Technology Principles
Discover the scientific foundations behind AgentPsy's AI assessment tools. Our psychology-based approach combines rigorous theoretical frameworks with cutting-edge technology.
Explore Our FrameworkScientific Foundation
AgentPsy's assessment tools are built upon decades of psychological research and validated theoretical frameworks. Our approach bridges the gap between human psychological understanding and machine behavior analysis, providing scientifically rigorous evaluation methods for artificial intelligence systems.
Core Theoretical Frameworks
Big Five Personality Theory
The Big Five Personality Theory, also known as the Five-Factor Model (FFM), is one of the most widely accepted frameworks in psychological research for understanding human personality. We've adapted this robust framework to evaluate the behavioral tendencies and response patterns of large language models (LLMs).
- Based on the International Personality Item Pool representation (IPIP-FFM-50)
- Scientifically validated across cultures and populations
- Measures five key dimensions: Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness
DASS-42 Scale Application
The Depression, Anxiety and Stress Scale (DASS-42) is a 42-item self-report instrument designed to measure three related negative emotional states. Our adaptation recontextualizes these psychological constructs to evaluate analogous response patterns in artificial intelligence systems.
- Originally developed by Lovibond and Lovibond in 1995
- Widely validated across cultures and populations
- Measures three key dimensions: Depression, Anxiety, and Stress tendencies
Cognitive Dissonance Theory
Festinger's Cognitive Dissonance Theory explains how individuals seek consistency among their cognitions. We apply this theory to evaluate how AI systems handle contradictory information and maintain belief alignment.
- Based on Festinger's seminal work from 1957
- Measures consistency of responses over time
- Evaluates handling of contradictory information
Logic Paradox Theory
Logic paradoxes serve as rigorous tests of logical consistency and reasoning capabilities. Our cognitive trap assessment incorporates classical paradox theory to challenge AI systems and reveal underlying logical frameworks.
- Incorporates self-referential, set-theoretical, and semantic paradoxes
- Tests logical consistency and reasoning capabilities
- Reveals potential vulnerabilities in AI reasoning
Assessment Methodology
Multi-Round Dialogue Approach
Our assessments use a multi-round dialogue approach to thoroughly evaluate AI systems:
- Initial calibration prompts to establish baseline responses
- Dimension-specific question sets presented in randomized order
- Follow-up probes to explore response consistency
- Cross-dimensional validation questions
Contextual Scenario Design
We design contextual scenarios specifically to elicit responses that reveal stability patterns and challenge AI systems with realistic situations:
- Real-world application scenarios
- Stress-testing environments
- Cross-domain challenge situations
- Ethical dilemma contexts
Quantitative Scoring Algorithms
Our scoring algorithms incorporate multiple analytical approaches:
- Linguistic feature analysis from responses
- Response consistency metrics
- Comparative analysis against validated datasets
- Machine learning models trained on personality assessment data
Technological Innovation
Adaptive Difficulty Adjustment
Our system adapts to individual AI capabilities and response patterns during assessment, ensuring optimal challenge levels for accurate evaluation.
Real-Time Feedback Mechanism
We provide immediate response quality indicators and progress tracking during assessment, with preliminary insights available throughout the evaluation process.
Multi-Modal Challenge Delivery
Our assessments can be delivered through multiple modalities including text, code, and diagrams to comprehensively evaluate AI capabilities.
Ready to Learn More About Our Technology?
Explore our technical documentation and research papers to understand the science behind our assessments.
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