arXiv:2606. 18265v1 Announce Type: cross Abstract: As human relationships with artificial intelligence systems become increasingly frequent and sustained, existing language and theory fail to accurately capture the nature of these affiliations.
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.
arXiv:2606. 19144v1 Announce Type: new Abstract: Current conversational AI systems have made significant progress in language generation, personalization, and long-context interaction.
arXiv:2607. 17826v1 Announce Type: cross Abstract: Despite the growing availability of customizable social artificial intelligence (AI), such as ChatGPT, Grok, and Character.
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.
arXiv:2606. 00807v2 Announce Type: replace Abstract: Traditional artificial intelligence has largely conceptualized intelligence as isolated computation occurring within bounded agents.
arXiv:2607. 25057v1 Announce Type: new Abstract: As conversational AI systems become increasingly integrated into daily life, their potential effects on user well-being require ongoing attention.
arXiv:2606. 12420v1 Announce Type: cross Abstract: Our concepts of survival and self-interest were built for single, continuous biological lives.
We’ve written a paper arguing that long-term AI safety research needs social scientists to ensure AI alignment algorithms succeed when actual humans are involved. Properly aligning advanced AI systems with human values requires resolving many uncertainties related to the psychology of human rationality, emotion, and biases.
arXiv:2606. 00807v1 Announce Type: new Abstract: Traditional artificial intelligence has largely conceptualized intelligence as isolated computation occurring within bounded agents.
arXiv:2607. 14240v1 Announce Type: new Abstract: Current alignment approaches typically focus on emulating human behavior using static representations of human preferences, failing to capture the dynamic, context-dependent nature of real-world human-AI interactions.
arXiv:2608. 10672v1 Announce Type: cross Abstract: Social interaction has become one of the most common uses of LLMs, yet research on emotional bonds with AI has focused largely on how users experience these systems, leaving the systems' role in relationship formation poorly understood.
arXiv:2608. 08443v1 Announce Type: cross Abstract: Previous studies have shown that people can develop shared symbols, partner-specific expressions, personal idioms, inside jokes, and other parts of a relational microculture.