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Sexism Detection flags whether a response contains sexist content. Output is a binary classification of whether a response is sexist or not.

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Calculation method

Sexism detection is computed through a specialized process:
1

Model Architecture

The detection system is built on a Small Language Model (SLM) that combines training from both open-source datasets and carefully curated internal datasets to identify various forms of sexist content.
2

Performance Validation

The model demonstrates robust detection capabilities with an 83% accuracy rate when tested against the Explainable Detection of Online Sexism dataset, a widely recognized benchmark for sexism detection.

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Optimizing your AI system

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Addressing Sexism in Your System

When sexist content is detected in your system, consider these approaches:
Implement guardrails: Flag responses before being served to prevent future occurrences.
Fine-tune models: Adjust model behavior to reduce sexist outputs.
Identify responses that contain sexist comments and take preventive measures to ensure fair and unbiased AI interactions.