A study of 20 million children shows the fragility of the American Dream.
Our Babies Aren’t 'Bad'—Understanding Autism in Black Children
Too many Black children—especially our Black boys—are being labeled as “bad." Let's get understanding of autism in Black children.
Black Schoolgirls at the Intersection of Consent and Property: Mapping a Socio-Historical Analysis for Anti-Rape Education Futures in Schooling
This article examines how the concept of consent, persons as property, with its links to the convergence of law, imperial governance and schooling reveal the fragility and possibilities of consent ...
Disparities in Autism Ascertainment in Black Children
Tune in to learn about disparities in autism diagnosis and access to supports.
The Racist Beginnings of Standardized Testing | NEA
From grade school to college, students of color have suffered from the effects of biased testing.
Analytic racecraft: Race-based averages create illusory group differences in perceptions of racism.
Expert: The NAACP is Fighting to Keep Black Communities From Becoming AI’s Collateral Damage – The Root
In Fighting for Every Black Child, Did I Betray My Own?
A decade ago, I made a decision about my daughter’s education that I hoped would challenge New York City’s separate and unequal school system. Now 16, she thinks I made the wrong choice.
In Fighting for Every Black Child, Did I Betray My Own?
A decade ago, I made a decision about my daughter’s education that I hoped would challenge New York City’s separate and unequal school system. Now 16, she thinks I made the wrong choice.
News for Black America - NewsOne
Breaking news for and about Black America: politics, original stories, diverse opinions, current events and their impact on Black lives.
Can We Detect the Effects of Racial Violence on Patenting? Reanalyzing an Article by Lisa Cook · Econ Journal Watch : Reanalysis, replication, conflict, innovation
In 2014, Lisa Cook published an article in Journal of Economic Growth titled, “Violence and Economic Activity: Evidence from African American Pa…
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.
Nikole Hannah-Jones’ school choice for her daughter sparks a debate over Black parents, education and sacrifice
Nikole Hannah-Jones's reflection on her daughter’s public school education sparks a larger debate about Black parents, opportunity and community.
Opinion | The Policies of White Resentment (Published 2017)
Trump won on the politics of racial backlash. Now he’s following through with an agenda meant to stoke it further.
Fearing the Black Body
Winner, 2020 Body and Embodiment Best Publication Award, given by the American Sociological AssociationHonorable Mention, 2020 Sociology of Sex and Gender Di...
Toward an Anti-Racist Music Education: A Critical Pedagogy of Popular Music Teacher Education
In this article, we propose a framework for a critical pedagogy of popular music for teacher education to better prepare music teachers to enact anti-racist praxis within their classrooms. Although a growing body of literature in music education addresses issues of racism within the field, fewer scholars have studied this within teacher education. Drawing from critical pedagogy, our framework centers popular music as a means for music teacher educators to interrogate issues of identity and power and (re)contextualize pedagogy, considering the socio-political contexts and communities from which music practices originate. These processes facilitate reflection on how racisms shape taken-for-granted practices within music education by centering the socio-political contexts of popular music. Through our framework, music teacher educators could prompt pre-service music educators to consider the multiple racialized epistemologies of musical value students and teachers bring to the classroom, working toward the possibility of enacting a multicentric approach to music education.
