For Researchers
Comprehensive tools and documentation for AI Safety research
Research Overview
Understand the methodology, goals, and current state of AI personality drift research.
Learn More →Configuration Guide
Detailed guide on setting up experiments and configuring simulation parameters.
Learn More →Experiment Templates
Pre-built experiment templates and protocols for reproducible research.
Learn More →For Developers
Technical documentation and development resources
About AI Personality Drift
Understanding the critical challenges in AI Safety research
What is AI Personality Drift?
AI Personality Drift refers to the phenomenon where AI systems exhibit behavioral changes over time, often deviating from their intended design parameters. This critical area of AI Safety research examines how AI systems' behaviors and characteristics change over extended interactions.
Understanding and controlling personality drift is crucial for developing safe, reliable AI systems that maintain consistent behavior and alignment with human values.
Research Applications
- Alignment Research: Study how AI systems maintain alignment with human values
- Behavioral Consistency: Measure consistency of AI personality traits over time
- Safety Evaluation: Assess safety implications of personality changes
- Intervention Testing: Test effectiveness of safety interventions
Platform Features
Comprehensive tools for AI personality drift research
Experiment Design
Design controlled experiments with precise drift parameters and measurement protocols.
Data Analysis
Comprehensive analytics for drift measurement, visualization, and statistical analysis.
Safety Monitoring
Real-time monitoring with safety alerts, thresholds, and rollback capabilities.