The AI Fairness 360 toolkit is an open-source, flexible library that contains methods created by the research community to assist in identifying and reducing bias in machine learning models over the course of the AI application lifecycle. Python and R versions of the AI Fairness 360 package are both available.
Included in the AI Fairness 360 are the features:
– A complete collection of measures for testing biases in datasets and models.
– The rationales behind these measurements.
– Models and datasets bias mitigation algorithms. Its goal is to move algorithmic research from the lab into real-world applications in a variety of industries, including banking, human capital management, healthcare, and education.
Our team is dedicated to the moral and legitimate application of AI technologies, assisting companies in identifying and controlling any biases. In order to promote trust between humans and technology, we support moral AI practices.
AI Fairness 360 is an open source toolkit that can be used to identify, assess, and reduce bias and discrimination in machine learning models. It includes algorithms created by the research community and metrics such as Theil index, Euclidean distance, Manhattan distance, Mahalanobis distance, and others.
It can also evaluate many characteristics of individual and group fairness, such as statistical parity difference, equal opportunity difference, average chances difference, differential impact, and more. All of these are readily available to help you with anything associated with AI ethics and the like.
Our team of pros at Virtuous AI can assist you with all your AI Fairness 360-related concerns. We have just the right team of people who can work together with you and your business to achieve all your technological goals.
Contact us today to get a free consultation!