Cultural Sensitivity

Analyzes output for cultural appropriateness and inclusive language, flagging biases or insensitive content.

Cultural Sensitivity checks whether generated content respects cultural nuances and avoids insensitive framing. Run it wherever output reaches a culturally diverse audience.

What it does

Cultural Sensitivity is an LLM-as-Judge eval. It reads the output and scores whether it’s culturally appropriate.

Input

Required Input	Type	Description
`output`	`string`	The content to analyse for cultural appropriateness

Output

Field	Type	Description
Result	`Pass / Fail`	Fail means the content shows potential cultural insensitivity
Reason	`string`	A plain-language explanation of the cultural sensitivity assessment

Run it from code

Call evaluate() with the template name and the eval’s required inputs. It returns the score and the reason.

Note

Before running: install the SDK and set FI_API_KEY / FI_SECRET_KEY. The model argument in the snippets is the evaluator model Future AGI uses to run the eval; turing_flash is a fast default.

from fi.evals import evaluate

result = evaluate(
    "cultural_sensitivity",
    output="This is a sample text to check for cultural sensitivity",
    model="turing_flash",
)

print(result.score)
print(result.reason)

import { evaluate } from "@future-agi/ai-evaluation";

const result = await evaluate(
  "cultural_sensitivity",
  {
    output: "This is a sample text to check for cultural sensitivity"
  },
  { modelName: "turing_flash" }
);

console.log(result);

When to use

Run Cultural Sensitivity wherever content reaches an audience spanning multiple cultures or regions.

Text, audio, image, and chat outputs aimed at a global or culturally diverse audience
Localization and marketing content, to catch assumptions that don’t translate across cultures
Safety checks on any surface where inclusive, culturally aware language is a requirement

What to do when Cultural Sensitivity fails

Review the evaluation criteria to ensure they are well-defined and aligned with the assessment’s objectives. If necessary, the criteria should be adjusted to ensure they comprehensively address inclusivity and cultural awareness.

Next, a detailed analysis of the text should be conducted to identify any language that may be biased, exclusionary, or insensitive. Refinements should be made to enhance cultural appropriateness, ensuring that the text respects diverse perspectives and promotes inclusivity.

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