The Presence of Covert Racism in Language Models

In a recent study published in the journal Nature by a team of AI researchers, it was found that popular Language Models (LLMs) exhibit covert racism against individuals who speak African American English (AAE). This study sheds light on the inherent biases embedded in artificial intelligence systems, highlighting the need for further research and development in this area.

The team of researchers, consisting of members from the Allen Institute for AI, Stanford University, and the University of Chicago, trained multiple LLMs on samples of AAE text and examined their responses to user queries. The results of the study revealed a troubling trend of covert racism in the answers provided by these models when presented with AAE text.

Covert Racism in LLMs

Unlike overt racism, which has been addressed through the implementation of filters in LLMs to prevent problematic responses, covert racism is much more subtle and challenging to detect. Covert racism in text often manifests as negative stereotypes and biases that are reflected in the language used by the AI models.

Research Findings

To investigate the presence of covert racism in LLMs, the researchers asked five popular models questions phrased in AAE and standard English. The responses to AAE questions revealed a pattern of negative adjectives such as “dirty,” “lazy,” and “stupid,” while responses to standard English questions contained positive adjectives such as “clean” and “friendly.”

The implications of these findings are significant, especially as LLMs are increasingly being used in various applications such as screening job applicants and police reporting. The research team emphasizes the need for further efforts to eliminate racism from LLM responses and to ensure that these systems do not perpetuate harmful stereotypes and biases.

The study highlights the presence of covert racism in popular LLMs and underscores the importance of addressing bias and discrimination in artificial intelligence systems. As these technologies continue to evolve and play a prominent role in society, it is crucial to prioritize ethical considerations and diversity in AI development.