Confident AI
It aims to improve trust and reliability in AI/ML systems for users and developers, but appears incremental as it builds on existing concepts without introducing a new paradigm.
The paper tackles the problem of designing AI/ML systems with confidence in predictions and results by proposing 'Confident AI' based on four tenets: Repeatability, Believability, Sufficiency, and Adaptability, which address fundamental issues in current systems.
In this paper, we propose "Confident AI" as a means to designing Artificial Intelligence (AI) and Machine Learning (ML) systems with both algorithm and user confidence in model predictions and reported results. The 4 basic tenets of Confident AI are Repeatability, Believability, Sufficiency, and Adaptability. Each of the tenets is used to explore fundamental issues in current AI/ML systems and together provide an overall approach to Confident AI.