Managing Bias, Inclusivity, and Offensive Content in Multiple Languages

welocalize July 6, 2022

How AI and NLP can be used to monitor, identify, rate, and replace harmful content

Non-inclusive and hate speech online content is an increasing and important issue —and the problem is multilingual. The consequences of harmful content are varied and very real.

People post an immense amount of data online every minute. Every second, on average, there are 6,000 posts tweeted on Twitter. Diversity, equality, and inclusion (DEI) has never been  so important to people and companies around the world.

And it’s not just content posted by users on forums or in social media, but unconsciously, companies themselves could be posting content internally and externally that is biased – for example, ‘master/slave dependency’ terminology used to describe software systems in product content.

So how do we deal with potentially harmful, biased content?

Artificial intelligence (AI) and especially natural language processing (NLP) are playing key roles in uncovering and replacing offensive content online in multiple languages.

Welocalize CEO Smith Yewell and Welocalize VP of AI Innovation Olga Beregovaya recently took part in a CSA Research Leadership Council on this very topic. In this short video, they talk about the innovation behind this approach and how global brands can manage volumes of (potentially) harmful content. Olga goes into detail on the concept of using NLP to make improvements in inclusive speech, without impacting the true meaning of language. Take a look at the video to learn more:


“Inclusive language is an essential part of companies’ Diversity, Equity, and Inclusion (DEI) policies – and yet many tell CSA Research that they struggle when taking these strategies global.  Whether within their own content, or that shared through social media, organizations are looking for help and guidance in identifying and standardizing content that excludes no-one. This is an area of opportunity for AI and NLP tools to be used to identify instances of non-inclusivity, to flag bias, and to suggest replacement with better content in both English and other languages.”

Alison Toon, Senior Research Analyst, CSA Research


More about the solution..

This AI-enabled solution won the 2022 American Best in Business Awards’ Silver Globee. It leverages deep learning neural models in 60+ #languages to monitor, identify, rate, and remove offensive #multilingual content. The cutting-edge technology analyzes client’s own marketing materials and user assistance materials for non-inclusivity, and identifies offensive/harmful content in non-branded user generated content (UGC) such as knowledge bases, forums, opinion portals, and emails.

If you would like to speak to a member of the Welocalize AI team to see how we can help, contact us here.