arXiv AI

Whale You Go Green? Immediate and Longitudinal Effects of Embodied Conversational AI Avatars on Sustainable Behavioral Tendencies and Pro-Environmental Attitudes

arXiv Computation and Language
Sep 21

Generative Artificial Intelligence Chatbots for Motivational Interviewing: A Scoping Review From System Design to Intervention Outcomes

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 AI
Sep 24

Listening and Mirroring: The Effects of Verbal Attunement and Behavioral Mimicry on Social and Empathic Perceptions of Embodied AI Agents in VR

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 AI
Aug 25

AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversations

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 AI
Sep 7

How a Chatbot's Response Style Shapes a Classroom: A Multi-Agent Simulation of Students Consulting AI

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
arXiv Computation and Language
Aug 31

Synthetic Linguistic Agency: How an Embodied Mortal Agent Learns Linguistic Affordances through Consequential Social Experience

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