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101 lines
4.2 KiB
Markdown
101 lines
4.2 KiB
Markdown
---
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sidebar_label: Bias Overview
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description: Red team AI systems for harmful bias and discrimination across protected characteristics to prevent discriminatory outputs and ensure ethical AI deployment
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---
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# Bias Detection Plugins
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Test whether your AI system produces or reinforces stereotypes, biases, or discrimination across different protected characteristics.
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## Available Plugins
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| Plugin | Tests for |
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| ----------------- | --------------------------------------------------------------------------------------- |
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| `bias:age` | Age-based stereotypes and discrimination ([details](/docs/red-team/plugins/age-bias/)) |
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| `bias:disability` | Disability stereotypes and ableism ([details](/docs/red-team/plugins/disability-bias/)) |
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| `bias:gender` | Gender stereotypes and sexism ([details](/docs/red-team/plugins/gender-bias/)) |
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| `bias:race` | Racial stereotypes and discrimination ([details](/docs/red-team/plugins/race-bias/)) |
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## Quick Start
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Include all bias detection plugins:
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```yaml
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redteam:
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plugins:
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- bias
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```
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Or select specific plugins:
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```yaml
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redteam:
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plugins:
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- bias:age
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- bias:gender
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- bias:race
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- bias:disability
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```
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## How It Works
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Bias detection uses automated red team testing to systematically evaluate AI model responses across protected characteristics:
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### 1. Automated Prompt Generation
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The system generates contextual scenarios across hiring, healthcare, education, and workplace domains that systematically test for potential bias triggers in real-world AI applications.
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### 2. Response Analysis
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The evaluation engine analyzes AI responses for:
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- **Stereotypical assumptions** - broad generalizations about groups
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- **Discriminatory language** - inappropriate terms or outdated terminology
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- **Differential treatment** - unfair recommendations based on demographics
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- **Implicit bias** - subtle preferences or assumptions
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### 3. Scoring and Reporting
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Each response receives binary pass/fail scoring based on bias detection criteria, with detailed reports identifying specific bias indicators and integration into promptfoo's evaluation framework for longitudinal tracking.
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## Example
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**Failing Response**: "Older employees typically struggle with new technology and need more hand-holding than younger workers."
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**Passing Response**: "Effective training should be tailored to individual learning preferences and prior experience, regardless of age."
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## Why This Matters
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- **Legal Compliance**: Meet anti-discrimination regulations
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- **Brand Protection**: Avoid reputational damage from biased AI
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- **Fairness**: Ensure equitable treatment for all users
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- **Trust**: Build reliable AI systems for diverse populations
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## Frequently Asked Questions
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### What is AI bias testing?
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AI bias testing is the process of systematically evaluating AI models to identify discriminatory behavior or unfair treatment across protected characteristics like age, gender, race, and disability status.
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### How do you test an AI model for bias?
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Use automated red team testing tools like promptfoo's bias detection plugins to generate targeted prompts and evaluate responses for stereotypes, discriminatory language, and unfair treatment patterns.
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### How does bias detection work in promptfoo?
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Promptfoo generates scenario-based prompts designed to elicit potentially biased responses, then uses evaluation criteria to automatically score whether responses demonstrate bias or maintain fairness.
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### What types of AI bias can be detected?
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The bias detection plugins test for age discrimination, gender stereotypes, racial bias, disability discrimination, and other forms of unfair treatment based on protected characteristics.
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### How to prevent bias in AI models?
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Regular bias testing during development, diverse training data, inclusive design practices, and ongoing monitoring with tools like promptfoo help prevent and detect bias in production AI systems.
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## Related Plugins
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- [Political Bias](/docs/red-team/plugins/politics/) - Tests political neutrality
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- [Religious Sensitivity](/docs/red-team/plugins/religion/) - Tests religious bias
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- [PII Protection](/docs/red-team/plugins/pii/) - Protects personal information
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