Most contemporary artificial intelligence (AI) systems learn to complete tasks via machine learning and deep learning.

Researchers at KAIST have developed a neurodevelopment-inspired training method that reduces overconfidence in AI predictions by briefly exposing models to random noise before task-specific data. The ...

A new approach has been proposed to address the problem of “overconfidence”—one of the most critical risks of artificial intelligence (AI) in areas ...

With the rising popularity of AI, particularly Large Language Models (LLMs), there has been a lot of talk about bias. Since AI is made by humans, our cognitive shortcomings can easily creep into AI ...