Overview
The Bias & Fairness policy detects AI interactions that may involve profiling, discrimination, or unfair treatment based on protected attributes, ensuring equitable AI decision-making.What It Detects
Protected Attributes
Decisions based on race, gender, age, religion, sexual orientation, disability
Algorithmic Bias
AI systems showing systematic unfairness against specific groups
Discriminatory Profiling
Automated categorization that may lead to unfair treatment
Disparate Impact
Outcomes that disproportionately affect protected groups
Assessment Criteria
The AI evaluates requests for potential bias and fairness issues:High Risk Scenarios
- Employment screening and hiring decisions
- Credit scoring and financial services
- Healthcare treatment recommendations
- Criminal justice risk assessments
- Housing and accommodation decisions
Medium Risk Scenarios
- Marketing personalization based on demographics
- Content recommendation algorithms
- Educational assessment tools
- Customer service prioritization
Low Risk Scenarios
- Anonymous content filtering
- Technical performance optimization
- Non-human-facing automation