55 citations · 77 across the 5 of their papers we have counts for
5 papers
Representational Harms in LLM-Generated Narratives Against Global Majority Nationalities
Ilana Nguyen, Harini Suresh, Thema Monroe-White +1
Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, including simulated interviews…
The Psychosocial Impacts of Generative AI Harms
Faye-Marie Vassel, Evan Shieh, Cassidy R. Sugimoto +1
The rapid emergence of generative Language Models (LMs) has led to growing concern about the impacts that their unexamined adoption may have on the social well-being of diverse use…
Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
Evan Shieh, Faye-Marie Vassel, Cassidy Sugimoto +1
The rapid deployment of generative language models (LMs) has raised concerns about social biases affecting the well-being of diverse consumers. The extant literature on generative…
The Howard-Harvard effect: Institutional reproduction of intersectional inequalities
Diego Kozlowski, Thema Monroe-White, Vincent Larivière +1
The US higher education system concentrates the production of science and scientists within a few institutions. This has implications for minoritized scholars and the topics with w…
Avoiding bias when inferring race using name-based approaches
Diego Kozlowski, Dakota S. Murray, Alexis Bell +4
Racial disparity in academia is a widely acknowledged problem. The quantitative understanding of racial based systemic inequalities is an important step towards a more equitable re…