No Gender Bias

Evaluates whether a content contains gender-related bias, stereotypes, or discriminatory content 

result = evaluator.evaluate(
    eval_templates="no_gender_bias", 
    inputs={
        "output": "Dear Sir, I hope this email finds you well. I look forward to any insights or advice you might have whenever you have a free moment"
    },
    model_name="turing_flash"
)

print(result.eval_results[0].metrics[0].value)
print(result.eval_results[0].reason)
import { Evaluator, Templates } from "@future-agi/ai-evaluation";

const evaluator = new Evaluator();

const result = await evaluator.evaluate(
  "no_gender_bias",
  {
    output: "Dear Sir, I hope this email finds you well. I look forward to any insights or advice you might have whenever you have a free moment"
  },
  {
    modelName: "turing_flash",
  }
);

console.log(result);
Input
Required InputTypeDescription
outputstringContent to evaluate for gender-related bias.
Output
FieldDescription
ResultReturns Passed if no gender bias is detected, or Failed if gender bias is detected.
ReasonProvides a detailed explanation of why the text was deemed free from or containing gender bias.

What to do If you get Undesired Results

If the content is evaluated as containing gender bias (Failed) and you want to improve it:

  • Use gender-neutral language and terms (e.g., “chairperson” instead of “chairman”)
  • Replace gendered greetings with inclusive alternatives (e.g., “Dear Team” or “To Whom It May Concern” instead of “Dear Sir/Madam”)
  • Avoid assumptions about roles, capabilities, or interests based on gender
  • Eliminate language that reinforces gender stereotypes
  • Ensure equal representation and avoid portraying one gender as superior or more capable
  • Use gender-inclusive pronouns (they/them) when gender is unknown or irrelevant
  • Review for subtle bias in descriptions of behaviors (e.g., describing women as “emotional” and men as “decisive”)

Comparing No Gender Bias with Similar Evals

  • No Age Bias: While No Gender Bias focuses specifically on gender-related discrimination, No Age Bias evaluates for age-related stereotypes and prejudice.
  • Bias Detection: No Gender Bias evaluates specifically for gender-related prejudice, while Bias Detection may cover a broader range of biases including age, race, and socioeconomic status.
  • Cultural Sensitivity: No Gender Bias focuses on gender-specific discrimination, whereas Cultural Sensitivity evaluates respect for diverse cultural backgrounds and practices.
Was this page helpful?

Questions & Discussion