arXiv:2608.05107cs.AIcs.MA2026-08中稿 · the 2026 Internati…

让医生和AI共同制定可争议的照护计划,支持多方协作与修改。

CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs

论文配图:CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs
图 1 · 摘自论文原文
  • AI与人类分工生成建议和论据,支持角色化评审。
  • 可动态调整计划,适应临床判断与患者实际需求。
  • 适合医疗团队协作场景,提升决策透明度与责任归属。

AI辅助照护规划可帮助临床医生、患者、照护者及团队协调复杂的临床、功能、心理社会与环境需求决策。然而,许多AI系统将建议呈现为固定输出,限制了各方在与临床判断、患者价值观或现实可行性冲突时进行审查、质疑和修订的能力。本文提出CoPlan——一种人机共智且可争议的照护规划界面。CoPlan采用多智能体工作流:专业AI代理生成候选干预措施及支持或反驳的论据,人类照护规划者可接受、拒绝、修改或添加论据后生成最终计划。该设计融合共智(人类与AI互补贡献)与可争议性(建议始终开放审查、修订与论证)。我们在居家养老照护场景中验证了CoPlan,系统支持自适应照护团队招募、基于角色的论据审查、最终计划生成及通过调度代理实现的后续跟进。本研究贡献了一个可争议的照护规划界面及其可信人机协作的设计范式,保障人类主导权与临床问责性。

原文摘要 · Abstract (English)

AI-supported care planning can help clinicians, patients, caregivers, and care teams coordinate complex decisions across clinical, functional, psychosocial, and environmental needs. However, many AI systems present recommendations as fixed outputs, limiting stakeholders' ability to inspect, challenge, and revise plans when they conflict with clinical judgment, patient values, or real-world feasibility. We present CoPlan - a Co-Intelligent and Contestable Interface for Human-AI Care Planning. CoPlan uses a multi-agent workflow in which specialized AI agents generate candidate interventions and supporting or challenging arguments, while human care planners can accept, reject, modify, or add arguments before final plan generation. Through this design, CoPlan combines co-intelligence, in which humans and AI agents contribute complementary expertise, with contestability, where recommendations remain open to inspection, revision, and justification. We demonstrate CoPlan in an aging-in-place care planning scenario. The system supports adaptive care team recruitment, role-based argument review, final care plan generation, and practical follow-up through scheduling agents. This work contributes a contestable care planning interface and a design framing for trustworthy human-AI care planning that preserves human agency and clinical accountability.

人机协作医疗AI可解释性照护规划

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