When Single-User-Oriented LLM-based Assistants Involve Others: A Scoping Review of Pathways, Risks, and Responses

2026-09-12

AI Summary

研究通过回顾58项研究，探讨了单用户导向的LLM助手在涉及多参与者时的路径、风险及应对措施，提出了关注角色关系变化的治理和设计建议。

Abstract

LLM-based assistants are increasingly extending into multi-party contexts, while core operational processes for context management, personalization, identity attribution, authority attribution, and action execution often remain organized around a single user. Existing work examines particular multi-party settings, but lacks a systematic account of how these single-user-oriented assistants begin to involve additional human parties and what risks emerge. To address this gap, we conducted a scoping review of 58 studies. We identify five operational pathways spanning direct and indirect involvement, five recurring risk domains, and five areas of implemented and proposed responses. Based on these findings, we argue for governance that attends to changing cross-person roles and relationships in practice, and for assistant designs that preserve person-specific boundaries throughout interaction.

Problem

• LLM-based assistants
• multi-party contexts
• context management
• risks

Innovation

• multi-party contexts
• context management
• governance
• personal boundaries
• risk domains