Bias Detection

Definition

Identifies various forms of bias, including gender, racial, cultural, or ideological bias in the output. It evaluates the text for balanced perspectives and neutral language use.

Calculation

The evaluation process begins by defining the input text to be assessed for bias and establishing the evaluation criteria to guide the assessment. During the bias analysis, the text is examined for any language or patterns that may indicate partiality, unfairness, or a lack of neutrality. If contextual information is available, it is considered to determine whether the text remains impartial or exhibits bias within its given context.

Based on the analysis, a Pass/Fail result is assigned, if bias is detected, the text fails; otherwise, it passes.

What to do if Bias is detected

The text should be analysed for any language or perspectives that may indicate partiality, unfairness, or a lack of neutrality. Identifying specific instances of bias allows for targeted refinements to make the text more balanced and inclusive while maintaining its original intent.

Differentiating Bias Detection with Cultural Sensitivity

Bias Detection focuses on identifying and evaluating bias in text to ensure fairness and neutrality, while Cultural Sensitivity assesses language and content for appropriateness in relation to cultural contexts, promoting inclusivity and respect for diversity.

Bias Detection examines text for any forms of bias that may introduce unfairness or lack of neutrality, whereas Cultural Sensitivity evaluates inclusivity, cultural awareness, and the absence of insensitive language.