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Knowing When to Ask: Self-Gated Clarification for Hierarchical Language Agents Collaborative Human-Agent Protocol (CHAP) UXBench: Benchmarking User Experience in AI Assistants Impedance MPC for Physical Human-Robot Interaction: Predictive Disturbance Rejection with Joint-Limit Safety Formalizing all indexed mathematics as a benchmark for general reasoning, with the example of implementing dilatations of categories Face versus Body Tracking for Human-Robot Interaction: An Egocentric Dataset What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build Learning to Decide with AI Assistance under Human-Alignment Positive Alignment: Artificial Intelligence for Human Flourishing Sycophantic AI makes human interaction feel more effortful and less satisfying over time Exploring Interaction Paradigms for LLM Agents in Scientific Visualization The Alignment Target Problem: Divergent Moral Judgments of Humans, AI Systems, and Their Designers Participatory provenance as representational auditing for AI-mediated public consultation Aligning Human-AI-Interaction Trust for Mental Health Support: Survey and Position for Multi-Stakeholders Semantic Prompting: Agentic Incremental Narrative Refinement through Spatial Semantic Interaction Multimodal Ambivalence/Hesitancy Recognition in Videos for Personalized Digital Health Interventions The Augmentation Trap: AI Productivity and the Cost of Cognitive Offloading Can LLMs Reason About Attention? 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Context Aware Family Dynamics based Internet of Things Access Control Towards Better Child Safety
Yasar Majib, Charith Perera · 2019-11-06 · via cs.HC updates on arXiv.org

Today, children are increasingly connected to the Internet and consume content and services through various means. It has been a challenge for less tech-savvy parents to protect children from harmful content and services. Internet of Things (IoT) has made the situation much worse as IoT devices allow children to connect to the Internet in novel ways (e.g., connected refrigerators, TVs, and so on). In this paper, we propose mySafeHome, an approach which utilises family dynamics to provide a more natural, and intuitive access control mechanism to protect children from harmful content and services in the context of IoT. In mySafeHome, access control dynamically adapts based on the physical distance between family members. For example, a particular type of content can only be consumed, through TV, by children if the parents are in the same room (or hearing distance). mySafeHome allows parents to assess a given content by themselves. Our approach also aims to create granular levels of access control (e.g., block / limit certain content, features, services, on certain devices when the parents are not in the vicinity). We developed a prototype using OpenHAB and several smart home devices to demonstrate the proposed approach. We believe that our approach also facilitates the creation of better relationships between family members. A demo can be viewed here: http://safehome.technology/demo.