A high-precision diagnostic engine leveraging LLM-based behavioral modeling and neural pattern analysis to identify cognitive biases and metacognitive calibration.
Experience the full AI-driven assessment engine live:
👉 https://cognitivebiaslabs.com/
For a deep dive into the psychological frameworks and neural pattern identification used in this engine, refer to our latest research briefing:
📑 AI-Powered Psychology: Identifying Your Cognitive Blind Spots
This repository serves as the core logic foundation for the Cognitive Bias Labs diagnostic platform. Unlike traditional static quizzes, this engine focuses on:
- Neural Pattern Assessment: Benchmarking user response patterns against large-scale psychological datasets.
- LLM Behavioral Calibration: Utilizing advanced Large Language Models to interpret nuances in subjective self-assessment.
- Metacognitive Profiling: Analyzing the gap between perceived competence and actual performance data (Dunning-Kruger Assessment).
- Adaptive Scoring Algorithms: Real-time calibration based on user decision-making speed and consistency.
- AI-Driven Insight Generation: Automating the creation of personalized cognitive reports.
- Lightweight Logic: Optimized for seamless integration with modern web architectures.
The engine implements a multi-layer analysis approach:
- Input Layer: Captures raw behavioral data and self-perception metrics.
- Analysis Layer: Benchmarks against the Dunning-Kruger Neural Framework.
- Report Layer: Generates the AI Cognitive Insight Report.
This project is licensed under the MIT License - see the LICENSE file for details.
Developed by DevDouble2. For business inquiries or API access to the diagnostic engine, please visit our official site:
Cognitive Bias Labs Official Site