What are the common vulnerabilities in AI systems?
An example of an AI chatbot conversation about vulnerabilities in AI systems.
What are the common vulnerabilities in AI systems?
Common vulnerabilities in AI systems include data poisoning, adversarial attacks, and model inversion.
Can you explain data poisoning?
Data poisoning occurs when an attacker manipulates the training data to corrupt the model's learning process.
What are adversarial attacks?
Adversarial attacks involve inputting deceptive data to trick the AI into making incorrect predictions.
How can we protect AI systems from these vulnerabilities?
Protecting AI systems involves robust training, regular audits, and implementing security measures like anomaly detection.
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