Adnan KhanAdnanProduct & AI
San Francisco Bay Area
Get in touch

Source note2 min read

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

Source

arXiv

arxiv.org/abs/2608.05107v1

Read the source

Source

Plain-Language Brief

The paper introduces CoPlan, a new AI system designed to aid in care planning. CoPlan allows various stakeholders like clinicians, patients, and caregivers to collaborate on complex decisions by generating potential interventions along with supporting or challenging arguments. Human care planners can then inspect, challenge, revise, or add to these arguments before a final plan is generated. The system also supports adaptive team recruitment, role-based argument review, care plan generation, and practical follow-up.

What the Document Says

  • The paper presents CoPlan, an AI-supported human-AI interface for care planning.
  • CoPlan uses a multi-agent workflow where AI agents generate candidate interventions and arguments, while humans can accept, reject, modify, or add arguments.
  • The system combines co-intelligence (human and AI expertise) with contestability (open to inspection, revision, and justification).
  • CoPlan was demonstrated in an aging-in-place care planning scenario.
  • The system supports adaptive team recruitment, role-based argument review, final care plan generation, and practical follow-up through scheduling agents.

Key Concepts Mentioned

  • AI-supported care planning
  • CoPlan
  • multi-agent workflow
  • co-intelligence
  • contestability
  • adaptive team recruitment
  • role-based argument review
  • care plan generation
  • practical follow-up

Claims Made by the Document

  • AI-supported care planning can help coordinate complex decisions.
  • Fixed outputs from AI systems limit stakeholders' ability to inspect, challenge, and revise plans.

Evidence Used

  • The text states that AI-supported care planning can help in coordinating complex decisions. It also mentions that many AI systems present recommendations as fixed outputs.

Methods / Approach

UNKNOWN

Limitations Stated by the Authors

UNKNOWN

Limitations Noted by the Agent

Agent interpretation — not from the source.

UNKNOWN

Open Questions

UNKNOWN

Notes for Future Q&A

May include interpretation. Labeled where it does.

UNKNOWN

Raw Abstract / Excerpt

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.