Responsible AI Technical Report

arXiv cs.CL / 3/23/2026

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Key Points

  • KT developed a Responsible AI (RAI) assessment methodology and risk mitigation technologies to ensure the safety and reliability of AI services, aligning with domestic regulatory framework and global governance trends.
  • The report presents a comprehensive risk taxonomy and a systematic method to verify model safety and robustness from AI development through operation.
  • It includes practical tools for managing and mitigating identified AI risks and introduces a proprietary Guardrail called SafetyGuard that blocks harmful responses from AI models in real time.
  • The release aims to guide organizations in developing compliant, responsible AI within the domestic ecosystem and to advance safety across the AI lifecycle.

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 insights for organizations seeking to develop Responsible AI.

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