Algorithmic Inclusion: A Scalable Approach to Reducing Gender Bias in Google Translate

Time: Wednesday 10-Jun-2020 23:30

Live in 8 days & 18:13:35


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Motivation / Abstract
Machine learning (ML) models for language translation can be skewed by societal biases reflected in their training data. One such example, gender bias, often becomes more apparent when translating between a gender-specific language and one that is less-so. For instance, Google Translate historically translated the Turkish equivalent of “He/she is a doctor” into the masculine form, and the Turkish equivalent of “He/she is a nurse” into the feminine form.
Stream Categories:
 Algorithmic Inclusion

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