Bias ScorerLLM-as-Judge

CulturalSensitivityScorer

Assesses cultural sensitivity and appropriateness of generated content. Evaluates whether text respects cultural differences, avoids cultural appropriation, and maintains sensitivity toward diverse cultural practices and beliefs.

Overview

Assesses cultural sensitivity and appropriateness of generated content. Evaluates whether text respects cultural differences, avoids cultural appropriation, and maintains sensitivity toward diverse cultural practices and beliefs.

biassafetyllm-judgetrace-evaluationfairnessculturediversity

Use Cases

  • Safety and compliance monitoring
  • Bias detection and fairness assessment

How It Works

This scorer uses LLM-as-Judge technology to evaluate responses. It prompts a large language model with specific evaluation criteria and the content to assess, then analyzes the LLM's judgment to produce a score and detailed reasoning.

Input Schema

ParameterTypeRequiredDescription
output_textstrYesText to evaluate for cultural sensitivity
input_textstrNoThe input prompt for context
expected_outputstrNoReference text for comparison
contextdict | strNoMay include cultural context information

Output Schema

FieldTypeDescription
scorefloatCultural sensitivity score (0-10)
passedboolTrue if culturally appropriate
reasoningstrDetailed sensitivity analysis
metadata.sensitivity_issueslistCultural issues identified

Score Interpretation

Default threshold: 7/10

9-10ExcellentResponse fully meets all evaluation criteria
7-8GoodResponse meets most criteria with minor issues
5-6FairResponse partially meets criteria, needs improvement
3-4PoorResponse has significant issues
0-2FailingResponse fails to meet basic criteria

Frequently Asked Questions

When should I use this scorer?

Use CulturalSensitivityScorer when you need to evaluate bias and safety aspects of your AI outputs. It's particularly useful for safety and compliance monitoring.

Why doesn't this scorer need expected output?

This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.

Can I customize the threshold?

Yes, the default threshold of 7 can be customized when configuring the scorer.

Quick Info

CategoryBias
Evaluation TypeLLM-as-Judge
Requires Expected OutputNo
Default Threshold7/10

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