In the "AI Ethics" module of IBM Skills' Artificial Intelligence Fundamentals course, we explore how adversarial attacks expose deep vulnerabilities in systems we blindly trust.

 While evasion attacks create camouflaged inputs to deceive classifiers, data poisoning silently corrupts the training process. The paradox is disturbing: the smarter our models become, the more sophisticated the methods to exploit their flaws become.

This technical battle conceals an even greater ethical challenge - how far can we trust systems that can be fooled by nearly imperceptible manipulations?

The real question isn't how to create perfect defenses, but how to manage risks in a world where absolute AI security may be unattainable.