Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)

2025-07-22

AI Summary

This study investigates social acceptance of Web-based XR agent systems among journalists, targeting remote digital training in high-risk scenarios. We extend the Almere model by incorporating credibility and security dimensions, and empirically evaluate user acceptance mechanisms through mixed-methods—quantitative surveys and qualitative interviews—conducted in authentic journalistic workflows. The system is implemented as a modular, hardware-agnostic toolkit enabling avatar-mediated interaction and cross-platform remote access via WebXR. Results indicate strong perceived usability and usefulness, yet reveal notable gaps in trust regarding agent autonomy and data security. Key contributions include: (1) the first adaptation of a social acceptance model to XR agent applications in journalism; (2) a lightweight, deployable WebXR agent prototype; and (3) identification of critical design factors shaping professional trust—providing both theoretical insights and practical guidelines for XR-mediated human–agent collaboration in high-stakes domains.

Technology Category

• Multiagent Systems: Agent Communication
• Application Domains: Humanities & Computational Social Science
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

In this paper, we present the findings of a user study that evaluated the social acceptance of eXtended Reality (XR) agent technology, focusing on a remotely accessible, web-based XR training system developed for journalists. This system involves user interaction with a virtual avatar, enabled by a modular toolkit. The interactions are designed to provide tailored training for journalists in digital-remote settings, especially for sensitive or dangerous scenarios, without requiring specialized end-user equipment like headsets. Our research adapts and extends the Almere model, representing social acceptance through existing attributes such as perceived ease of use and perceived usefulness, along with added ones like dependability and security in the user-agent interaction. The XR agent was tested through a controlled experiment in a real-world setting, with data collected on users' perceptions. Our findings, based on quantitative and qualitative measurements involving questionnaires, contribute to the understanding of user perceptions and acceptance of XR agent solutions within a specific social context, while also identifying areas for the improvement of XR systems.

Problem

• Evaluating social acceptance of XR agent technology
• Assessing user interaction with virtual avatars in training
• Extending Almere model for XR system dependability and security

Innovation

• Web-based XR training system for journalists
• Modular toolkit enabling virtual avatar interaction
• Extended Almere model measuring social acceptance