发表机构
Hugging Face; Data & Society（Hugging Face; Data & Society）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对AI智能体自主性提升带来的人类监督退化问题，该研究提出需同等重视监督者需求与AI能力，结合自动化和人机交互设计方案以抵消技能萎缩，呼吁开发者采用相关方法。
AI 中文摘要
随着AI智能体被赋予越来越高的自主性，它们带来了重大风险。人们普遍提出的解决方案是人类监督，保持“人类在控制回路中”，但这并非简单的解决方案：当前AI智能体的设计方法不仅阻碍了有效的人类监督，而且长期使用AI系统还会降低执行该监督所需的认知能力。这篇立场文件认为，当前AI智能体系统的开发和部署方法无法支持有效的人类监督——它们会导致人类监督能力的退化。为解决这一问题，AI智能体发展的首要重点应是支持有效人类监督的情境化目标和认知需求，将监督者的人类需求与AI智能体的能力置于同等重要的地位。为将这一理念付诸实践，我们将自动化和人机交互领域的研究与AI智能体过程相连接，概述了设计层面的可供性和组织协议，以（1）支持监督者行使关键判断，（2）抵消长期使用自动化所导致的技能萎缩。我们敦促开发者和部署者采用这些或类似方法。如果不明确支持人机交互的认知需求，AI智能体系统将继续被动地导致其赖以依赖的人类技能退化。
英文摘要
AI agents pose significant risks as they are granted increasing autonomy. A commonly proposed solution is human oversight and keeping a ''human in the loop'', but this is not a simple solution: Not only do current approaches to AI agent design impede effective human oversight, but the cognitive capacities required for it are also themselves degraded by extended use of AI systems. This position paper argues that current approaches to the development and deployment of AI agent systems do not support effective human oversight -- they contribute to its degradation. To address this, a top priority in the advancement of AI agents should be supporting the situated goals and cognitive requirements of effective human oversight, treating the human needs of overseers at the same level of importance as AI agent capability. To put this idea into practice, we connect work on automation and human-computer interaction to AI agent processes, outlining design-level affordances and organizational protocols that (1) support overseers in exercising critical judgement and (2) counteract the skill atrophy that arises from extended use of automation. We urge developers and deployers to adopt these or similar approaches. Without explicit support for the cognitive demands of effective human-agent interaction, AI agent systems will continue to passively incentivize the degradation of the very human skills they rely on.
