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cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why 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 Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Privacy-Preserving Behaviour of Chatbot Users: Steering T...
Julia Ive, Vishal Yadav, Mariia Ignashina, Matthew Rand, Paulina · 2024-11-27 · via cs.HC updates on arXiv.org

Introduction: The use of chatbots is becoming increasingly important across various aspects of daily life. However, the privacy concerns associated with these communications have not yet been thoroughly addressed. The aim of this study was to investigate user awareness of privacy risks in chatbot interactions, the privacy-preserving behaviours users practice, and how these behaviours relate to their awareness of privacy threats, even when no immediate threat is perceived. Methods: We developed a novel "privacy-safe" setup to analyse user behaviour under the guarantees of anonymization and non-sharing. We employed a mixed-methods approach, starting with the quantification of broader trends by coding responses, followed by conducting a qualitative content analysis to gain deeper insights. Results: Overall, there was a substantial lack of understanding among users about how chatbot providers handle data (27% of the participants) and the basics of privacy risks (76% of the participants). Older users, in particular, expressed fears that chatbot providers might sell their data. Moreover, even users with privacy knowledge do not consistently exhibit privacy-preserving behaviours when assured of transparent data processing by chatbots. Notably, under-protective behaviours were observed among more expert users. Discussion: These findings highlight the need for a strategic approach to enhance user education on privacy concepts to ensure informed decision when interacting with chatbot technology. This includes the development of tools to help users monitor and control the information they share with chatbots