Explainable AI (XAI) has emerged as a critical component of building trust in AI systems. At Data Science Connect, we explore how XAI is bridging the belief gap between humans and machines in AI systems.
Discover the latest trends and best practices in XAI, including model transparency, fairness, and interpretability. Learn how XAI can help organizations build more trustworthy and responsible AI systems, improve human understanding and trust in model decisions, and reduce the risk of errors and bias. Explore real-world examples of how XAI is being used to improve AI’s transparency and accountability.
Rodrigo Aramayo
Global Head of Data Insights & Analytics