👉 Confidence computing is an emerging framework that aims to quantify and communicate the reliability of AI predictions, particularly in scenarios where uncertainty is significant. It goes beyond traditional accuracy metrics by providing a probabilistic measure of confidence, often represented through techniques like Bayesian neural networks or ensemble methods. This approach allows users to understand not just whether a prediction is correct, but how certain they are about it, which is crucial in high-stakes applications such as healthcare, finance, and autonomous systems. By offering a nuanced view of prediction reliability, confidence computing enhances decision-making processes, enabling more informed and cautious actions when AI outputs are uncertain.
