List of Datasets curated for Bias Evaluation with code implementations
With AI getting more integrated into our daily lives, one of the most pressing issues with adopting AI is biases in language models. It is surprising and unsettling to see how AI can pick up and amplify the biases in the data it’s trained on. If you’re a data scientist or machine learning enthusiast, you’ve likely encountered this issue before. You would have built a model that performed well but faced bias and fairness challenges.
To tackle this, various datasets have been specifically curated to evaluate bias in language models. These datasets are systematic tools to measure bias and are essential in creating more equitable AI systems.
Addressing bias isn’t just a technical task — it’s a matter of responsibility.
To simplify things, I have categorized these datasets based on their structure, such as Counterfactual Inputs or Prompts. This categorization will help you choose the right metrics for evaluation. Also, I added a table with a comprehensive view of all the bias evaluation dataset and their capabilities at the end. It will help you choose the right bias evaluation dataset for your use case.