Text Embeddings Contain Bias. Here's Why That Matters.
Abstract
With the public release of embedding models, it’s important to understand the various biases that they contain. Developers who use them should be aware of the biases inherent in the models as well as how biases can manifest in downstream applications that use these models. In this post, we examine a few specific forms of bias and suggest tools for evaluating as well as mitigating bias.
Research Areas
