The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models
Year: 2024

‘Scale the model, scale the data, scale the GPU farms’ is the reigning sentiment in the world of generative AI today. While model scaling has been extensively studied, data scaling and its downstream impacts on model performance remain under-explored. This is particularly important in the context of multimodal datasets whose main source is the World Wide Web, condensed and packaged as the Common Crawl dump, which is known to exhibit numerous drawbacks. In this paper, we evaluate the downstream i