In this section, we delve into examples of racialized names and biases in AI-generated content. We show the most common names generated by race, emphasizing how non-white characters are omitted or subordinated in both neutral and power-laden scenarios. Additionally, we provide examples of AI-generated text that reflect racial, socioeconomic, and geographic prejudices, exploring how these factors intersect with stereotypes such as saviorism.
Our company, Q2BSTUDIO, specializes in technology development and services to address these issues and promote equity and diversity in the field of artificial intelligence.
