Examining Gender and Racial Bias in Large Vision–Language Models Using a Novel Dataset of Parallel Images (2024.eacl-long)
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| Challenge: | a new wave of large vision–language models (LVLMs) incorporate images as input in addition to text . a recent study examined potential gender and racial biases in such systems based on the perceived characteristics of the people in the input images. |
| Approach: | They examine potential gender and racial biases in large vision–language models . they query a dataset of AI-generated images of people to see whether they differ . |
| Outcome: | The proposed dataset shows that the images differ in gender and race according to the perceived characteristics of the person depicted. |
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