arXiv:2606. 10861v1 Announce Type: cross Abstract: LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use.
By Nitish Patkar, Pooja Rani, Jack Gl\"asser, Simon L\"uscher, Martin Kropp
arXiv:2602.17850v2 Announce Type: replace-cross
Abstract: Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and...
By Erik Derner, Dalibor Ku\v{c}era, Aditya Gulati, Ayoub Bagheri, Nuria Oliver
arXiv:2604. 03881v2 Announce Type: replace-cross Abstract: Encouraging pro-environmental behavior remains a major challenge for sustainable cities.
By Zonghan Li, Yi Liu, Chunyan Wang, Song Tong, Kaiping Peng, Feng Ji
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.
By Jina Suh, Mihaela Vorvoreanu, Forough Poursabzi-Sangdeh, Emily Tseng, Eugenia Kim, Luke Nicholls, James W. Pennebaker, Eric Horvitz
This scoping review examined 48 studies on generative AI chatbots designed to deliver motivational interviewing (MI). It found that most systems were text‑based and disembodied, with about half incorporating dynamic adaptation, and that safety reporting was inconsistent. While user perceptions were generally positive and many studies reported MI‑consistent interactions, evidence for sustained behavioral or functional change remains limited.
By Runze Hu, Jingqi Kong, Yang Yang, Yihang Yang, Jingyao Liu, Haizhou Tang, Shanghang Zhang, Zheng Liu
arXiv:2607. 25166v1 Announce Type: new Abstract: AI chatbots can be ``sycophantic,'' or overly agreeable and flattering toward users.
By Meryl Ye, Robert Kraut, Steve Rathje
arXiv:2607. 09253v1 Announce Type: cross Abstract: AI chatbots are increasingly used for answering health-related questions.
By Gwenn Beets, Anniek Jansen, Saar Hommes, Ruben D. Vromans, Leonie Westerbeek, Supraja Sankaran, Julia C. M. van Weert, Emiel J. Krahmer, Nadine Bol
The study investigates how verbal attunement and real‑time behavioral mimicry affect users’ perceptions of an embodied AI counselor in virtual reality. Participants interacted with a system that varied in verbal attunement (attuned vs. neutral) and behavioral mimicry (present vs. absent). Results indicated that verbal attunement most reliably increased perceived empathy, while mimicry had a marginal effect on perceived humanness and showed exploratory positive associations with empathy, positivity, and humanness, especially among female participants.
By Nathalia Gomez, Haig Shamlian, Omar Khan, Tiffany D. Do
arXiv:2608.21841v1 Announce Type: new
Abstract: Conversational AI increasingly shapes consequential decisions, yet users have limited support for recognizing and resisting manipulation. We present AI...
By Rachel Poonsiriwong (Pub), Chayapatr (Pub), Archiwaranguprok, Constanze Albrecht, Monchai Lertsutthiwong, Pattie Maes, Pat Pataranutaporn
arXiv:2608. 11794v1 Announce Type: cross Abstract: The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement.
By Adrian Rauchfleisch, Andreas Jungherr
The study simulates a virtual classroom of 20 student agents who consult either a friend or a counselor AI when stressed. Five state variables (stress, happiness, self‑reliance, AI dependence, sociability) are tracked over daily phases, and the counselor AI is tested with six response styles (affirming, listening, solution‑oriented, reality‑redirecting, inciting, blaming). Results show that a solution‑oriented style lowers AI dependence and boosts self‑reliance, while affirming and inciting styles increase AI dependence, with inciting also raising stress and absenteeism; the listening style does not alleviate stress.
By Rin Tamai, Yuya Dan
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