ML Model Feedback Security

This question asks if you verify that feedback to your AI system comes from legitimate sources and hasn't been tampered with. When your AI learns from user interactions or corrections, you need to ensure that feedback is genuine - not from bots, hackers, or malicious users trying to corrupt your system. It's like checking IDs at the door to make sure only authorized people can teach your AI new things.

Unverified feedback is an open door for competitors or bad actors to poison your AI. They could systematically feed false information to make your AI perform poorly, damage your reputation, or even use your system for malicious purposes. This vulnerability could turn your self-improving AI into a liability that gets worse over time. Proper authentication protects your investment in AI and maintains the trust of customers who rely on your system's accuracy.

Companies often implement basic user authentication but don't verify the quality or intent of the feedback itself. Another mistake is accepting all feedback equally without considering the source's expertise or history. Many also forget to implement rate limiting, allowing attackers to flood the system with malicious feedback.