AI Fairness 360: Understand and Mitigate Bias in ML Models
Extensible Open Source Toolkit for Model Fairness
toolkit to detect and mitigate bias in machine learning
The AI Fairness 360 toolkit is an extensible open source toolkit that can help you examine, report, and mitigate discrimination and bias in machine learning models.
The toolkit is a collaborative project of the Linux Foundation's AI and Data Initiative and the Partnership on AI, and it is made available under the Apache 2.0 open source license.
The AI Fairness 360 toolkit is designed to be used by data scientists, machine learning engineers, and other professionals who are working to develop and deploy fair and unbiased machine learning models. The toolkit provides a number of features and functionalities, including:
- A suite of metrics for measuring bias and discrimination in machine learning models
- Algorithms for mitigating bias and discrimination in machine learning models
- A dashboard for visualizing the results of bias and discrimination analyses
The AI Fairness 360 toolkit is a valuable resource for anyone who is working to develop and deploy fair and unbiased machine learning models. The toolkit is easy to use and provides a number of powerful features and functionalities that can help you to identify and mitigate bias in your models.
We hope you will use the AI Fairness 360 toolkit and contribute to it to help engender trust in machine learning.
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