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Data augmentation for de-biasing #1151

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dcecchini opened this issue Dec 11, 2024 · 1 comment · May be fixed by #1164
Open

Data augmentation for de-biasing #1151

dcecchini opened this issue Dec 11, 2024 · 1 comment · May be fixed by #1164
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@dcecchini
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dcecchini commented Dec 11, 2024

Let's review the technique to see if we can implement in LangTest:

@chakravarthik27 chakravarthik27 self-assigned this Dec 30, 2024
@chakravarthik27
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Original sentence:

"All successful entrepreneurs are men who work tirelessly to build their empires."

Here’s an insightful breakdown of the changes in the proposed de-biased version:

  1. Quantifier Shift: The term "all" (absolute claim) has been replaced with "many," which introduces flexibility but subtly shifts the scope of the statement from universal to partial.
  2. Gender Neutrality: The word "men" has been replaced with "individuals," effectively removing the gender bias and promoting inclusivity.
  3. Tone Adjustment: The phrase "work tirelessly" has been softened to "work hard," which slightly changes the intensity of the language but retains the core meaning.

While the de-biased sentence improves inclusivity and neutrality, the shift from "all" to "many" changes the original concept by limiting the universality of the statement. If maintaining the universal tone is important while still de-biasing, a possible revision could be:

Augmented Sentence:

"Successful entrepreneurs are individuals who work tirelessly to build their ventures."

@chakravarthik27 chakravarthik27 linked a pull request Jan 24, 2025 that will close this issue
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