<ul><li>Data poisoning occurs when attackers inject malicious data into the training datasets of AI models, compromising their learning process.</li><li>This can lead to skewed outputs, decreased accuracy, and even system failure.</li><li>The rise of generative AI technologies has increased concerns about data poisoning, posing threats to the reliability and safety of AI applications.</li><li>Efforts to combat data poisoning include implementing robust training protocols, continuous monitoring, and enhanced security measures to protect AI systems.</li></ul>

The Dark Side of AI: How Data Poisoning Jeopardizes Technology and Society

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