Designing Transparent AI-Mediated Language Support for Intergenerational Family Communication

2026-04-21

AI Summary

This study addresses how intergenerational language differences impede effective communication and emotional intimacy within families. It proposes GenSync, a chat interface that treats AI translation as an interpretive mediator, and systematically evaluates three translation visibility modes—no translation, black-box translation, and transparent translation—on intergenerational dialogue. Transparent translation, which juxtaposes original and translated utterances, significantly enhances conversation quality, perceived intimacy, and system usability, whereas black-box translation often disrupts conversational flow. This work provides the first empirical evidence of the critical role translation visibility plays in sensitive social interactions and offers a new design paradigm for AI-mediated communication systems.

Technology Category

• Humans and AI: Intelligent User Interfaces
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Multiagent Systems: Agent Communication

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Intergenerational linguistic differences pose challenges to effective and intimate family communication. This paper presents GenSync, a chat-based interface that supports intergenerational understanding through different forms of translation visibility. We conducted a controlled within-subjects study with 16 family dyads (32 participants), comparing three conditions: no translation, black-box translation, and transparent translation that displays both original and interpreted messages. The results show that translation visibility plays a critical role in shaping conversational experiences. Transparent translation supported conversational quality, intimacy, and usability, while black-box translation often disrupted conversational flow. These findings position intergenerational language support as a form of interpretive mediation and contribute design implications for AI-mediated communication in socially sensitive contexts.

Problem

• intergenerational communication
• language support
• AI-mediated communication
• translation visibility
• family communication

Innovation

• transparent translation
• AI-mediated communication
• intergenerational communication
• interpretive mediation
• translation visibility