...