Importance of Uncertainty Analysis in Artificial Intelligence Predictors and Posterior Decision Making in Construction

Uncertainty analysis is a great forgotten method in systems development for construction applications based on artificial intelligence. Its capabilities to quantify and provide data regarding AI predictions and its consequences down data-driven decision-making processes are often overlooked in academic literature. This paper hopes to highlight the importance of such methods, providing two case studies where uncertainty analysis is performed following Bayesian approaches. The two case studies are computer vision applications for classification and localisation of elements within construction environments. These are taken as representative solutions that have been popular in the field.