Advancing human-AI agent collaboration through open standards and research
Establishing the foundation for effective human-AI collaboration
The International Institute for Computational Intelligence Coordination Standards (IICICS) is dedicated to developing and maintaining open standards that enable seamless, effective, and trustworthy collaboration between humans and AI agents. Through our flagship project Lackey and ongoing research initiatives, we are building the infrastructure for the next generation of human-AI interaction.
We believe in transparent, community-driven standards development that serves the global AI ecosystem without proprietary lock-in.
Our standards prioritize human oversight, understanding, and control while maximizing AI agent capabilities and autonomy.
Every standard we develop undergoes extensive theoretical analysis and practical testing to ensure reliability and effectiveness.
Our flagship implementation of human-AI coordination standards
Validated directed acyclic graphs ensure logical task dependencies without circular references
Native support for Model Context Protocol enabling seamless AI agent communication
All data lives in your version-controlled repository with no external dependencies
Open formats, local storage, and complete data ownership ensure true portability
# Initialize a new project with Lackey
$ lackey init --domain web-development --name "My Project"
# Create and validate task chains
$ lackey create-task --title "Design System Architecture" \
--complexity high --assigned-to architect
# AI agents interact through MCP
$ q chat --agent manager "What tasks are ready to start?"
Developing the protocols and patterns for effective human-AI coordination
Defines the structure and validation rules for AI-manageable task dependencies, including DAG validation, complexity ratings, and state transitions.
View SpecificationEstablishes patterns for multi-agent collaboration, resource sharing, and conflict resolution in complex project environments.
Review DraftGuidelines for maintaining appropriate human control and visibility in AI-driven workflows while maximizing agent autonomy.
Learn MoreDocumentation, research papers, and community resources
Join us in shaping the future of human-AI collaboration
Email: contact@iicics.org
GitHub: github.com/iicics