Private Etymology: A Design Model for Shared Symbols in Human-AI Interaction
A recent concept-and-prototype paper presents 'Private Etymology,' a machine-representable relational provenance that captures the evolution of dyad-specific symbolic expressions over time in long-term interactions between humans and AI. Available on arXiv (2608.08443), it introduces 'relational reuse' as a technique to reactivate specific expressions in future sessions without needing to re-explain their meanings. Prior research has indicated that individuals create shared symbols, partner-specific phrases, personal idioms, and inside jokes, leading to relational microcultures. Although recent studies have explored how humans and conversational AI negotiate symbolic meanings, existing long-term systems lack a comprehensive design model for documenting the meaning-making process. This paper proposes a model to track the lifecycle of shared symbols, aiming to enhance the depth and continuity of human-AI relationships.
Key facts
- Paper title: 'Private Etymology: Designing Relational Reuse of Shared Symbols in Long-Term Human-AI Interaction'
- arXiv ID: 2608.08443
- Announce type: replace-cross
- Introduces 'Private Etymology' as a relational provenance model
- Proposes 'relational reuse' for reactivating dyad-specific expressions
- Addresses lack of design model for recording meaning and acceptance in long-term human-AI systems
- Builds on prior work on shared symbols and relational microcultures
- Paper is a concept-and-prototype paper
Entities
Institutions
- arXiv