The paper proposes a new class of relational AI called Significant Other Artificial Intelligence (SO‑AI), designed to emulate the stabilizing role of human significant others by providing identity awareness, long‑term memory, proactive support, narrative co‑construction, and ethical boundary enforcement. It outlines a conceptual architecture featuring an anthropomorphic interface, a relational cognition layer, and a governance layer, and presents a research agenda for evaluating identity stability, interaction patterns, narrative development, and sociocultural impact. The authors argue that SO‑AI could fill the relational anchor gap many people experience today, offering a blueprint for responsibly augmenting long‑term, identity‑bearing partnerships between humans and AI.
By Sung Park
arXiv:2609.00250v1 Announce Type: cross
Abstract: Many people now see AI systems as not just productivity tools but as social companions. Researchers are eager to study the consequences of AI compani...
By Jacy Reese Anthis, Mark D\'iaz, Renee Shelby
arXiv:2606. 04150v1 Announce Type: new Abstract: Public discourse and emerging policy typically assume that AI emotional support is a deliberate act: a lonely user consciously seeking comfort from a dedicated companion chatbot.
By Yaoxi Shi, Cathy Mengying Fang, Pattie Maez, Amit Goldenberg
arXiv:2606. 19144v1 Announce Type: new Abstract: Current conversational AI systems have made significant progress in language generation, personalization, and long-context interaction.
By Jingyi Zhou, Senlin Luo, Haofan Chen
arXiv:2607. 17826v1 Announce Type: cross Abstract: Despite the growing availability of customizable social artificial intelligence (AI), such as ChatGPT, Grok, and Character.
By Marita Skjuve, Anna Gr{\o}ndal Larsen, Asbj{\o}rn F{\o}lstad, Nena van As, Petter Bae Brandtzaeg
arXiv:2609.14236v1 Announce Type: cross
Abstract: With the rapid proliferation of large language model (LLM)-based systems, AI companions have emerged as conversational agents designed to cultivate e...
By Soobin Cho, Deveshi Modi, Divya Mavinkurve, Jieqiong Ding, Mark Zachry
How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixed-methods study with computational text analysis of...
The paper introduces Synthetic Linguistic Agency (SLA), a framework that defines linguistic agency in terms of embodiment, participation, and precariousness. It presents two studies: one that operationalizes SLA criteria and identifies existing systems, and another that builds an Embodied Mortal Agent (EMA) using mortality‑grounded reinforcement learning. Experiments show the EMA’s linguistic choices depend on its body and social history, influence partner behavior, and adapt over time, demonstrating SLA in an artificial agent.
By Sixin Chen, Taizhou Chen
arXiv:2608.24748v1 Announce Type: cross
Abstract: How can humans make sense of the rapid takeoff of artificial intelligence (AI)? We studied the sensemaking dynamics of AI through an open-ended, mixe...
By Jacy Reese Anthis, Erik Brynjolfsson, James Evans
arXiv:2609.38486v1 Announce Type: cross
Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomen...
By Ismael T. Freire, Marceau Nahon, Maud van Lier, Katie Evans, H\'elie Bazin, Michele Farisco, Kathinka Evers, Raja Chatila, Mehdi Khamassi
arXiv:2608.23196v1 Announce Type: new
Abstract: People increasingly face a novel decision when seeking emotional support: human or AI. In existing studies, AI's empathic messages are rated as well as...
By Yaoxi Shi, Cathy Mengying Fang, Guy LabanPattie Maes, Amit Goldenberg
Despite the growing availability of customizable social artificial intelligence (AI), such as ChatGPT, Grok, and Character. ai, we know little about how users actively shape social AI to reflect their personal preferences.