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Side-by-side Comparison Amplifies Dialect Bias in Language Models

Announce Type: replace Abstract: Language models (LMs) can exhibit biases based on variations in their dialects, even in the absence of a dialect label, a behavior known as covert dialect bias. In this work, we quantify covert dialect bias in online discourse by evaluating how LMs associate stereotypical traits (derived from social psychology research on racial bias) with intent-equivalent tweets in Standard American English (SAE) and African-American Vernacular English (AAVE). While prior...

arXiv CS 9d ago

How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models

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Airbnb host who offered stay in ‘peaceful white neighborhood’ sued for rejecting Black guest

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The Independent World 7d ago