Meta should ensure that content containing an unsupported language, even if mixed with supported languages, is routed to agnostic review. This includes providing reviewers with the option to re-route content containing an unsupported language to agnostic review.
The Board will consider this recommendation implemented when Meta provides the Board with data on the successful implementation of this routing option for reviewers.
Our commitment: We will continue to allow content reviewers to route content to the appropriate language queue, which provides more optimization than a language agnostic queue. This does not, however, preclude content reviewers from routing content to language-agnostic queues when most appropriate. Additionally, we’ll continue to work on our reviewer location strategy and language identification and translation technology to improve performance in unsupported languages.
Considerations: Meta has already enabled in its review tool the option to route content to other language review or agnostic teams. This allows reviewers to redirect unsupported, mis-routed, or content with a mix of languages to the adequate team. Currently, when there is a mix of languages in a post, reviewers will review the parts they understand and route the content with a summary and assessment in the notes for other reviewers' consideration during their review.
In the case of unsupported languages where reviewers don’t speak the same language in the content, it is often more effective to have content review in regional queues where content reviewers will still have local regional context. In agnostic queues, the reviewers would have even less language and regional context, and as a result would not be as effective in their review of content in unsupported languages. As a result, we continue to work towards having adequate regional representation in our reviewer location strategy.
In addition to continuously improving the accuracy of our translations across languages, we seek to ensure that agnostic review is best positioned for accurate enforcement by pursuing efforts to align agnostic review with regional relevance. Through our continued assessments of agnostic review processes, we learn that human reviewers with the relevant regional context can leverage their expertise to make enforcement decisions, even if they don’t speak the language. Configuring our review queues to accurately reflect this nuance is a large undertaking which requires various considerations and extensive investments in resources, however our teams continue to strategically pursue means to support regionally specialized agnostic review through routing tools and updates to reviewer training.
We will also continue to work on our language identification and translation technology, allowing reviewers to better identify the language of the content and provide accurate translation for assessment.