IBM continues momentum in AI and trust leadership - DevOps.com

IBM continues to serve as an industry leader in advancing what we call Trusted AI, focused on developing diverse approaches that implement elements of fairness, explainability, and accountability across the entire lifecycle of an AI application. Under our Trusted AI efforts, IBM released in 2018 the AI Fairness 360 toolkit (AIF360), which is an extensible, open source toolkit that can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. It contains over 70 fairness metrics and 11 state-of-the-art bias mitigation algorithms developed by the research community, and it is designed to translate algorithmic research from the lab into the actual practice of domains as wide-ranging as finance, human capital management, healthcare, and education. Now, IBM is adding two new ways in which AIF360 is becoming even more accessible for a wider range of developers, as well as increased functionality: compatibility with scikit-learn and R. AI fairness is an important topic as machine learning models are increasingly used for high-stakes decisions. Machine learning discovers and generalizes patterns in the data and therefore, could replicate systematic advantages of privileged groups.