arXiv:2606. 19286v1 Announce Type: cross Abstract: When social chatbots make mistakes, and they do, how they recover determines whether users trust them again.
When social chatbots make mistakes, and they do, how they recover determines whether users trust them again. Social chatbots are increasingly integrated into everyday life, yet they remain prone to generating convincing but inaccurate information.
arXiv:2607. 24761v1 Announce Type: cross Abstract: Research on human-AI interaction has long framed verification of system outputs as a trust-contingent behavior that better-calibrated trust should reduce.
The study explores how children design AI chatbots and what they consider trustworthy. Using a custom chatbot-building environment, 115 learners aged 8‑18 created 119 chatbots and adjusted traits such as confidence, transparency, and formality. Findings show younger children equate trust with purpose‑fulfillment, while older children focus on transparent, calibrated design, and that students calibrate academic chatbots to be more formal and transparent than hobby ones.
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.
arXiv:2606. 21317v2 Announce Type: replace-cross Abstract: Recent work has raised concerns about the influence of sycophantic AI on user judgment and relationships.
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.
arXiv:2607. 25166v1 Announce Type: new Abstract: AI chatbots can be ``sycophantic,'' or overly agreeable and flattering toward users.
arXiv:2609.14638v1 Announce Type: cross Abstract: This paper is an encore submission of our 2026 journal article "Expertise and Information Seeking in the Age of Generative AI: New Procedures, New Pr...
arXiv:2607. 20001v1 Announce Type: cross Abstract: Artificial intelligence (AI) chatbots (e.
arXiv:2609.00250v1 Announce Type: cross Abstract: Many people now see AI systems as not just productivity tools but as social companions. Researchers are eager to study the consequences of AI compani...
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:2606. 05976v1 Announce Type: new Abstract: Recent work shows that LLM agents struggle to correct errors in their own reasoning traces yet show markedly higher correction rates when identical claims appear under external sources.