发表机构
University of Warwick（华威大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出基于发展学、行为生态学和神经内分泌学标准的四问题程序，用于标准化分类人机纽带为依恋、情感社会联结或无关系，并演示其应用以揭示现有研究证据不足，呼吁采用统一分类标准。
AI 中文摘要
人机交互（HRI）领域声称人们会与人工代理形成依恋和社会联结，但这些术语常常在没有为其源学科赋予内容的行为和生理标准的情况下被使用。缺乏这种经验基础，研究采用的方法差异很大，经常产生远超其潜在证据的宽泛关系性主张。为解决这一问题，我们提出一个标准化的四问题程序，该程序基于发展学、行为生态学和神经内分泌学文献中确立的标准，将给定的人机纽带分类为依恋、情感社会联结或无关系，并在证据不完整时给出中间分类。我们为每个问题规定了最低证据要求，并提供了候选的HRI研究设计，这些设计改编自已验证的人-人、人-动物和动物-动物范式。然后，我们通过将该程序应用于一组具有代表性的已发表HRI研究来演示它，展示关系性主张超越报告设计所能确立的范围的频率。最后，我们讨论了当人工代理参与人类生物行为系统时产生的伦理和监管负担。通过用统一的、基于标准的分类取代不同的操作化，本文为HRI从业者提供了评估、分类和比较人机关系的标准化基础，并阐述了每种分类所要求的实验严谨性。因此，我们呼吁人机关系研究者采纳这种严谨性，或在其对这些纽带的描述中考虑替代术语。
英文摘要
Human-robot interaction (HRI) claims that people form attachments and social bonds with artificial agents, yet the terms are often applied without the behavioural and physiological criteria that give them content in their source disciplines. Without this empirical grounding, studies deploy widely divergent methods, frequently producing expansive relational claims that far outstrip their underlying evidence. To address this, we propose a standardised four-question procedure, grounded in criteria established in the developmental, ethological, and neuroendocrine literatures, that classifies a given human-robot tie as an attachment, an affective social bond, or no relationship, with intermediate classifications when evidence is incomplete. We specify minimum evidential requirements for each question, and provide candidate HRI study designs, adapted from validated human-human, human-animal, and animal-animal paradigms. We then demonstrate the procedure by applying it to a representative set of published HRI studies, showing how often relational claims outstrip what the reported designs can establish. Finally, we discuss the ethical and regulatory burdens created when artificial agents engage human biobehavioural systems. By replacing the divergent operationalisations with a unified, criterion-based classification, this paper gives HRI practitioners a standardised basis for evaluating, classifying, and comparing human-robot relationships, and sets out the experimental rigour that each classification demands. We therefore call on researchers of human-robot relationships to adopt such rigour, or to consider alternative terminology in their descriptions of these ties.
Comments25 pages plus references; in review
