arXiv:2609.15696v1 Announce Type: cross
Abstract: Generative AI (GenAI) tools are increasingly woven into how blind and low-vision (BLV) people communicate, not only with digital information, but wit...
By Protik Dey, Mohd Saifuzzaman, Taslima Akter
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
arXiv:2608. 10773v1 Announce Type: cross Abstract: The increasing use of Generative Artificial Intelligence (GenAI) in journalism raises concerns about possible detrimental effects both on journalism and its democratic function.
By Mari Reisj{\aa}, Anders Sundnes L{\o}vlie
The increasing use of Generative Artificial Intelligence (GenAI) in journalism raises concerns about possible detrimental effects both on journalism and its democratic function. We explore these risks through a case study of GenAI in Norwegian Newsrooms during the 2025 parliamentary election campaign.
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. But the effects of such disclosures remain uncertain.
The paper investigates whether large language model (LLM) chatbots can emulate human legal judgments of reasonableness. By comparing responses from 26 LLMs to those of human participants across 25 legal scenarios, the study finds that chatbots generally track human answers but tend to produce more homogeneous, government‑ and corporation‑friendly responses and align more closely with white, male, older, and more educated respondents. The authors note that these patterns warrant further systematic research.
By Nirav Patel, Emily Wenger, Christopher Buccafusco
arXiv:2606. 01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among the general public.
By Meredith Ringel Morris
arXiv:2608.22266v1 Announce Type: new
Abstract: In the context of information seeking, conversational agents are undergoing an evolution from reactive tools to proactive, personalized assistants. A c...
By Zhihong Cao, Chen Huang
arXiv:2606. 18256v1 Announce Type: cross Abstract: LLM-based chatbots are increasingly applied in interpersonal domains such as counseling and peer support, where establishing human-AI rapport is crucial yet remains challenging.
By Yoonseok Oh, Inseo Jung, Jinkyu Kim, Jungbeom Lee, Minwoo Kang, Suhong Moon
arXiv:2509.24877v3 Announce Type: replace
Abstract: The social science of large language models (LLMs) examines how these systems evoke mind attributions, interact with one another, and transform hum...
By Xiao Jia, Zhanzhan Zhao
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
The paper explores how generative AI can lower the barrier to personalizing health dashboards by enabling users to co-design interfaces in Figma Make. In a study with 14 participants, redesigns of Google and Apple Health focused on personal context, future planning, and interactive experiences, though conversational AI designs tended toward chat-window conventions. AI facilitated the materialization of loosely articulated ideas, yet model defaults and generation latency influenced iteration, and the process highlighted interpretability and accountability over privacy, trust, and emotional safety.
By Karthik S. Bhat, Vidhi Shah, Vedika Agnihotri, Dong Whi Yoo, Koustuv Saha