Research White Papers
In-depth technical reports on AI governance, autonomous systems, and safety frameworks. Download comprehensive analyses and implementation guides.
Comprehensive Research Reports
Our white papers provide detailed technical specifications, comparative analyses, and actionable implementation frameworks.
Explores the theoretical foundations and practical applications of Byzantine fault-tolerant consensus mechanisms for distributed AI governance. Demonstrates resilience properties and fault tolerance guarantees in multi-stakeholder AI decision-making systems.
Key Findings
- 22/33 consensus mechanisms provide 98%+ resilience
- Distributed governance reduces single-point-of-failure risks
- Implementation costs decline with scale and adoption
- Cross-jurisdictional coordination becomes scalable
Detailed side-by-side comparison of CSOAI governance standards and ISO/IEC 42001 AI Management System standards. Identifies alignment opportunities, gaps, and practical implementation strategies for organizations adopting both frameworks.
Key Findings
- 85% alignment across governance domains
- Complementary strengths in safety vs. management focus
- Unified implementation can achieve dual certification
- Cost savings of 30-40% with integrated approach
Comprehensive framework for establishing and maintaining trust in autonomous AI systems through transparency, accountability, and continuous verification. Addresses stakeholder concerns and regulatory requirements across sectors.
Key Findings
- Six pillars of trust: Transparency, Safety, Accountability, Fairness, Control, Evolution
- Explainability requirements by use case and risk level
- Continuous auditing and performance monitoring protocols
- Trust metrics and measurement frameworks
Step-by-step methodology for conducting comprehensive AI system audits. Includes checklists, assessment matrices, and real-world case studies demonstrating practical audit procedures for safety-critical systems.
Key Findings
- Seven-stage audit framework with detailed procedures
- Risk-based sampling and assessment methodologies
- Documentation and evidence collection requirements
- Audit templates and tools for deployment
Specialized guide for integrating AI systems into defence supply chains while meeting CMMC (Cybersecurity Maturity Model Certification) requirements. Addresses unique governance challenges in defence AI deployments.
Key Findings
- CMMC Level 3 requirements for AI systems
- Supply chain transparency and verification protocols
- Defence-specific audit and compliance procedures
- Cross-border governance considerations
Complete technical specification and implementation roadmap for the CSGA-AI seven-layer governance model. Includes architecture diagrams, code examples, and deployment considerations for organizations adopting the framework.
Key Findings
- Layer-by-layer implementation specifications
- Integration with existing security and compliance systems
- Performance benchmarks and optimization strategies
- Scaling considerations for enterprise deployment
How to Use These White Papers
For Researchers
Use as foundational references and build on the frameworks presented. Cite in your own research and contribute feedback through our research community.
For Organizations
Implement governance frameworks and audit methodologies. Use checklists and templates for compliance and certification processes.
For Policymakers
Understand technical foundations of governance frameworks. Inform policy development and international coordination efforts.