厘清机器伴侣的定义与测量方法，为人工智能社交性研究提供框架。
Conceptualization, Operationalization, and Measurement of Machine Companionship: A Scoping Review
- 基于71篇文献提出机器伴侣的正式定义和核心特征。
- 发现50多种不同测量变量，反映概念多样性与不一致性。
- 适合人机交互、情感计算等领域研究者参考。
机器伴侣的概念长期存在于社会技术想象中。近年来人工智能的发展使这些构想在界面、机器人身体和设备中成为可感知的社交体验。尽管这些机器常被通俗称为'伴侣'，但学界对机器伴侣（MC）作为正式概念或可测量变量的关注仍寥寥无几。本研究遵循PRISMA指南，系统性地筛选、调查并综合2017至2025年间关于机器伴侣的71项学术成果。研究发现，现有工作在理论基础、预设属性维度（主观积极、持续性、共动性、自指性）以及测量概念上差异显著，共识别出超过50种不同的测量变量。本文最终基于文献提出：机器伴侣是一种主观积极、随时间持续、双向协调的主客体关系，且具备自指性。
原文摘要 · Abstract (English)
The notion of machine companions has long been embedded in social-technological imaginaries. Recent advances in AI have moved those media musings into believable sociality manifested in interfaces, robotic bodies, and devices. Those machines are often referred to colloquially as "companions" yet there is little careful engagement of machine companionship (MC) as a formal concept or measured variable. This PRISMA-guided scoping review systematically samples, surveys, and synthesizes current scholarly works on MC (N = 71; 2017-2025), to that end. Works varied widely in considerations of MC according to guiding theories, dimensions of a-priori specified properties (subjectively positive, sustained over time, co-active, autotelic), and in measured concepts (with more than 50 distinct measured variables). WE ultimately offer a literature-guided definition of MC as an autotelic, coordinated connection between human and machine that unfolds over time and is subjectively positive.
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