Fair and Equitable: How IBM Is Removing Bias from AI - DZone AI

As more apps come to market that rely on Artificial Intelligence, software developers and data scientists can unwittingly (or perhaps even knowingly) inject their personal biases into these solutions. This can cause a variety of problems ranging from a poor user experience to major errors in critical decision-making. We at IBM have created a solution specifically to address AI bias. Because flaws and biases may not be easy to detect without the right tool, IBM is deeply committed to delivering services that are unbiased, explainable, value-aligned and transparent. Thus, we are pleased to back up that commitment with the launch of AI Fairness 360, an open-source library to help detect and remove bias in Machine Learning models and data sets.