About CAIS

Learn more about the Causal AI Scientist project, including how to cite it in your research, track version changes, and understand licensing terms.

Project Information

• Citation Information
  • BibTeX Format
  • License and Usage Terms
  • Contact for Citation Questions
• Changelog
  • Version 0.1.2 (Current)
  • Version 0.1.1
  • Version 0.1.0
  • Contributing to Changelog
  • Release Process
  • Contact for Release Information
• License and Usage Terms
  • MIT License
  • What This Means
  • Usage Guidelines
  • Third-Party Dependencies
  • Data and Model Licenses
  • Contributing and License
  • License Compliance
  • Frequently Asked Questions
  • Contact for License Questions
  • License History

Project Overview

The Causal AI Scientist (CAIS) is an open-source project designed to democratize causal inference by making advanced statistical methods accessible to researchers and practitioners across various domains.

Mission

To provide an intelligent, automated system that helps users conduct rigorous causal inference analysis regardless of their statistical background.

Vision

A world where causal questions can be answered reliably and efficiently, enabling better decision-making in research, policy, and business.

Core Principles

• Accessibility: Make causal inference approachable for non-experts

• Rigor: Maintain high standards for statistical validity

• Transparency: Provide clear explanations of methods and assumptions

• Reproducibility: Enable reproducible research practices

• Community: Foster an open, collaborative development environment