cs.AI updates on arXiv.org 09月25日
RAI评估与风险缓解技术
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本文介绍了KT开发的负责AI(RAI)评估方法和风险缓解技术,以确保AI服务的安全性和可靠性。通过分析AI实施的基本法和全球AI治理趋势,建立了独特的合规监管方法,并系统性地识别和管理所有潜在风险因素。本文提出了基于KT AI风险分类法的可靠评估方法,以系统验证模型的安全性和鲁棒性,并提供识别的风险管理的实用工具。同时,本文还发布了Guardrail : SafetyGuard,用于实时阻止AI模型的有害响应,以支持国内AI开发生态系统的安全提升。

arXiv:2509.20057v1 Announce Type: cross 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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人工智能 风险评估 风险缓解 RAI AI治理
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