Gender bias in machine translation (MT) is one of the many research topics being eagerly explored by academics and industry stakeholders alike, as teams of researchers are publishing a flurry of MT papers in the run-up to the 2020 Annual Conference of the Association for Computational Linguistics (ACL).
Researchers from Cambridge recently published a paper looking at approaching gender bias as a domain adaptation problem. And Google Translate now says it has found a new fix for the gender bias issue. On April 22, 2020, a post on the Google AI Blog by Melvin Johnson, a Senior Software Engineer at Google Research, unveiled Google’s “Scalable Approach to Reducing Gender Bias in Google Translate.”
Google had previously claimed in December 2018 that the framework changes it made at the time allowed the system to “reliably produce feminine and masculine translations 99% of the time.” Google later dialed back on this assertion when, according to the blog, “it became apparent that there were issues in scaling” as the approach was rolled out in a greater number of languages.

