Definition
An adversarial example is a specially crafted input designed to trick an artificial intelligence model into making an incorrect prediction or classification. These inputs are often imperceptible to humans but cause significant deviations in the AI's output. Adversarial examples exploit vulnerabilities in how AI models learn and generalize from data, making them a critical concern in AI security. For instance, a few strategically placed pixels on an image could cause an AI to misidentify a stop sign as a speed limit sign. This differs from simple data noise, which is random and unintentional. Understanding adversarial examples is essential for securing AI systems and is relevant for certifications like CompTIA Security+ and AWS Certified Security Specialty.