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<p>As large language models (LLMs) enable increasingly fluent interaction, artificial intelligence (AI) systems are becoming embedded in everyday social contexts. This paper offers a conceptual synthesis explaining why humans come to perceive AI as a social Other. Rather than attributing this perception to intrinsic sentience or moral status, it argues that it arises from evolved cognitive mechanisms, including agency detection, theory of mind, and sensitivity to relational continuity, that structure human social cognition. Drawing on philosophy, psychology, and computational research, the paper examines how contemporary AI systems activate these mechanisms and how prevailing design choices may reshape empathy, trust, and social coordination. It argues that emerging social risks associated with AI stem not from intelligence itself, but from relational architectures that position AI as an exclusive or personalized social interlocutor, thereby displacing human–human interaction. In response, the paper introduces the concept of <i>interconnected AI</i> as a structural orientation toward relational architecture rather than a prescriptive system or governance model. Interconnected AI situates artificial systems within multi-user relational networks, supporting shared context and coordination while preserving human responsibility and moral authorship. By reframing AI as a participant embedded within human relational life, this perspective provides a foundation for designing relationally sustainable AI grounded in the realities of human social cognition.</p>

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From isolated to interconnected: an evolutionary psychological account of artificial othering and a design paradigm to preserve human social cohesion

  • 期刊论文

  • 发表日期：

    2026年3月2日

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  • Sehyun Ryu

摘要

As large language models (LLMs) enable increasingly fluent interaction, artificial intelligence (AI) systems are becoming embedded in everyday social contexts. This paper offers a conceptual synthesis explaining why humans come to perceive AI as a social Other. Rather than attributing this perception to intrinsic sentience or moral status, it argues that it arises from evolved cognitive mechanisms, including agency detection, theory of mind, and sensitivity to relational continuity, that structure human social cognition. Drawing on philosophy, psychology, and computational research, the paper examines how contemporary AI systems activate these mechanisms and how prevailing design choices may reshape empathy, trust, and social coordination. It argues that emerging social risks associated with AI stem not from intelligence itself, but from relational architectures that position AI as an exclusive or personalized social interlocutor, thereby displacing human–human interaction. In response, the paper introduces the concept of interconnected AI as a structural orientation toward relational architecture rather than a prescriptive system or governance model. Interconnected AI situates artificial systems within multi-user relational networks, supporting shared context and coordination while preserving human responsibility and moral authorship. By reframing AI as a participant embedded within human relational life, this perspective provides a foundation for designing relationally sustainable AI grounded in the realities of human social cognition.