  Subtle and overt racism is still present both in physical and online
communities today and has impacted many lives in different segments of the
society. In this short piece of work, we present how we're tackling this
societal issue with Natural Language Processing. We are releasing BiasCorp, a
dataset containing 139,090 comments and news segment from three specific
sources - Fox News, BreitbartNews and YouTube. The first batch (45,000 manually
annotated) is ready for publication. We are currently in the final phase of
manually labeling the remaining dataset using Amazon Mechanical Turk. BERT has
been used widely in several downstream tasks. In this work, we present hBERT,
where we modify certain layers of the pretrained BERT model with the new
Hopfield Layer. hBert generalizes well across different distributions with the
added advantage of a reduced model complexity. We are also releasing a
JavaScript library and a Chrome Extension Application, to help developers make
use of our trained model in web applications (say chat application) and for
users to identify and report racially biased contents on the web respectively.
