The paper argues that deploying generative AI agents requires more than isolated task success; they must remain useful across repeated interactions, changing conditions, and dependencies on people within shared workflows. The authors introduce two complementary evaluation aspects—operational resilience and considerate participation—to assess how agents recover from blocked work, communicate limits, and adapt to affected people and role boundaries. Using 120 simulated healthcare trajectories across two AI models and twelve stakeholder-derived tasks under varying challenge levels, the study finds that agents shift toward greater human dependence and increased workload as challenge accumulates, while also broadening from task-focused adaptation to task reframing and wider coordination.
By Yuanchen Bai, Zijian Ding, Angelique Taylor
arXiv:2607. 26853v1 Announce Type: cross Abstract: Human personality theories characterize traits not as isolated attributes captured by a single score, but as stable individual tendencies expressed through the interplay among persons, situations, and behaviors.
By Ruikang Zhang, Shuo Wang, Qi Su
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
The paper compares human group discussions with large language model (LLM) deliberation traces on various reasoning tasks, finding that both humans and LLMs exhibit an assembly bonus asymmetry where discussion benefits the average member more than the best initial member. While LLM groups mirror some outcome-level patterns of human deliberation, they differ in process-level behaviors: they tend to follow majorities, surface less unique information, and converge earlier. Interventions inspired by human group‑decision research yield modest outcome improvements but do not eliminate coordination bottlenecks.
By Ala N. Tak, Teruhisa Misu, Kumar Akash, Zhaobo K. Zheng, Kevin H. Joo, Jonathan Gratch
The paper examines how conversational AI, specifically ChatGPT, displays aspects of cooperative dialogue such as morality, politeness, and alignment compared to human-human conversations. Using over 26,000 multi‑turn dialogues and mixed‑effects modeling, the authors find that AI mimics the surface features of cooperation—like warmth and hedging—yet lacks the underlying social architecture that drives mutual adaptation. Key findings include a dissociation between AI’s moral output and human negotiation, a decline in linguistic convergence, and a reversal of typical human accommodation mechanisms when interacting with AI.
By Marina Mitiaeva, Lu Xiao
arXiv:2608. 04016v1 Announce Type: cross Abstract: Social disadvantage is associated with multimorbidity, but the pathways linking social conditions to disease burden remain poorly understood.
By Cong Cao, Shuangge Ma
arXiv:2608. 13046v1 Announce Type: new Abstract: Organizational decisions are co-created while evidence, constraints, and human priorities continue to evolve.
By Sanjeev Manivannan
In long, multi-turn dialogue a large language model maintains an implicit relational stance toward the user, spanning from "push the user toward real-world others" to "position itself as the user's sole support. " When it slides toward the latter, "support" degrades into "you only have me" -- a harm documented in real companion conversations (Moore et al.
arXiv:2606.08081v2 Announce Type: replace-cross
Abstract: Repeated reference games test whether interlocutors replace their initially long descriptions with shorter, partner-specific expressions grou...
By Po-Ya Angela Wang, Chinmaya Mishra, Asl{\i} \"Ozy\"urek, Paula Rubio-Fern\'andez, Esam Ghaleb
arXiv:2603.27611v2 Announce Type: replace
Abstract: When a cognitive system modifies its own functioning, what exactly does it modify: a low-level rule, a control rule, or the criterion that evaluate...
By Florentin Koch
arXiv:2606. 16944v1 Announce Type: new Abstract: Theory of mind (ToM), the capacity to ascribe mental states to others and use those ascriptions for prediction and inference, is widely assumed to be essential for effective human-machine integration.
By Nikolos Gurney
arXiv:2607. 27179v1 Announce Type: cross Abstract: Conversational AI is increasingly positioned as a teammate rather than a tool, yet we know little about how its presence reshapes communication among the humans on the team.
By Nia Nixon, Jaeyoon Choi, Pedro Martins De Bastos, Mohammad Amin Samadi, Luise Mehner, Seehee Park, Spencer JaQuay