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AI 伦理与安全
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== 核心安全议题 == === 对齐问题 === '''对齐'''(Alignment)指确保 AI 系统的目标与行为符合人类真实意图与价值观。随着模型能力增强,如何避免系统追求被错误指定的目标(即"目标错误规范")成为关键挑战。相关研究包括基于人类反馈的强化学习(RLHF)、宪法式 AI 等方法。 === 鲁棒性与可靠性 === AI 系统应在面对噪声、分布外输入或恶意攻击(如对抗样本)时保持稳定与可靠的表现。鲁棒性研究关注系统在非理想环境下的行为边界。 === 可控性 === 随着自主智能体(Agent)能力的提升,如何确保人类始终能够监督、干预乃至中止 AI 系统的运行,成为安全研究的重点,涉及可中断性、人类监督等机制设计。 === 滥用风险 === 强大的 AI 能力可能被用于生成虚假信息、网络攻击、自动化欺诈等恶意用途。防范技术滥用需要技术防护与制度约束的协同。
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