arXiv AI
Assessing the Applicability of Existing Design Recommendations to AI Companion Design: A Multi-Method Study
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arXiv AI
Jul 23
A Framework of User Experience Principles for Human-AI Agent Interaction in the Workplace
arXiv:2607. 19941v1 Announce Type: cross Abstract: As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and successful adoption.
arXiv AI
Aug 24
Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI
arXiv:2411.08881v3 Announce Type: replace-cross Abstract: AI-based systems, including Large Language Models (LLMs), impact millions by supporting diverse tasks but face issues like misinformation, bi...
arXiv AI
Jul 3
Copewell: A Multi-Agent Swarm Architecture for Equitable Mental Wellness Support
arXiv:2607. 02245v1 Announce Type: new Abstract: Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due to workforce shortages, cost barriers, and stigma.
arXiv AI
Jul 10
Psychological Competence as a Missing Dimension in AI Evaluation
arXiv:2607. 08285v1 Announce Type: new Abstract: Current AI evaluation frameworks focus primarily on technical performance, including accuracy, robustness, reasoning ability, and policy compliance.
arXiv AI
Jun 4
Stumbling Into AI Emotional Dependence: How Routine AI Interactions Reshape Human Connection
arXiv:2606. 04150v1 Announce Type: new Abstract: Public discourse and emerging policy typically assume that AI emotional support is a deliberate act: a lonely user consciously seeking comfort from a dedicated companion chatbot.
arXiv AI
Sep 15
Personalizing Personal Health Interfaces: Co-Design with Generative AI
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.