提出人机协作中决策者心智模型的演化框架。
Development of Mental Models in Human-AI Collaboration: A Conceptual Framework
- 构建三类互补的心智模型：领域认知、信息处理、协同意识
- 揭示数据上下文化、推理透明度、绩效反馈三大驱动机制
- 为设计高效人机协作提供可落地的理论指导
人工智能已深度融入组织决策过程，但现有研究多聚焦AI系统设计与协作架构，通常假设人类决策者是固定的。本文填补这一空白，提出人机协作中三种相互依赖的心智模型——领域认知、信息处理和协同意识——的演化机制。通过构建整合性社会技术框架，识别出数据上下文化、推理透明度和绩效反馈三类核心驱动力。研究贡献包括：明确三类心智模型的构成；强调其动态演化特性；建立可引导有效协作设计的机制体系。
原文摘要 · Abstract (English)
Artificial intelligence has become integral to organizational decision-making and while research has explored many facets of this human-AI collaboration, the focus has mainly been on designing the AI agent(s) and the way the collaboration is set up - generally assuming a human decision-maker to be "fixed". However, it has largely been neglected that decision-makers' mental models evolve through their continuous interaction with AI systems. This paper addresses this gap by conceptualizing how the design of human-AI collaboration influences the development of three complementary and interdependent mental models necessary for this collaboration. We develop an integrated socio-technical framework that identifies the mechanisms driving the mental model evolution: data contextualization, reasoning transparency, and performance feedback. Our work advances human-AI collaboration literature through three key contributions: introducing three distinct mental models (domain, information processing, complementarity-awareness); recognizing the dynamic nature of mental models; and establishing mechanisms that guide the purposeful design of effective human-AI collaboration.
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