提出六要素设计框架，破解人机协同效能不足的难题。
Addressing the Synergy Gap: The Six Elements of the Design Space
- 构建六要素协同设计空间，涵盖情境、决策、角色、能力等维度。
- 实证表明当前人机协作多为辅助而非真正协同，存在明显效能缺口。
- 适合系统设计师、研究者及评估者使用，推动全面人机协同评价。
人工智能已广泛应用于医疗、金融、政策等领域，但真正的人机协同——即双方合作表现优于各自独立时——却极为罕见。元分析显示，人工智能辅助能提升人类表现，但实现真正协同的研究仍属少数。我们称此现象为‘协同差距’。现有研究多聚焦可解释性、信任校准或界面设计，仅覆盖部分影响因素。我们认为，弥合协同差距需拓展至更广泛的系统设计空间。本文提出由六个相互关联的要素构成的设计框架：社会技术背景、决策框架、人类参与者、AI能力、交互方式与整体评估。针对每个要素，阐明其内涵、与其他要素的互动机制及对设计的影响。该框架为人机混合系统开发者提供通用术语，为研究者提供分析视角，并为评估者提供超越准确率的综合评估起点。
原文摘要 · Abstract (English)
AI is now embedded in healthcare, finance, policy, and many other domains, yet genuine human-AI synergy - combined performance that exceeds what either party achieves alone - is uncommon. Meta-analyses show that AI assistance tends to improve human performance compared to working alone, but studies finding true synergy are scarce. We call this persistent shortfall the synergy gap. Most current work treats human-AI combination as an engineering problem and concentrates on interpretability, trust calibration, or interface design. These matter, but they cover only part of what determines whether combination works. Closing the synergy gap, we argue, requires explicit engagement with a wider design space. We map that space through six interconnected elements: sociotechnical context, decision-making frameworks, human decision participants, AI capabilities, interaction, and holistic evaluation. For each element, we describe what it covers, how it shapes the others in practice, and what it implies for design. The result is a shared vocabulary for practitioners building hybrid systems, an analytical lens for researchers studying combination patterns, and a starting point for evaluators interested in the full quality of human-AI decision-making rather than accuracy alone.
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