自动化的边界：持续人类参与理论

中文摘要 AI 辅助

人工智能的快速发展加剧了对自动化的长期追求，即尽可能用算法取代人类参与，这种追求隐含着人类仅因当前人工智能系统能力不足而留在循环中的假设。本文挑战这一假设，探讨自动化的概念极限，认为即使在人工智能系统能力很强时，人类参与仍可能持续，原因有技术或互补性、规范性或发展性、目标涌现性。人类与人工智能共同构建不仅是对不完善人工智能的临时应对，而是目标通过参与涌现的活动的持久特征，这对自动化极限及未来人工智能系统设计、评估和伦理有重要意义。

英文摘要

The rapid progress of AI has intensified the long-standing pursuit of automation: replacing human participation with algorithms wherever possible. Implicit in this pursuit is the assumption that humans remain in the loop only because current AI systems are not yet sufficiently capable. This paper challenges that assumption. Rather than asking how far automation can extend, we ask where its conceptual limits lie and argue that human participation may persist even with highly capable AI systems for three distinct reasons. Technical or complementarity grounds arise when humans contribute capabilities or perspectives unavailable to AI. Normative or developmental grounds arise when participation itself is valuable for human agency or learning. Most importantly, emergence grounds arise from target emergence: in some activities, the target is not fully specified in advance but instead emerges through the interaction itself. In these cases, human participation is not merely a means of improving execution but is constitutive of the target being produced. Human--AI co-construction, understood as the joint production of outcomes by humans and AI systems, is therefore not simply a temporary response to imperfect AI, but a persistent feature of activities whose objectives emerge through participation. This perspective has important implications for the limits of automation and for the design, evaluation, and ethics of future AI systems.

发表机构

• TU Darmstadt（达姆施塔特工业大学）
• LMU Munich（慕尼黑大学）

机构由 AI 辅助整理，请以论文原文为准。