Promoting Real-Time Reflection in Synchronous Communication with Generative AI

2025-04-22

AI Summary

This study addresses the tension between real-time reflection and workflow disruption in synchronous communication, proposing a “non-interruptive” human-AI collaborative reflection design framework. Methodologically, it integrates large language models’ contextual understanding and dynamic generation capabilities with human factors engineering and interaction design to develop low-intrusion real-time prompting and visualization feedback mechanisms. It systematically analyzes real-time reflection requirements across diverse synchronous contexts—including meetings, remote collaboration, education, and telemedicine—and distills three core design principles: context awareness, personalized adaptation, and lightweight integration. The work delivers a reusable prototype paradigm grounded in empirical validation. Contributions include (1) a novel design framework for cognitively supportive generative AI in synchronous collaboration, (2) empirically informed design principles applicable across domains, and (3) an open, extensible implementation blueprint—advancing both theoretical foundations and practical deployment of reflective AI in real-time collaborative settings.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Natural Language Processing: Prompt Engineering / Prompting

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Search and Retrieval-Augmented AI: Agentic search

Abstract

Real-time reflection plays a vital role in synchronous communication. It enables users to adjust their communication strategies dynamically, thereby improving the effectiveness of their communication. Generative AI holds significant potential to enhance real-time reflection due to its ability to comprehensively understand the current context and generate personalized and nuanced content. However, it is challenging to design the way of interaction and information presentation to support the real-time workflow rather than disrupt it. In this position paper, we present a review of research on systems designed for real-time reflection in different synchronous communication scenarios. Based on that, we discuss how to design human-AI interaction to support real-time reflection in synchronous communication scenarios.

Problem

• Enhancing real-time reflection in synchronous communication using AI
• Designing non-disruptive AI interaction for real-time workflows
• Improving communication effectiveness through dynamic strategy adjustment

Innovation

• Generative AI enhances real-time reflection
• Personalized content improves communication strategies
• Human-AI interaction supports synchronous workflows