Owls are wise and foxes are unfaithful: Uncovering animal stereotypes in vision-language models
This work addresses bias in AI-generated visual content, highlighting an underexplored issue for AI ethics and fairness, though it is incremental as it focuses on a specific domain.
The study investigated whether DALL-E perpetuates animal stereotypes like 'owls as wise' in image generation, finding significant instances where the model consistently produced images aligned with cultural biases.
Animal stereotypes are deeply embedded in human culture and language. They often shape our perceptions and expectations of various species. Our study investigates how animal stereotypes manifest in vision-language models during the task of image generation. Through targeted prompts, we explore whether DALL-E perpetuates stereotypical representations of animals, such as "owls as wise," "foxes as unfaithful," etc. Our findings reveal significant stereotyped instances where the model consistently generates images aligned with cultural biases. The current work is the first of its kind to examine animal stereotyping in vision-language models systematically and to highlight a critical yet underexplored dimension of bias in AI-generated visual content.