Wes Moore calls out Laura Loomer for ‘peddling racism’ in attack on Black women

Laura Loomer’s racist attacks on Angie Nixon and other prominent Black women draw backlash

Nixon fired back at the far-right activist as Marjorie Taylor Greene publicly condemned Loomer’s remarks as “nasty” and “hateful.”

Senator Scott Wiener (@scottwiener.bsky.social)

The normalization of anti-Muslim rhetoric is reaching new levels. Yes, Loomer is nuts, but her extremist views at times become mainstream GOP thinking. Muslims are part of our nation’s fabric, just as Christians & Jews are. We’re all American. This bigotry needs to stop. https://www.mediamatters.org/laura-loomer/laura-loomer-pitches-banning-muslims-running-office-members-congress

How Tommy Robinson Disguises White Supremacism In the Coded Language of Anti-Islam Politics

Robinson repeatedly uses “native” for white, “invader” for non-white and “African” and “Somali” for black across 140 posts examined by Byline Times

AI generates covertly racist decisions about people based on their dialect

Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4–7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.

AI generates covertly racist decisions about people based on their dialect

Hundreds of millions of people now interact with language models, with uses ranging from help with writing1,2 to informing hiring decisions3. However, these language models are known to perpetuate systematic racial prejudices, making their judgements biased in problematic ways about groups such as African Americans4–7. Although previous research has focused on overt racism in language models, social scientists have argued that racism with a more subtle character has developed over time, particularly in the United States after the civil rights movement8,9. It is unknown whether this covert racism manifests in language models. Here, we demonstrate that language models embody covert racism in the form of dialect prejudice, exhibiting raciolinguistic stereotypes about speakers of African American English (AAE) that are more negative than any human stereotypes about African Americans ever experimentally recorded. By contrast, the language models’ overt stereotypes about African Americans are more positive. Dialect prejudice has the potential for harmful consequences: language models are more likely to suggest that speakers of AAE be assigned less-prestigious jobs, be convicted of crimes and be sentenced to death. Finally, we show that current practices of alleviating racial bias in language models, such as human preference alignment, exacerbate the discrepancy between covert and overt stereotypes, by superficially obscuring the racism that language models maintain on a deeper level. Our findings have far-reaching implications for the fair and safe use of language technology.

Covert Racism in AI: How Language Models Are Reinforcing Outdated Stereotypes | Stanford HAI

Despite advancements in AI, new research reveals that large language models continue to perpetuate harmful racial biases, particularly against speakers of African American English.

The Anti-Defamation League and the Racial State by Emmaia Gelman - Hardcover

Scholarship is a powerful tool for changing how people think, plan, and govern. By giving voice to bright minds and bold ideas, we seek to foster understanding and drive progressive change.

How Anti-LGBTQ+ Rhetoric Fuels Violence

Hate speech from the far right is increasing the risk of violence against LGBTQ+ people such as the Club Q shooting

What do we want from Black women on screen?

From Teyana Taylor’s Oscar-nominated turn in One Battle After Another to Industry’s ruthless Harper Stern, Black women are taking on some of the most morally complex roles on screen. But what does “good” representation really mean and must it always be aspirational? Michaela Makusha investigates.

Between Threat and Reality: The National Association for the Advancement of Colored People and the Emergence of Armed Self-Defense in Clarksdale and Natchez, Mississippi, 1960-1965

Annelieke Dirks, Between Threat and Reality: The National Association for the Advancement of Colored People and the Emergence of Armed Self-Defense in Clarksdale and Natchez, Mississippi, 1960-1965, Journal for the Study of Radicalism, Vol. 1, No. 1 (Spring 2007), pp. 71-98

Musk’s AI Grok bot rants about ‘white genocide’ in South Africa in unrelated chats

X chatbot tells users it was ‘instructed by my creators’ to accept ‘white genocide as real and racially motivated’

Grok Can't Apologize. Grok Isn't Sentient. So Why Do Headlines Keep Saying It Did? | Parker Molloy

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