How transparency impacts trust in teleoperated autonomous robots under uncertainty
Publication date: October–November 2026 Source: International Journal of Human-Computer Studies, Volume 215 Author(s): Min Cai, Kuangyong Gao, Ziling Ji, Xueqi Xu
Record details
Published: 14 July 2026
Source: International Journal of Human-Computer Studies
Category: Research
Topics: Agents & autonomy · Transparency
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Paradoxes of meaningful work in human-robot automotive production lines: Flow versus repair, recognition versus audit, safety versus work precarity in Sweden and Türkiye
Technology in Society · 14 July 2026
MAIS: Exploring human-AI interaction in fair and transparent recruitment with a multi-agent LLM-based system
International Journal of Human-Computer Studies · 14 July 2026
Do AI Agents Know When a Task Is Simple? Toward Complexity-Aware Reasoning and Execution
arXiv cs.AI · 14 July 2026
Automated Textbook Auditing with Multi-Agent LLM Systems
arXiv cs.CY · 14 July 2026
Explaining Reinforcement Learning Agents via Inductive Logic Programming
arXiv · 15 July 2026
An Explainable Agentic System for Detection of Conversational Scams with Summary-Based Memory
arXiv cs.HC · 13 July 2026
How to cite this record
ethics.ai (14 July 2026), “How transparency impacts trust in teleoperated autonomous robots under uncertainty,” evidence record 2065, https://ethics.ai/record/2065 (originally published by International Journal of Human-Computer Studies).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.