Abstract
This paper presents a framework that facilitates human-AI collaboration more effectively. The framework allows multi-users and Artificial Intelligence (AI) to collaborate in the virtual reality (VR) space. The case study presented in this paper integrates machine learning (ML) and multi-user VR technology to enhance human-ML collaboration for breast cancer diagnosis using digital pathology. ML, particularly convolutional neural networks (CNNs), has played a crucial role in breast cancer detection in recent years by automating the identification of cancerous regions in Whole Slide Images (WSIs). These results can then be visualised within a VR environment, providing pathologists with an immersive and interactive platform that supports real-time collaboration between human experts and ML. The integration of ML and VR can improve diagnostic accuracy and foster collaborative decision-making among senior and junior pathologists, potentially leading to better patient outcomes.