人际交往
心理学
认知科学
适应(眼睛)
人类智力
人际关系
关系理论
社会技术系统
社会关系
认识论
社会心理学
统计关系学习
进化心理学
人际互动
认知心理学
人格
情商
社会心理的
人际交往
桥(图论)
社会认知
社会关系
人工智能
人工心理学
心理学理论
关系(数据库)
计算机科学
作者
Ryan L. Boyd,David M. Markowitz
标识
DOI:10.1177/17456916251404394
摘要
As artificial intelligence (AI) becomes increasingly embedded in social life, understanding its interpersonal and psychological implications is urgent yet undertheorized. This article introduces the machine-integrated relational adaptation (MIRA) model, a transdisciplinary, middle-range theoretical framework that provides a foundational account of when, how, and why AI functions as a relational entity in human ecosystems. MIRA distinguishes two crucial roles of AI: relational partner (direct-interaction companion) and relational mediator (shaping human-to-human communication). Synthesizing psychosocial theories of human relationships, interpersonal communication theory, psycholinguistics, and human-computer interaction, MIRA structures AI's relational impact within antecedents, processes, moderators, and outcomes. Central to MIRA are four principles describing how AI fosters social adaptation: linguistic reciprocity, psychological proximity, interpersonal trust, and relational substitution versus enhancement. These principles illuminate how adaptive AI language and behavior can elicit emotional investment, simulate mutual understanding, or even supplant human interaction. MIRA integrates established theories-attachment theory, social exchange theory, and epistemic trust frameworks-and proposes a research agenda that bridges foundational psychology with emerging sociotechnical contexts. Rather than offering a deterministic view, MIRA provides a generative, testable structure for investigating the evolving role of AI in relational life and guiding future human-AI-connection research.
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