Foundations of AI & Cybersecurity - Lesson 15: Secure Feedback, Audit, and Continuous Improvement

This module explains why AI systems cannot be treated as set-it-and-forget-it tools after deployment. It focuses on model drift, evolving attacker behavior, and the need for secure feedback loops that continuously collect, analyze, update, and re-deploy improvements. Without that cycle, AI becomes less accurate, less safe, and easier to exploit over time.

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