MIT study: Selective regression method improves AI accuracy

Knowing when to trust a model's predictions is not always an easy challenge for professionals who use machine-learning models to aid in decision-making, especially since these models are frequently so complicated that their inner workings remain a mystery. Selective regression is a method in which the model calculates its confidence level for each prediction and rejects predictions if its confidence is too low. After then, a person can look over those situations, gather further data, and manually decide on each one. While researchers are working on new models, regulators are trying to set a standard in the usage of artificial intelligence. Two months ago we discussed the EU AI Act and now the UK prepares the AI rulebook.