The Secondary Opinion Protocol
Don't just trust. Verify. Falsify.
To bridge fundamental research and real-world impact, AICRIT is working on the Second Opinion Protocol. In this mode, AICRIT operates as an independent, automated second-opinion system for policies, strategies, and AI-driven decisions.
How It Works
Our systems transform thousands of pages of documents, datasets, and deliberations into verifiable, deconstructed analyses. Drawing from centuries of dialectic logic, we design AI agents that:
01 / REVEAL
Identify hidden assumptions and epistemic biases within the input data.
02 / TRACE
Map the sedimentation of data and influence, ensuring traceability to the verifiable source.
03 / PRODUCE
Generate decisions that can be challenged, not merely accepted.
04 / OPTIMIZE
Reduce AI's carbon footprint.
The Workflow Engine
AICRIT Stack orchestrates complex adversarial agent interactions and the dialectic "thinking" process. This layer ensures that every step of the interrogation—from data ingestion to the final challenge—is executed, tracked, and verifiable across the stack.
Use Cases
- Auditing Policy: Scanning proposals for greenwashing or hidden lobbying influence.
- Stress-Testing: Challenging institutional narratives and AI-generated reports with adversarial logic.
- Transparency Trails: Producing defensible decision trails that can be inspected by humans.
Frequently Interrogated Questions
How does AICRIT bridge the "Opacity Gap"?
AICRIT transforms the AI "Black Box" into a Glass Box. AICRIT maps inference and reasoning into transparent, auditable processes, even at node level. This traceability allows teams to review and replay the AI's decision path, converting what would otherwise be statistical outputs into fully documented, defensible decision records. For example, when an AI recommends a particular investment strategy, AICRIT provides stakeholders with a complete trail of the reasoning process, highlighting which data points influenced the recommendation and why.
How does the Second Opinion Protocol prevent AI greenwashing?
Traditional AI often regurgitates corporate sustainability reports without auditing the underlying data. AICRIT's Second Opinion Protocol deconstructs claims by deploying adversarial agents that demand primary source verification. If a model claims "carbon neutrality," the protocol forces a trace to the specific energy joules and offset certifications, exposing the gap between marketing narratives and material facts.
What is Epistemic Security and why does AICRIT prioritize it?
Epistemic Security in AICRIT protects the integrity of knowledge and decision-making processes—essentially safeguarding how we know what we know. In today's AI landscape, organizational knowledge is vulnerable to misinformation, AI hallucinations, and manipulated data. AICRIT builds security directly into the information architecture, ensuring every insight is traceable to verified sources and tested against contrary evidence. This approach verifies the actual content and reasoning behind AI outputs.
What is a "Dialectic Worker" and how does it optimize energy efficiency?
Dialectic Workers are specialized AI agents designed for specific logical tasks rather than resource-intensive general processing. Similar to microservices in software architecture, these purpose-built agents handle targeted functions with minimal computational overhead. The AICRIT workflow routes tasks to the most efficient worker—using lightweight local models for sensitive analysis and reserving power-intensive computation only when necessary. This orchestration can reduce energy consumption significantly compared to always-on large language models while maintaining comparable performance.
How does the protocol support Multi-Intelligence Decisionmaking?
Our architecture treats AI, ecological data, and Indigenous knowledge as peer intelligence systems. Instead of a single "correct" answer, the protocol maps the dialectic—the tensions and agreements between different ways of knowing. This ensures city planners or cooperative leaders see a "Transparency Trail" that respects relational resilience over techno-authoritarian enforcement.
Why is Data Residency a core feature of the AICRIT Stack?
In the age of AI extraction, data residency is the foundation of sovereignty. The AICRIT protocol utilizes "Hard-Coded Geographic Integrity," ensuring that sensitive interrogation logic—whether in Vancouver Island or Rwanda—is executed within local legal and physical boundaries, preventing the "data laundering" common in centralized cloud architectures.
What is the "Adversarial Synthesis" method?
Unlike standard AI systems that primarily seek confirming evidence, AICRIT's Adversarial Synthesis actively searches for contradictory information. This approach, inspired by legal discovery processes, automatically generates comprehensive briefings that include supporting evidence, potential counterarguments, and identified uncertainties. For critical decisions, this prevents confirmation bias by ensuring decision-makers see not just what supports their hypothesis, but also what might challenge it—turning potential blind spots into visible considerations..