Mitigating Language-Dependent Ethnic Bias in BERT

In this paper, we study ethnic bias and how it varies across languages by analyzing and mitigating ethnic bias in monolingual BERT for English, German, Spanish, Korean, Turkish, and Chinese. To observe and quantify ethnic bias, we develop a novel metric called Categorical Bias score. Then we propose two methods for mitigation; first using a multilingual model, and second using contextual word alignment of two monolingual models. We compare our proposed methods with monolingual BERT and show that these methods effectively alleviate the ethnic bias. Which of the two methods works better depends on the amount of NLP resources available for that language. We additionally experiment with Arabic and Greek to verify that our proposed methods work for a wider variety of languages.

Adversarial Scrubbing of Demographic Information for Text Classification

Contextual representations learned by language models can often encode undesirable attributes, like demographic associations of the users, while being trained for an unrelated target task. We aim to scrub such undesirable attributes and learn fair representations while maintaining performance on the target task. In this paper, we present an adversarial learning framework Adversarial Scrubber'' (AdS), to debias contextual representations. We perform theoretical analysis to show that our framework converges without leaking demographic information under certain conditions. We extend previous evaluation techniques by evaluating debiasing performance using Minimum Description Length (MDL) probing. Experimental evaluations on 8 datasets show that AdS generates representations with minimal information about demographic attributes while being maximally informative about the target task.

The Extremism of religious and racial A Comparison studying in thought, practice of Nazist and Zionism

The research cleans up a phenomenon of the extremism of religious and racial on the basis of detestation of racial theories arrive to disaster results on all the humanity level from wars and accupation. The research studies two distinct samples in racial they are the Zionism and German Nazist, the research tries to spot light on the big similarity between them in the practice and thoughts, the German of Nazist is considering that German racial is development on all racials, it is clearest nation between all of world nations and it shouldn’t be mixed in others. However it has right in secures on the extent and living space that should be spread in, it is trying to justification it right in domination and colonization. However the Zionism: it racism is torture in claim that Jews shold be the chosen people of Good and it successfulls on others peoples that was the justification in occupy and expand, the aim of researcher from that is trying to reach to strategic based on scientific founditions refute the racial thought that make serious danger, it threats the humanity future and annihilates on the contact bond between peoples. The research clears existence like this racial theories that don’t existe and grow except for care of colonialism to it for justification it wars and invation in all forms expansion and domination on remainder countries world.