Artificial intelligence bias has become one of the most important challenges facing organizations deploying AI systems.  Bias can emerge from training data, model design, deployment practices, and human decision-making processes. These issues affect hiring, lending, healthcare, law enforcement, education, marketing, and customer service, making AI fairness a critical concern for businesses, policymakers, researchers, and consumers. Understanding AI bias statistics is essential for technology leaders, data scientists, compliance professionals, regulators, HR teams, financial institutions, healthcare organizations, and AI developers. The statistics below highlight the prevalence, impacts, perceptions, and mitigation efforts related to AI bias. Contents General AI Bias Statistics1. 66% of … Continue reading AI Bias Statistics: State of Algorithmic Fairness