Resilient AI
Resilient AI refers to the design and implementation of artificial intelligence systems that can maintain functionality, adapt to disruptions, and recover from failures in dynamic or adversarial environments. It focuses on robustness against data corruption, model attacks, and operational challenges to ensure reliable performance. This concept is critical for deploying AI in safety-critical applications like autonomous vehicles, healthcare, and cybersecurity.
Developers should learn about Resilient AI when building AI systems for high-stakes domains where failures could have severe consequences, such as in finance, defense, or infrastructure. It is essential for mitigating risks from adversarial attacks, data drift, and system vulnerabilities, ensuring that AI models remain trustworthy and effective over time. This knowledge helps in creating more secure and dependable AI applications that can withstand real-world uncertainties.