The market for AI training datasets has gained substantial traction, with the major catalyst being the need for fair and unbiased datasets. Enterprises are gradually realizing the implications of bias within the dataset. Such bias was highlighted in the case of the Apple Card, where women were given lower credit limits than men due to biased training data embedded in the credit disbursal algorithms. Large language models have also been criticized for making negative stereotypes, such as when OpenAI's GPT-3 unintentionally linked objectionable words to certain ethnic groups