AI Maintenance: A Robustness Perspective
Pin‐Yu Chen, Payel Das
Abstract
In this article, we carve out artificial intelligence (AI) maintenance from the robustness perspective. Our proposal for AI maintenance facilitates robustness assessment, status tracking, risk scanning, model hardening, and regulation throughout the AI lifecycle, which is an essential milestone toward building sustainable and trustworthy AI ecosystems.
Topics & Concepts
Robustness (evolution)Computer scienceTrustworthinessArtificial intelligenceRisk analysis (engineering)Software engineeringComputer securityBusinessBiochemistryGeneChemistryAdversarial Robustness in Machine LearningAnomaly Detection Techniques and ApplicationsExplainable Artificial Intelligence (XAI)