AI 中文总结
该研究指出AI锁定是被低估的AI安全风险，分析其在个体、社会、国家层面的形成与升级机制，提出需提前应对以维护自主权与国家安全。
AI 中文摘要
AI安全研究主要聚焦两个领域：技术对齐（确保AI系统生成符合人类偏好的输出）以及生成式AI社会影响的监管（包括失业风险和劳动力市场动荡）。然而，一个同等重要却被低估的维度是：依赖AI系统本身所带来的风险。在这篇立场论文中，我们提出AI安全研究应关注AI锁定（AI Lock-In）这一现象——即过度依赖AI系统会导致人类技能退化、削弱人类独立行动的能力，并在AI系统不可用或被破坏时引发系统性脆弱性。我们强调，AI锁定是一种已在个体、社会和国家层面显现的系统性威胁，可能因AI服务中断或地缘政治冲突而大幅加剧。通过详细场景分析，我们研究了AI锁定如何在多个层面出现并升级，从个体技能萎缩到国家层面的基础设施故障。为应对这一问题，我们针对各层面如何缓解和准备此类风险提供了指导。我们认为，在这种依赖关系变得根深蒂固甚至不可逆之前，主动解决AI锁定问题，对维护个体自主权和国家安全至关重要。
英文摘要
AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of generative AI's societal impacts (including unemployment risk and labor market disruption). However, an equally important dimension remains underexplored: the risk inherent in dependence on AI systems themselves. In this position paper, we argue that AI safety research should address AI Lock-In, the phenomenon whereby excessive reliance on AI systems leads to human deskilling, diminishes human capacity for independent functioning, and creates systemic vulnerabilities when AI systems become unavailable or compromised. We highlight that AI Lock-In is a systemic threat that is already emerging at individual, societal, and national levels, one that could be dramatically amplified by AI service disruptions or geopolitical conflicts. Drawing on detailed scenarios, we investigate how AI Lock-In emerges and escalates across multiple levels, ranging from individual skill atrophy to national-scale infrastructure failures. To address this, we provide guidance on how such risks can be mitigated and prepared for at each level. We contend that proactively addressing AI Lock-In before such dependencies become entrenched, or even irreversible, is essential for preserving individual autonomy and national security.
CommentsICML 2026 Position Track Spotlight
