Robust AI
Robust AI refers to artificial intelligence systems designed to perform reliably and safely under a wide range of conditions, including unexpected inputs, adversarial attacks, and distribution shifts. It focuses on ensuring AI models maintain accuracy, fairness, and security despite uncertainties or perturbations in their operating environment. This concept is crucial for deploying AI in real-world applications where failures could have significant consequences.
Developers should learn about Robust AI when building AI systems for critical domains like healthcare, autonomous vehicles, finance, or cybersecurity, where reliability and safety are paramount. It is essential for mitigating risks such as adversarial examples that can fool models, data drift over time, or biases that lead to unfair outcomes. Understanding Robust AI helps create more trustworthy and resilient applications that can handle edge cases and maintain performance in dynamic environments.