👉 Uncertainty engineering is an approach to managing and quantifying the uncertainties inherent in complex systems, particularly those involving AI and machine learning. It involves systematically identifying, quantifying, and mitigating uncertainties in model predictions, data, and system behavior to ensure reliable and robust performance. This process includes techniques such as probabilistic modeling, sensitivity analysis, and scenario planning to understand how variations in inputs or conditions can affect outputs. By acknowledging and addressing these uncertainties, uncertainty engineering helps build more resilient systems, improve decision-making, and enhance trust in AI-driven solutions.
