大模型时代，AI责任体系需从单一控制转向分布式持续监管。
The AI Accountability Ecosystem in the Era of Language Models
- 将责任体系扩展至AI基础设施与供应链
- 强化结果监测以支持去中心化系统改进
- 纳入终端用户责任，应对语言模型的不可预测风险
本文基于最新发展更新了AI责任生态系统框架。针对通用大语言模型发布以来的变化，提出三项相互关联的调整：（i）将责任体系重新聚焦于AI基础设施与供应链；（ii）加强结果监控与问题识别，推动去中心化系统优化；（iii）引入终端用户责任，应对语言模型在真实场景中的不可预测性。这些更新标志着责任机制正从集中、离散、由单一主体控制的模式，转向分布、持续、制度化的形态，不再局限于行业特定监督下的前沿应用产品化管理。
原文摘要 · Abstract (English)
This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the latest developments since the release of Large Language Models for general public use. We propose three interlinked updates to the original AI accountability ecosystem: (i) reorienting the accountability ecosystem to AI infrastructure and supply chains, (ii) providing greater emphasis on outcomes monitoring and identification of issues that support decentralized system improvement, and (iii) incorporating end-user accountability given the new risks of unpredictability of language models in-the-wild. Collectively, these updates mark a shift towards accountability as distributed, continuous, and institutionalized, away from a system in which frontier AI applications can be modeled as discrete products controlled by single identifiable actors with industry-specific oversight.
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