AI Definitions: Causal AI
/Causal AI – The application of causal inference principles to AI to uncover connections between data points. The goal is to find cause-and-effect relationships. Causal AI uses methods like A/B testing to gauge the impact of changes in user behavior by manipulating specific factors. The result is more precise insights for decision-making, especially when real-time forecasting is needed. In contrast, predictive AI is focused on finding patterns, considering, for instance, users' preferences based on past behavior and user characteristics. Predictive AI finds correlations and trends, but it doesn’t get at the “why” of results.