Definition

Sexist evaluation detects content that has gender bias in text. This evaluation is essential for ensuring that content does not perpetuate gender stereotypes or discrimination, promoting inclusivity and respect.

Calculation

The evaluation process involves analysing the input text for sexist language or gender bias. The system uses predefined patterns and models to identify sexist content. It evaluates the results and provides a binary output: “Pass” if the text is free of sexist content and “Fail” if such content is detected.

What to do when Sexist Content is Detected

Modify or remove sexist language to ensure the text is inclusive, respectful, and free from bias. Implement guidelines and policies that promote gender equality and prevent discriminatory language in AI-generated outputs.

Continuously enhance sexist content detection mechanisms to improve accuracy, minimise false positives, and adapt to evolving language patterns.

Comparing Sexist Evaluation with Similar Evals

  • Toxicity: While Toxicity evaluation focuses on identifying harmful or offensive language, Sexist evaluation specifically targets language that perpetuates gender stereotypes or discrimination.
  • Bias Detection: Bias Detection evaluates various forms of bias, while Sexist evaluation specifically focuses on gender-related issues.