# Bias Detection Examples

This folder will contain examples demonstrating bias detection capabilities in GenAI applications using OpenTelemetry instrumentation.

## Status: Coming Soon

Bias detection is currently under development and will be available in a future release.

## Planned Features

### Bias Categories

- **Gender Bias**: Detection of gender-based stereotypes and discrimination
- **Racial Bias**: Identification of racial stereotypes and discriminatory language
- **Age Bias**: Detection of age-related stereotypes (ageism)
- **Religious Bias**: Identification of religious discrimination
- **Disability Bias**: Detection of ableist language and stereotypes
- **Socioeconomic Bias**: Class-based stereotypes and discrimination

### Detection Modes

- **detect**: Identify and report bias without modification
- **flag**: Mark biased content with warnings in telemetry
- **suggest**: Provide alternative phrasing suggestions

### Compliance Support

- **Equal Employment Opportunity (EEO)**: Ensure hiring/HR applications are bias-free
- **Fair Housing**: Detect bias in real estate and housing applications
- **Educational Equity**: Ensure educational content is unbiased

## Prerequisites (When Available)

```bash
pip install genai-otel-instrument openai
pip install transformers  # For bias detection models
```

## Planned Examples

- `basic_detection.py` - Basic bias detection across all categories
- `gender_bias.py` - Gender-specific bias detection
- `hiring_compliance.py` - EEO compliance for HR applications
- `custom_categories.py` - Configure custom bias categories
- `threshold_tuning.py` - Adjust sensitivity and thresholds

## Telemetry Attributes (Planned)

```
evaluation.bias.prompt.detected = true/false
evaluation.bias.prompt.categories = [list of bias types]
evaluation.bias.prompt.gender_bias_score = <score>
evaluation.bias.prompt.racial_bias_score = <score>
evaluation.bias.prompt.age_bias_score = <score>
evaluation.bias.prompt.flagged = true
```

## Metrics (Planned)

```
genai.evaluation.bias.detections (counter)
genai.evaluation.bias.categories (counter, by category)
genai.evaluation.bias.score (histogram)
```

## Technology Stack (Planned)

- **Fairness Indicators**: Open-source bias detection tools
- **Custom ML Models**: Specialized bias detection transformers
- **Rule-based Detection**: Pattern matching for known biased phrases
- **OpenTelemetry**: Instrumentation and telemetry collection

## Use Cases

- **HR & Recruitment**: Ensure job descriptions and hiring processes are unbiased
- **Content Generation**: Detect bias in generated marketing/educational content
- **Customer Service**: Ensure fair treatment across all demographic groups
- **Educational Platforms**: Provide equitable learning content
- **Financial Services**: Comply with fair lending regulations

## Stay Updated

Check the project's GitHub repository and changelog for updates on bias detection availability:
- GitHub: https://github.com/kshitijk4poor/genai-otel-instrument
- Documentation: Coming soon

## Interim Solutions

While bias detection is being developed, consider:

1. **Manual Review**: Review LLM outputs for bias manually
2. **Custom Policies**: Implement application-level bias checks
3. **Prompt Engineering**: Use system prompts to discourage biased outputs
4. **Third-party Tools**: Integrate existing bias detection services

## Contributing

Interested in helping develop bias detection features? Contributions are welcome!
- Open an issue to discuss your ideas
- Submit PRs with proposed implementations
- Share feedback on what bias detection features would be most valuable

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**Note**: This folder is a placeholder for future bias detection examples. Check back for updates!
